diff --git a/AD450_math.py b/AD450_math.py new file mode 100644 index 0000000..481036f --- /dev/null +++ b/AD450_math.py @@ -0,0 +1,6 @@ +def add(num1, num2): + return num1 + num2 + +def multiply(num1, num2): + return num1 * num2 + diff --git a/data_processing.py b/data_processing.py new file mode 100644 index 0000000..20064bc --- /dev/null +++ b/data_processing.py @@ -0,0 +1,65 @@ +# This file is used by week_7 +import pandas as pd + +# Problem 1 +def rename_columns(df_raw): + """ + Convert blank spaces to _ + Convert everything into lower case + Remove trailing and leading spaces + Return a new DataFrame object + + I noticed you need to use strip() before replace otherwise it would replace any + leading or trailing spaces with a _ + """ + df_raw.rename(columns={"original_titlê":"original_title", "Genrë¨":"genre", "Unnamed:_8":"unnamed_8"}, inplace=True) + df_raw.columns = df_raw.columns.str.strip() + df_raw.columns = df_raw.columns.str.replace(' ', '_') + df_raw.columns = df_raw.columns.str.lower() + return df_raw + +# Problem #2 +def remove_fully_null_columns_rows(df_raw): + """ + Remove rows that are completely null + Remove columns that are completely null + Return a new DataFrame object + """ + df_raw = df_raw.dropna(how="all") + df_raw = df_raw.dropna(axis="columns", how="all") + return df_raw + +# Problem #3 +def clean_and_fill_content_rating(df_raw): + """ + Convert all NaN values in content_rating to "Unrated" + Convert all "Not Rated" with "Unrated" + Return a new DataFrame object + """ + df_raw.loc[df_raw["content_rating"].isnull(), "content_rating"] = "Unrated" + df_raw.loc[df_raw["content_rating"] == "Not Rated", "content_rating"] = "Unrated" + return df_raw + +# Problem #4 +def clean_release_year(df_raw): + """ + Add new column "release_year_coerce", use pd.to_datetime with errors="coerce" + Add new column "release_year_mixed", use pd.to_datetime with errors="coerce" and format="mixed" + Return a new DataFrame object + """ + df_raw["release_year_coerce"] = pd.to_datetime(df_raw["release_year"], errors="coerce") + df_raw["release_year_mixed"] = pd.to_datetime(df_raw["release_year"], errors="coerce", format="mixed", dayfirst=True) + return df_raw + +# Problem #5 +def clean_income(df_raw): + """ + Remove $, commas and other issues and covert to an int + Return a new DataFrame object + """ + df_raw["income"] = df_raw["income"].str.replace(r'[$,]','', regex=True) + df_raw["income"] = df_raw["income"].str.replace('o', '0', regex=False) + df_raw["income"] = df_raw["income"].astype("Int64") + return df_raw + + diff --git a/generate_week_10_data.py b/generate_week_10_data.py index 692a630..6c68ed6 100644 --- a/generate_week_10_data.py +++ b/generate_week_10_data.py @@ -4,8 +4,16 @@ def create_data(): np.random.seed(10) - word_file = "/usr/share/dict/words" - WORDS = open(word_file).read().splitlines() + """ + /usr/share/dict/words cannot be found so I created the try/except block below + and hard coded an array of names in the except block + """ + try: + word_file = "/usr/share/dict/words" + WORDS = open(word_file).read().splitlines() + except: + WORDS = ["Liam", "Ava", "Noah", "Mia", "Ethan", "Sophia", "Mason", "Isabella", "Lucas", "Emma", + "Jackson", "Olivia", "Aiden", "Charlotte", "Elijah", "Amelia", "James", "Harper", "Benjamin"] customers = pd.DataFrame({"customer_id": np.arange(1,11), "customer_age": np.random.uniform(0, 12*3, 10), "customer_name": [WORDS[i] for i in np.random.randint(1, len(WORDS), 10)]}) diff --git a/mortality_data.csv b/mortality_data.csv new file mode 100644 index 0000000..69e489a --- /dev/null +++ b/mortality_data.csv @@ -0,0 +1,477 @@ +Year,Age Group,Death Rate +1900,1-4 Years,1983.8 +1901,1-4 Years,1695.0 +1902,1-4 Years,1655.7 +1903,1-4 Years,1542.1 +1904,1-4 Years,1591.5 +1905,1-4 Years,1498.9 +1906,1-4 Years,1580.0 +1907,1-4 Years,1468.3 +1908,1-4 Years,1396.8 +1909,1-4 Years,1348.9 +1910,1-4 Years,1397.3 +1911,1-4 Years,1176.0 +1912,1-4 Years,1094.1 +1913,1-4 Years,1193.4 +1914,1-4 Years,1024.2 +1915,1-4 Years,924.2 +1916,1-4 Years,1111.5 +1917,1-4 Years,1066.0 +1918,1-4 Years,1573.5 +1919,1-4 Years,928.0 +1920,1-4 Years,987.2 +1921,1-4 Years,801.2 +1922,1-4 Years,742.0 +1923,1-4 Years,806.7 +1924,1-4 Years,683.2 +1925,1-4 Years,641.0 +1926,1-4 Years,723.4 +1927,1-4 Years,591.0 +1928,1-4 Years,647.5 +1929,1-4 Years,625.5 +1930,1-4 Years,563.6 +1931,1-4 Years,526.6 +1932,1-4 Years,461.9 +1933,1-4 Years,472.6 +1934,1-4 Years,507.7 +1935,1-4 Years,440.9 +1936,1-4 Years,439.8 +1937,1-4 Years,418.7 +1938,1-4 Years,383.8 +1939,1-4 Years,318.3 +1940,1-4 Years,289.6 +1941,1-4 Years,279.9 +1942,1-4 Years,243.4 +1943,1-4 Years,256.4 +1944,1-4 Years,233.0 +1945,1-4 Years,203.0 +1946,1-4 Years,181.5 +1947,1-4 Years,160.8 +1948,1-4 Years,160.1 +1949,1-4 Years,150.2 +1950,1-4 Years,139.4 +1951,1-4 Years,136.9 +1952,1-4 Years,141.1 +1953,1-4 Years,130.0 +1954,1-4 Years,118.3 +1955,1-4 Years,113.4 +1956,1-4 Years,110.2 +1957,1-4 Years,111.8 +1958,1-4 Years,111.7 +1959,1-4 Years,106.9 +1960,1-4 Years,109.1 +1961,1-4 Years,101.7 +1962,1-4 Years,99.2 +1963,1-4 Years,101.5 +1964,1-4 Years,98.5 +1965,1-4 Years,95.9 +1966,1-4 Years,96.4 +1967,1-4 Years,89.4 +1968,1-4 Years,89.6 +1969,1-4 Years,88.0 +1970,1-4 Years,84.5 +1971,1-4 Years,82.3 +1972,1-4 Years,80.4 +1973,1-4 Years,79.0 +1974,1-4 Years,73.3 +1975,1-4 Years,69.9 +1976,1-4 Years,68.8 +1977,1-4 Years,67.6 +1978,1-4 Years,67.9 +1979,1-4 Years,64.2 +1980,1-4 Years,63.9 +1981,1-4 Years,60.6 +1982,1-4 Years,58.2 +1983,1-4 Years,56.1 +1984,1-4 Years,52.2 +1985,1-4 Years,51.8 +1986,1-4 Years,52.4 +1987,1-4 Years,52.1 +1988,1-4 Years,51.5 +1989,1-4 Years,49.8 +1990,1-4 Years,46.8 +1991,1-4 Years,47.4 +1992,1-4 Years,43.5 +1993,1-4 Years,44.6 +1994,1-4 Years,42.7 +1995,1-4 Years,40.4 +1996,1-4 Years,38.0 +1997,1-4 Years,35.5 +1998,1-4 Years,34.1 +1999,1-4 Years,34.2 +2000,1-4 Years,32.4 +2001,1-4 Years,33.4 +2002,1-4 Years,31.4 +2003,1-4 Years,31.8 +2004,1-4 Years,30.3 +2005,1-4 Years,29.9 +2006,1-4 Years,29.1 +2007,1-4 Years,29.4 +2008,1-4 Years,29.3 +2009,1-4 Years,27.4 +2010,1-4 Years,26.5 +2011,1-4 Years,26.3 +2012,1-4 Years,26.3 +2013,1-4 Years,25.5 +2014,1-4 Years,24.0 +2015,1-4 Years,24.9 +2016,1-4 Years,25.3 +2017,1-4 Years,24.3 +2018,1-4 Years,24.0 +1900,5-9 Years,466.1 +1901,5-9 Years,427.6 +1902,5-9 Years,403.3 +1903,5-9 Years,414.7 +1904,5-9 Years,425.0 +1905,5-9 Years,396.3 +1906,5-9 Years,377.4 +1907,5-9 Years,365.6 +1908,5-9 Years,354.2 +1909,5-9 Years,330.2 +1910,5-9 Years,348.4 +1911,5-9 Years,310.0 +1912,5-9 Years,287.5 +1913,5-9 Years,317.7 +1914,5-9 Years,291.6 +1915,5-9 Years,260.6 +1916,5-9 Years,282.4 +1917,5-9 Years,290.7 +1918,5-9 Years,447.9 +1919,5-9 Years,300.0 +1920,5-9 Years,295.2 +1921,5-9 Years,281.4 +1922,5-9 Years,239.6 +1923,5-9 Years,240.0 +1924,5-9 Years,221.7 +1925,5-9 Years,211.5 +1926,5-9 Years,213.8 +1927,5-9 Years,208.3 +1928,5-9 Years,213.1 +1929,5-9 Years,208.0 +1930,5-9 Years,189.8 +1931,5-9 Years,182.0 +1932,5-9 Years,165.9 +1933,5-9 Years,161.3 +1934,5-9 Years,165.1 +1935,5-9 Years,162.4 +1936,5-9 Years,154.6 +1937,5-9 Years,142.9 +1938,5-9 Years,128.8 +1939,5-9 Years,112.6 +1940,5-9 Years,108.3 +1941,5-9 Years,103.8 +1942,5-9 Years,96.1 +1943,5-9 Years,103.1 +1944,5-9 Years,98.7 +1945,5-9 Years,93.6 +1946,5-9 Years,85.6 +1947,5-9 Years,73.3 +1948,5-9 Years,70.6 +1949,5-9 Years,68.2 +1950,5-9 Years,61.7 +1951,5-9 Years,61.7 +1952,5-9 Years,61.3 +1953,5-9 Years,56.1 +1954,5-9 Years,52.5 +1955,5-9 Years,50.6 +1956,5-9 Years,48.3 +1957,5-9 Years,50.1 +1958,5-9 Years,48.4 +1959,5-9 Years,49.4 +1960,5-9 Years,49.0 +1961,5-9 Years,45.8 +1962,5-9 Years,45.6 +1963,5-9 Years,45.3 +1964,5-9 Years,44.6 +1965,5-9 Years,43.9 +1966,5-9 Years,44.3 +1967,5-9 Years,42.9 +1968,5-9 Years,44.5 +1969,5-9 Years,44.0 +1970,5-9 Years,42.1 +1971,5-9 Years,42.0 +1972,5-9 Years,40.8 +1973,5-9 Years,41.1 +1974,5-9 Years,37.2 +1975,5-9 Years,35.2 +1976,5-9 Years,34.1 +1977,5-9 Years,33.3 +1978,5-9 Years,32.7 +1979,5-9 Years,31.1 +1980,5-9 Years,30.4 +1981,5-9 Years,29.1 +1982,5-9 Years,28.3 +1983,5-9 Years,26.5 +1984,5-9 Years,25.3 +1985,5-9 Years,25.0 +1986,5-9 Years,23.9 +1987,5-9 Years,24.7 +1988,5-9 Years,24.5 +1989,5-9 Years,24.1 +1990,5-9 Years,22.2 +1991,5-9 Years,21.5 +1992,5-9 Years,20.3 +1993,5-9 Years,21.0 +1994,5-9 Years,19.7 +1995,5-9 Years,19.4 +1996,5-9 Years,19.0 +1997,5-9 Years,18.0 +1998,5-9 Years,17.2 +1999,5-9 Years,16.9 +2000,5-9 Years,15.8 +2001,5-9 Years,15.3 +2002,5-9 Years,15.2 +2003,5-9 Years,14.8 +2004,5-9 Years,14.8 +2005,5-9 Years,14.6 +2006,5-9 Years,14.0 +2007,5-9 Years,13.8 +2008,5-9 Years,12.6 +2009,5-9 Years,12.5 +2010,5-9 Years,11.5 +2011,5-9 Years,12.1 +2012,5-9 Years,11.4 +2013,5-9 Years,11.8 +2014,5-9 Years,11.5 +2015,5-9 Years,11.7 +2016,5-9 Years,12.2 +2017,5-9 Years,11.6 +2018,5-9 Years,11.5 +1900,10-14 Years,298.3 +1901,10-14 Years,273.6 +1902,10-14 Years,252.5 +1903,10-14 Years,268.2 +1904,10-14 Years,305.2 +1905,10-14 Years,279.8 +1906,10-14 Years,272.2 +1907,10-14 Years,265.8 +1908,10-14 Years,247.9 +1909,10-14 Years,230.5 +1910,10-14 Years,235.9 +1911,10-14 Years,222.2 +1912,10-14 Years,202.2 +1913,10-14 Years,214.8 +1914,10-14 Years,207.2 +1915,10-14 Years,196.7 +1916,10-14 Years,205.1 +1917,10-14 Years,218.9 +1918,10-14 Years,375.1 +1919,10-14 Years,236.4 +1920,10-14 Years,229.9 +1921,10-14 Years,209.9 +1922,10-14 Years,186.6 +1923,10-14 Years,188.2 +1924,10-14 Years,179.8 +1925,10-14 Years,181.0 +1926,10-14 Years,171.4 +1927,10-14 Years,167.5 +1928,10-14 Years,173.8 +1929,10-14 Years,165.0 +1930,10-14 Years,152.8 +1931,10-14 Years,150.3 +1932,10-14 Years,142.2 +1933,10-14 Years,138.0 +1934,10-14 Years,141.5 +1935,10-14 Years,143.4 +1936,10-14 Years,141.0 +1937,10-14 Years,128.3 +1938,10-14 Years,113.8 +1939,10-14 Years,106.5 +1940,10-14 Years,99.5 +1941,10-14 Years,94.7 +1942,10-14 Years,85.8 +1943,10-14 Years,90.6 +1944,10-14 Years,89.7 +1945,10-14 Years,86.8 +1946,10-14 Years,78.6 +1947,10-14 Years,67.9 +1948,10-14 Years,65.6 +1949,10-14 Years,63.6 +1950,10-14 Years,58.1 +1951,10-14 Years,56.4 +1952,10-14 Years,56.8 +1953,10-14 Years,53.1 +1954,10-14 Years,47.8 +1955,10-14 Years,46.6 +1956,10-14 Years,46.3 +1957,10-14 Years,47.4 +1958,10-14 Years,44.6 +1959,10-14 Years,45.8 +1960,10-14 Years,44.0 +1961,10-14 Years,41.9 +1962,10-14 Years,41.9 +1963,10-14 Years,41.2 +1964,10-14 Years,41.6 +1965,10-14 Years,40.5 +1966,10-14 Years,41.1 +1967,10-14 Years,40.5 +1968,10-14 Years,41.6 +1969,10-14 Years,41.3 +1970,10-14 Years,40.6 +1971,10-14 Years,39.9 +1972,10-14 Years,40.4 +1973,10-14 Years,40.3 +1974,10-14 Years,38.3 +1975,10-14 Years,35.3 +1976,10-14 Years,34.2 +1977,10-14 Years,34.6 +1978,10-14 Years,33.7 +1979,10-14 Years,31.8 +1980,10-14 Years,30.8 +1981,10-14 Years,29.5 +1982,10-14 Years,28.2 +1983,10-14 Years,27.3 +1984,10-14 Years,28.3 +1985,10-14 Years,28.0 +1986,10-14 Years,28.6 +1987,10-14 Years,27.1 +1988,10-14 Years,27.7 +1989,10-14 Years,27.4 +1990,10-14 Years,26.0 +1991,10-14 Years,25.6 +1992,10-14 Years,24.4 +1993,10-14 Years,25.3 +1994,10-14 Years,24.8 +1995,10-14 Years,25.1 +1996,10-14 Years,23.4 +1997,10-14 Years,22.5 +1998,10-14 Years,21.5 +1999,10-14 Years,20.4 +2000,10-14 Years,20.3 +2001,10-14 Years,19.1 +2002,10-14 Years,19.4 +2003,10-14 Years,18.9 +2004,10-14 Years,18.4 +2005,10-14 Years,17.7 +2006,10-14 Years,16.2 +2007,10-14 Years,16.5 +2008,10-14 Years,15.2 +2009,10-14 Years,15.1 +2010,10-14 Years,14.3 +2011,10-14 Years,14.2 +2012,10-14 Years,13.9 +2013,10-14 Years,14.1 +2014,10-14 Years,14.0 +2015,10-14 Years,14.6 +2016,10-14 Years,14.6 +2017,10-14 Years,15.5 +2018,10-14 Years,14.9 +1900,15-19 Years,484.8 +1901,15-19 Years,454.4 +1902,15-19 Years,421.5 +1903,15-19 Years,434.1 +1904,15-19 Years,471.4 +1905,15-19 Years,439.3 +1906,15-19 Years,445.2 +1907,15-19 Years,437.7 +1908,15-19 Years,397.7 +1909,15-19 Years,363.6 +1910,15-19 Years,371.9 +1911,15-19 Years,366.0 +1912,15-19 Years,347.2 +1913,15-19 Years,360.3 +1914,15-19 Years,340.5 +1915,15-19 Years,330.9 +1916,15-19 Years,355.8 +1917,15-19 Years,380.3 +1918,15-19 Years,777.4 +1919,15-19 Years,438.5 +1920,15-19 Years,402.9 +1921,15-19 Years,326.5 +1922,15-19 Years,319.6 +1923,15-19 Years,325.8 +1924,15-19 Years,313.5 +1925,15-19 Years,314.0 +1926,15-19 Years,307.5 +1927,15-19 Years,289.5 +1928,15-19 Years,307.8 +1929,15-19 Years,298.0 +1930,15-19 Years,277.8 +1931,15-19 Years,263.5 +1932,15-19 Years,237.5 +1933,15-19 Years,223.4 +1934,15-19 Years,224.0 +1935,15-19 Years,222.3 +1936,15-19 Years,230.4 +1937,15-19 Years,219.0 +1938,15-19 Years,192.3 +1939,15-19 Years,179.8 +1940,15-19 Years,171.6 +1941,15-19 Years,169.0 +1942,15-19 Years,154.7 +1943,15-19 Years,164.0 +1944,15-19 Years,157.9 +1945,15-19 Years,152.3 +1946,15-19 Years,137.8 +1947,15-19 Years,126.8 +1948,15-19 Years,118.7 +1949,15-19 Years,111.8 +1950,15-19 Years,108.6 +1951,15-19 Years,108.9 +1952,15-19 Years,114.4 +1953,15-19 Years,106.9 +1954,15-19 Years,96.1 +1955,15-19 Years,97.3 +1956,15-19 Years,97.2 +1957,15-19 Years,100.2 +1958,15-19 Years,91.5 +1959,15-19 Years,92.8 +1960,15-19 Years,92.2 +1961,15-19 Years,88.1 +1962,15-19 Years,87.6 +1963,15-19 Years,90.5 +1964,15-19 Years,93.9 +1965,15-19 Years,95.3 +1966,15-19 Years,102.0 +1967,15-19 Years,102.1 +1968,15-19 Years,108.1 +1969,15-19 Years,113.5 +1970,15-19 Years,110.3 +1971,15-19 Years,110.3 +1972,15-19 Years,110.4 +1973,15-19 Years,111.0 +1974,15-19 Years,104.8 +1975,15-19 Years,100.2 +1976,15-19 Years,95.7 +1977,15-19 Years,99.8 +1978,15-19 Years,98.9 +1979,15-19 Years,98.8 +1980,15-19 Years,97.9 +1981,15-19 Years,90.0 +1982,15-19 Years,85.4 +1983,15-19 Years,81.1 +1984,15-19 Years,80.4 +1985,15-19 Years,80.5 +1986,15-19 Years,86.2 +1987,15-19 Years,83.5 +1988,15-19 Years,86.7 +1989,15-19 Years,85.9 +1990,15-19 Years,87.9 +1991,15-19 Years,88.7 +1992,15-19 Years,83.6 +1993,15-19 Years,85.8 +1994,15-19 Years,85.5 +1995,15-19 Years,82.1 +1996,15-19 Years,77.5 +1997,15-19 Years,73.6 +1998,15-19 Years,69.5 +1999,15-19 Years,68.6 +2000,15-19 Years,67.1 +2001,15-19 Years,66.3 +2002,15-19 Years,67.0 +2003,15-19 Years,65.4 +2004,15-19 Years,64.9 +2005,15-19 Years,63.8 +2006,15-19 Years,63.0 +2007,15-19 Years,60.3 +2008,15-19 Years,55.9 +2009,15-19 Years,51.9 +2010,15-19 Years,49.4 +2011,15-19 Years,48.9 +2012,15-19 Years,47.2 +2013,15-19 Years,44.8 +2014,15-19 Years,45.5 +2015,15-19 Years,48.3 +2016,15-19 Years,51.2 +2017,15-19 Years,51.5 +2018,15-19 Years,49.2 diff --git a/week_10_agg.ipynb b/week_10_agg.ipynb index ea6acd2..9ce1f0f 100644 --- a/week_10_agg.ipynb +++ b/week_10_agg.ipynb @@ -65,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -159,7 +159,7 @@ " Primates 0.0 NaN 0 0.0" ] }, - "execution_count": 1, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -186,7 +186,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -276,7 +276,7 @@ " Primates 0.0 " ] }, - "execution_count": 2, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -288,7 +288,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 62, "metadata": {}, "outputs": [ { @@ -375,7 +375,7 @@ "3 0.0 " ] }, - "execution_count": 3, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } @@ -399,7 +399,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 63, "metadata": {}, "outputs": [], "source": [ @@ -423,10 +423,845 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 64, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "'customers'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
customer_idcustomer_agecustomer_name
0127.767543septal
120.747070lamnectomy
2322.811336digitogenin
3426.956940shita
4517.946252dermatoma
568.092679tasselet
677.130263chyloid
7827.379106amputator
896.087990receivership
9103.180233rapscallionly
\n", + "
" + ], + "text/plain": [ + " customer_id customer_age customer_name\n", + "0 1 27.767543 septal\n", + "1 2 0.747070 lamnectomy\n", + "2 3 22.811336 digitogenin\n", + "3 4 26.956940 shita\n", + "4 5 17.946252 dermatoma\n", + "5 6 8.092679 tasselet\n", + "6 7 7.130263 chyloid\n", + "7 8 27.379106 amputator\n", + "8 9 6.087990 receivership\n", + "9 10 3.180233 rapscallionly" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'orders'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
order_idcustomer_idorder_amount
019300.700057
125113.984362
232828.681326
34446.896319
457626.287148
566547.586156
674819.286996
7810198.947540
897856.850302
91010351.652639
10112754.647692
111210295.961707
12135883.936480
13143325.511638
14157165.015898
15168392.529244
1617993.460375
17189821.105658
181910151.152020
19203384.114449
\n", + "
" + ], + "text/plain": [ + " order_id customer_id order_amount\n", + "0 1 9 300.700057\n", + "1 2 5 113.984362\n", + "2 3 2 828.681326\n", + "3 4 4 46.896319\n", + "4 5 7 626.287148\n", + "5 6 6 547.586156\n", + "6 7 4 819.286996\n", + "7 8 10 198.947540\n", + "8 9 7 856.850302\n", + "9 10 10 351.652639\n", + "10 11 2 754.647692\n", + "11 12 10 295.961707\n", + "12 13 5 883.936480\n", + "13 14 3 325.511638\n", + "14 15 7 165.015898\n", + "15 16 8 392.529244\n", + "16 17 9 93.460375\n", + "17 18 9 821.105658\n", + "18 19 10 151.152020\n", + "19 20 3 384.114449" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'web_visits'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
interaction_iddatecustomer_idtime_on_pagevisitor_id
012024-05-011.077.383030124.0
122024-05-01NaN3.995921924.0
232024-05-01NaN42.94921883.0
342024-05-01NaN31.49268763.0
452024-05-029.063.6491141116.0
562024-05-02NaN34.634715590.0
672024-05-02NaN4.309736507.0
782024-05-02NaN87.991517364.0
892024-05-022.076.324059248.0
9102024-05-03NaN87.809664374.0
10112024-05-03NaN41.750914990.0
11122024-05-039.060.5577561116.0
12132024-05-0310.051.3466631240.0
13142024-05-036.059.783665744.0
14152024-05-041.026.221566124.0
15162024-05-04NaN30.087131422.0
16172024-05-044.02.539978496.0
17182024-05-04NaN30.306256918.0
18192024-05-04NaN24.207588930.0
19202024-05-05NaN55.757819608.0
\n", + "
" + ], + "text/plain": [ + " interaction_id date customer_id time_on_page visitor_id\n", + "0 1 2024-05-01 1.0 77.383030 124.0\n", + "1 2 2024-05-01 NaN 3.995921 924.0\n", + "2 3 2024-05-01 NaN 42.949218 83.0\n", + "3 4 2024-05-01 NaN 31.492687 63.0\n", + "4 5 2024-05-02 9.0 63.649114 1116.0\n", + "5 6 2024-05-02 NaN 34.634715 590.0\n", + "6 7 2024-05-02 NaN 4.309736 507.0\n", + "7 8 2024-05-02 NaN 87.991517 364.0\n", + "8 9 2024-05-02 2.0 76.324059 248.0\n", + "9 10 2024-05-03 NaN 87.809664 374.0\n", + "10 11 2024-05-03 NaN 41.750914 990.0\n", + "11 12 2024-05-03 9.0 60.557756 1116.0\n", + "12 13 2024-05-03 10.0 51.346663 1240.0\n", + "13 14 2024-05-03 6.0 59.783665 744.0\n", + "14 15 2024-05-04 1.0 26.221566 124.0\n", + "15 16 2024-05-04 NaN 30.087131 422.0\n", + "16 17 2024-05-04 4.0 2.539978 496.0\n", + "17 18 2024-05-04 NaN 30.306256 918.0\n", + "18 19 2024-05-04 NaN 24.207588 930.0\n", + "19 20 2024-05-05 NaN 55.757819 608.0" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'ad_clicks'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
click_iddatead_idcustomer_idexternal_user_id
012024-05-0357768.0790344.0
122024-05-0344298.0790344.0
232024-05-04544210.0987930.0
342024-05-0467038.0790344.0
452024-05-0477921.098793.0
562024-05-0588934.0395172.0
672024-05-05337610.0987930.0
782024-05-051412NaN804651.0
892024-05-0622795.0493965.0
9102024-05-0659737.0691551.0
10112024-05-068710NaN274479.0
11122024-05-071985NaN292769.0
12132024-05-07735010.0987930.0
13142024-05-0763333.0296379.0
14152024-05-0850302.0197586.0
15162024-05-086133NaN713915.0
16172024-05-0847537.0691551.0
17182024-05-093564NaN667001.0
18192024-05-097871NaN498478.0
19202024-05-097684NaN47123.0
\n", + "
" + ], + "text/plain": [ + " click_id date ad_id customer_id external_user_id\n", + "0 1 2024-05-03 5776 8.0 790344.0\n", + "1 2 2024-05-03 4429 8.0 790344.0\n", + "2 3 2024-05-04 5442 10.0 987930.0\n", + "3 4 2024-05-04 6703 8.0 790344.0\n", + "4 5 2024-05-04 7792 1.0 98793.0\n", + "5 6 2024-05-05 8893 4.0 395172.0\n", + "6 7 2024-05-05 3376 10.0 987930.0\n", + "7 8 2024-05-05 1412 NaN 804651.0\n", + "8 9 2024-05-06 2279 5.0 493965.0\n", + "9 10 2024-05-06 5973 7.0 691551.0\n", + "10 11 2024-05-06 8710 NaN 274479.0\n", + "11 12 2024-05-07 1985 NaN 292769.0\n", + "12 13 2024-05-07 7350 10.0 987930.0\n", + "13 14 2024-05-07 6333 3.0 296379.0\n", + "14 15 2024-05-08 5030 2.0 197586.0\n", + "15 16 2024-05-08 6133 NaN 713915.0\n", + "16 17 2024-05-08 4753 7.0 691551.0\n", + "17 18 2024-05-09 3564 NaN 667001.0\n", + "18 19 2024-05-09 7871 NaN 498478.0\n", + "19 20 2024-05-09 7684 NaN 47123.0" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\"\"\" \n", + "I created a second code box below with the answer to this question as \n", + "I wanted to see all of the dataframes printed out. \n", + "\"\"\"\n", + "\n", + "display(\"customers\")\n", + "display(customers)\n", + "display('orders')\n", + "display(orders)\n", + "display('web_visits')\n", + "display(web_visits)\n", + "display('ad_clicks')\n", + "display(ad_clicks)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "customer_name\n", + "amputator 392.529244\n", + "chyloid 1648.153348\n", + "dermatoma 997.920841\n", + "digitogenin 709.626087\n", + "lamnectomy 1583.329018\n", + "rapscallionly 997.713906\n", + "receivership 1215.266089\n", + "shita 866.183315\n", + "tasselet 547.586156\n", + "Name: order_amount, dtype: float64" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "customer_name\n", + "amputator 392.529244\n", + "chyloid 1648.153348\n", + "dermatoma 997.920841\n", + "digitogenin 709.626087\n", + "lamnectomy 1583.329018\n", + "rapscallionly 997.713906\n", + "receivership 1215.266089\n", + "septal 0.000000\n", + "shita 866.183315\n", + "tasselet 547.586156\n", + "Name: order_amount, dtype: float64" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customers_and_orders = pd.merge(customers, orders, on=\"customer_id\", how=\"inner\")\n", + "question_1_1 = customers_and_orders.groupby(\"customer_name\")[\"order_amount\"].sum()\n", + "\n", + "customers_and_orders2 = pd.merge(customers, orders, on=\"customer_id\", how=\"left\")\n", + "question_1_2 = customers_and_orders2.groupby(\"customer_name\")[\"order_amount\"].sum()\n", + "\n", + "\n", + "\n", + "display(question_1_1)\n", + "display(question_1_2)\n" + ] }, { "cell_type": "markdown", @@ -444,10 +1279,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 66, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Average age of customers with orders with duplicates removed: 13.4\n", + "Average age of customers with orders without duplicates removed: 11.2\n", + "Cutomers without any order: septal\n" + ] + } + ], + "source": [ + "customers_and_orders_duplicates_removed = customers_and_orders[[\"customer_name\", \"customer_age\", \"customer_id\"]].drop_duplicates()\n", + "avg_cust_w_orders_age_duplicates_removed = customers_and_orders_duplicates_removed[\"customer_age\"].mean()\n", + "\n", + "customers_and_orders_duplicates_not_removed = customers_and_orders[[\"customer_name\", \"customer_age\", \"customer_id\"]]\n", + "avg_cust_w_orders_age_duplicates_not_removed = customers_and_orders_duplicates_not_removed[\"customer_age\"].mean()\n", + "\n", + "\n", + "customers_with_no_orders_df = customers_and_orders2.loc[customers_and_orders2[\"order_amount\"].isnull()] \n", + "customers_with_no_orders = customers_with_no_orders_df[\"customer_name\"][0]\n", + "customers_with_no_orders\n", + "\n", + "\n", + "print(f\"Average age of customers with orders with duplicates removed: {avg_cust_w_orders_age_duplicates_removed:.1f}\")\n", + "print(f\"Average age of customers with orders without duplicates removed: {avg_cust_w_orders_age_duplicates_not_removed:.1f}\")\n", + "print(f\"Cutomers without any order: {customers_with_no_orders}\")" + ] }, { "cell_type": "markdown", @@ -468,12 +1329,181 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 67, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
customer_nameinteraction_id_count_accurateinteraction_id_count_inaccurateclick_id_count_accurateclick_id_count_inaccurate
0amputator0033
1chyloid0022
2dermatoma0011
3digitogenin0011
4lamnectomy1111
5rapscallionly1333
6receivership2200
7septal2212
8shita1111
9tasselet1100
\n", + "
" + ], + "text/plain": [ + " customer_name interaction_id_count_accurate \\\n", + "0 amputator 0 \n", + "1 chyloid 0 \n", + "2 dermatoma 0 \n", + "3 digitogenin 0 \n", + "4 lamnectomy 1 \n", + "5 rapscallionly 1 \n", + "6 receivership 2 \n", + "7 septal 2 \n", + "8 shita 1 \n", + "9 tasselet 1 \n", + "\n", + " interaction_id_count_inaccurate click_id_count_accurate \\\n", + "0 0 3 \n", + "1 0 2 \n", + "2 0 1 \n", + "3 0 1 \n", + "4 1 1 \n", + "5 3 3 \n", + "6 2 0 \n", + "7 2 1 \n", + "8 1 1 \n", + "9 1 0 \n", + "\n", + " click_id_count_inaccurate \n", + "0 3 \n", + "1 2 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "5 3 \n", + "6 0 \n", + "7 2 \n", + "8 1 \n", + "9 0 " + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Start with this dataset \n", - "customers_visits_clicks_raw = customers.merge(web_visits, on=\"customer_id\", how=\"left\").merge(ad_clicks, on=\"customer_id\", how=\"left\")" + "customers_visits_clicks_raw = customers.merge(web_visits, on=\"customer_id\", how=\"left\").merge(ad_clicks, on=\"customer_id\", how=\"left\")\n", + "\n", + "customers_visits_clicks = (\n", + " customers_visits_clicks_raw.groupby(\"customer_name\")\n", + " .agg(\n", + " interaction_id_count_accurate=(\"interaction_id\", \"nunique\"),\n", + " interaction_id_count_inaccurate=(\"interaction_id\", \"count\"),\n", + " click_id_count_accurate=(\"click_id\", \"nunique\"),\n", + " click_id_count_inaccurate=(\"click_id\", \"count\")\n", + " )\n", + " .reset_index()\n", + ")\n", + "\n", + "customers_visits_clicks" ] }, { @@ -504,10 +1534,212 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 68, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
dateweb_visitsunique_web_visitorsunique_customers_visiting_websiteads_clicksunique_users_clickingunique_customers_clicking
02024-05-01441000
12024-05-02552000
22024-05-03553211
32024-05-04552333
42024-05-05110332
52024-05-06000332
62024-05-07000332
72024-05-08000332
82024-05-09000330
\n", + "
" + ], + "text/plain": [ + " date web_visits unique_web_visitors \\\n", + "0 2024-05-01 4 4 \n", + "1 2024-05-02 5 5 \n", + "2 2024-05-03 5 5 \n", + "3 2024-05-04 5 5 \n", + "4 2024-05-05 1 1 \n", + "5 2024-05-06 0 0 \n", + "6 2024-05-07 0 0 \n", + "7 2024-05-08 0 0 \n", + "8 2024-05-09 0 0 \n", + "\n", + " unique_customers_visiting_website ads_clicks unique_users_clicking \\\n", + "0 1 0 0 \n", + "1 2 0 0 \n", + "2 3 2 1 \n", + "3 2 3 3 \n", + "4 0 3 3 \n", + "5 0 3 3 \n", + "6 0 3 3 \n", + "7 0 3 3 \n", + "8 0 3 3 \n", + "\n", + " unique_customers_clicking \n", + "0 0 \n", + "1 0 \n", + "2 1 \n", + "3 3 \n", + "4 2 \n", + "5 2 \n", + "6 2 \n", + "7 2 \n", + "8 0 " + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_visits[\"date\"] = pd.to_datetime(web_visits[\"date\"])\n", + "ad_clicks[\"date\"] = pd.to_datetime(ad_clicks[\"date\"])\n", + "\n", + "all_dates = pd.DataFrame({\n", + " \"date\": pd.date_range(\"2024-05-01\", \"2024-05-09\")\n", + "})\n", + "\n", + "daily_web_visits = (\n", + " web_visits.groupby(\"date\").agg(\n", + " web_visits=(\"interaction_id\", \"count\"),\n", + " unique_web_visitors=(\"visitor_id\", \"nunique\"),\n", + " unique_customers_visiting_website=(\"customer_id\", \"nunique\")\n", + " )\n", + " .reset_index()\n", + ")\n", + "\n", + "daily_ad_clicks = (\n", + " ad_clicks.groupby(\"date\").agg(\n", + " ads_clicks=(\"click_id\", \"count\"),\n", + " unique_users_clicking=(\"external_user_id\", \"nunique\"),\n", + " unique_customers_clicking=(\"customer_id\", \"nunique\")\n", + " )\n", + " .reset_index()\n", + ")\n", + "\n", + "daily_counts_alt_method = (\n", + " all_dates\n", + " .merge(daily_web_visits, on=\"date\", how=\"left\")\n", + " .merge(daily_ad_clicks, on=\"date\", how=\"left\")\n", + " .fillna(0)\n", + ")\n", + "\n", + "count_cols = daily_counts_alt_method.columns.drop(\"date\")\n", + "daily_counts_alt_method[count_cols] = daily_counts_alt_method[count_cols].astype(int)\n", + "\n", + "daily_counts_alt_method" + ] }, { "cell_type": "markdown", @@ -530,10 +1762,147 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 69, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
datemean_time_on_pagetotal_time_on_pageads_clicks
02024-05-0138.955214155.8208560.0
12024-05-0253.381828266.9091410.0
22024-05-0360.249733301.2486632.0
32024-05-0422.672504113.3625193.0
42024-05-0555.75781955.7578193.0
52024-05-060.0000000.0000003.0
62024-05-070.0000000.0000003.0
72024-05-080.0000000.0000003.0
82024-05-090.0000000.0000003.0
\n", + "
" + ], + "text/plain": [ + " date mean_time_on_page total_time_on_page ads_clicks\n", + "0 2024-05-01 38.955214 155.820856 0.0\n", + "1 2024-05-02 53.381828 266.909141 0.0\n", + "2 2024-05-03 60.249733 301.248663 2.0\n", + "3 2024-05-04 22.672504 113.362519 3.0\n", + "4 2024-05-05 55.757819 55.757819 3.0\n", + "5 2024-05-06 0.000000 0.000000 3.0\n", + "6 2024-05-07 0.000000 0.000000 3.0\n", + "7 2024-05-08 0.000000 0.000000 3.0\n", + "8 2024-05-09 0.000000 0.000000 3.0" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "web_visits_time = (\n", + " web_visits.groupby(\"date\").agg(\n", + " mean_time_on_page=(\"time_on_page\", \"mean\"),\n", + " total_time_on_page=(\"time_on_page\", \"sum\")\n", + " )\n", + " .reset_index()\n", + ")\n", + "\n", + "daily_ad_clicks = (\n", + " ad_clicks.groupby(\"date\").agg(\n", + " ads_clicks=(\"click_id\", \"count\")\n", + " )\n", + " .reset_index()\n", + ")\n", + "\n", + "time_mean_total = (\n", + " all_dates\n", + " .merge(web_visits_time, on=\"date\", how=\"left\")\n", + " .merge(daily_ad_clicks, on=\"date\", how=\"left\")\n", + " .fillna(0)\n", + ")\n", + "\n", + "time_mean_total" + ] }, { "cell_type": "markdown", @@ -548,12 +1917,149 @@ "* 5 points for reproducing the figure. " ] }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0., 0., 0.],\n", + " [ 0., 0., -0.],\n", + " [ 0., -0., 0.]])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def minors_func(arr):\n", + " length = len(arr)\n", + " minors = np.zeros((length,length))\n", + " for row in range(length):\n", + " for col in range(length):\n", + " sub_arr = np.delete(np.delete(arr, row, axis=0),col,axis=1)\n", + " minors[row,col] = np.linalg.det(sub_arr) \n", + " return minors\n", + "\n", + "def grid_func(arr):\n", + " length = 3\n", + " grid = np.random.rand(length,length)\n", + " for row in range(length):\n", + " for col in range(length):\n", + " grid[row,col] = (-1)**(row+col)\n", + " return grid\n", + "\n", + "def cofactors_func(minors, grid):\n", + " return minors * grid\n", + "\n", + "def adjugate_func(cofactors, arr):\n", + " return cofactors.T / np.linalg.det(arr)\n", + "\n", + "n = 3 \n", + "arr = np.random.rand(n,n)\n", + "minors_mat = minors_func(arr)\n", + "grid_mat = grid_func(arr)\n", + "cofactors_mat = cofactors_func(minors_mat,grid_mat)\n", + "adjugate_mat = adjugate_func(cofactors_mat, arr)\n", + "inverse_mat = np.linalg.inv(arr)\n", + "\n", + "sol = np.round(inverse_mat - adjugate_mat, 4)\n", + "sol\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.imshow(minors_mat, cmap='gray')\n", + "plt.title('Minors Matrix')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(grid_mat, cmap='gray')\n", + "plt.title('Grid Matrix')\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(cofactors_mat, cmap='gray')\n", + "plt.title('Cofactors Matrix')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(adjugate_mat, cmap='gray')\n", + "plt.title('Adjugate Matrix')\n", + "plt.show()" + ] }, { "cell_type": "markdown", @@ -580,15 +2086,58 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 90, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Distance between (AB)^-1 and (A^-1)(B^-1) is: \n", + " [[ 20.65658 -35.49501 10.79484]\n", + " [-56.2425 3.7967 11.0738 ]\n", + " [ 26.89543 43.14634 -24.45328]] \n", + "\n", + "Distance between (AB)^-1 and (B^-1)(A^-1) is: \n", + " [[ 0. -0. 0.]\n", + " [-0. 0. 0.]\n", + " [-0. 0. -0.]] \n", + "\n", + "Distance between (A^-1)(B^-1) and (B^-1)(A^-1) is: \n", + " [[-20.65658 35.49501 -10.79484]\n", + " [ 56.2425 -3.7967 -11.0738 ]\n", + " [-26.89543 -43.14634 24.45328]]\n" + ] + } + ], + "source": [ + "n = 3\n", + "A = np.random.rand(n,n)\n", + "B = np.random.rand(n,n)\n", + "\n", + "#1\n", + "ex1 = np.linalg.inv(A@B)\n", + "\n", + "#2\n", + "ex2 = (np.linalg.inv(A)) @ (np.linalg.inv(B))\n", + "\n", + "#3\n", + "ex3 = (np.linalg.inv(B)) @ (np.linalg.inv(A))\n", + "\n", + "distance1 = np.round(ex1 - ex2, 5)\n", + "distance2 = np.round(ex1 - ex3, 5)\n", + "distance3 = np.round(ex2 - ex3, 5)\n", + "\n", + "print(\"Distance between (AB)^-1 and (A^-1)(B^-1) is: \\n\", distance1, \"\\n\")\n", + "print(\"Distance between (AB)^-1 and (B^-1)(A^-1) is: \\n\", distance2, \"\\n\")\n", + "print(\"Distance between (A^-1)(B^-1) and (B^-1)(A^-1) is: \\n\", distance3)\n", + "\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -602,7 +2151,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_2_intro_ipython.ipynb b/week_2_intro_ipython.ipynb index 1a469f7..e6bf222 100644 --- a/week_2_intro_ipython.ipynb +++ b/week_2_intro_ipython.ipynb @@ -24,12 +24,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "BQybla17FRh5" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "My name is Joe.\n", + "I am a student at North Seattle College.\n" + ] + } + ], + "source": [ + "print(f\"My name is Joe.\\nI am a student at North Seattle College.\")" + ] }, { "cell_type": "markdown", @@ -43,12 +54,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": { "id": "P7QDyWncFRh8" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "My phone number is 2065555555\n" + ] + } + ], + "source": [ + "phone_num = \"2065555555\"\n", + "\n", + "print(f\"My phone number is {phone_num}\")" + ] }, { "cell_type": "markdown", @@ -62,12 +85,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "id": "OnOau948FRh9" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hello my name is Joe and my phone number is 206-555-5555\n" + ] + } + ], + "source": [ + "phone = \"206-555-5555\"\n", + "name = \"Joe\"\n", + "\n", + "print(f\"Hello my name is {name} and my phone number is {phone}\")" + ] }, { "cell_type": "markdown", @@ -82,12 +118,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "id": "5x2rIFzRFRh9" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "I graduate in June of 2027.\n" + ] + } + ], + "source": [ + "month, year = \"June\", 2027\n", + "\n", + "print(f\"I graduate in {month} of {year}.\")" + ] }, { "cell_type": "markdown", @@ -109,12 +157,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "OkyeAVPXFRh-" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ans = 58.5\n" + ] + } + ], + "source": [ + "ans = 12 * 5 - 3 / 2\n", + "ans_type = str(type(ans))\n", + "\n", + "print(f\"ans = {ans}\")\n", + "\n", + "# ans is a float" + ] }, { "cell_type": "markdown", @@ -136,12 +199,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "Lo-LEy8bKYmG" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "31 days\n" + ] + } + ], + "source": [ + "oct = \"October\"\n", + "\n", + "if oct == \"October\":\n", + " print(\"31 days\")\n", + "else:\n", + " print(\"30 days\")" + ] }, { "cell_type": "markdown", @@ -157,12 +235,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "id": "qscUkh813QKH" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "between 100 and 150\n" + ] + } + ], + "source": [ + "x = 140\n", + "\n", + "if x > 150:\n", + " print(\"greater than 150\")\n", + "elif x > 100 and x < 150:\n", + " print(\"between 100 and 150\")\n", + "else:\n", + " print(\"less than 100\")" + ] }, { "cell_type": "markdown", @@ -177,12 +272,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "id": "1vxg4nMbFRh_" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number is divisible by 5 and 10.\n", + "Number is divisible by 7 or by 2\n" + ] + } + ], + "source": [ + "y = 70\n", + "\n", + "# you only need to check for mod 10 below becuase if it is divisible by 10 then \n", + "# it is also divisible by 5\n", + "if y % 10 == 0:\n", + " print(\"Number is divisible by 5 and 10.\")\n", + "\n", + "if y % 7 == 0 or y % 2 == 0:\n", + " print(\"Number is divisible by 7 or by 2\")\n" + ] }, { "cell_type": "markdown", @@ -195,12 +309,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "id": "JY_Ci5v-FRiA" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7\n", + "14\n", + "21\n", + "28\n", + "35\n", + "42\n", + "49\n", + "56\n", + "63\n", + "70\n", + "77\n", + "84\n", + "91\n", + "98\n" + ] + } + ], + "source": [ + "for i in range(1,101):\n", + " if i % 7 == 0:\n", + " print(i)" + ] }, { "cell_type": "markdown", @@ -213,12 +352,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "id": "4a1D64hpFRiA" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3 6 9 \n", + "18\n" + ] + } + ], + "source": [ + "sum = 0\n", + "i = 1\n", + "\n", + "while i < 11:\n", + " if i % 3 == 0:\n", + " print(i, end= \" \")\n", + " sum += i\n", + " i += 1\n", + "\n", + "print(f\"\\n{sum}\")" + ] }, { "cell_type": "markdown", @@ -241,12 +400,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "id": "ntBnYxzi1RPc" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Set: 1\n", + "Set: 2\n", + "Student: 1\n", + "Student: 2\n", + "Student: 3\n", + "Student: 4\n", + "Student: 5\n", + "Set: 3\n", + "Set: 4\n", + "Student: 1\n", + "Student: 2\n", + "Student: 3\n", + "Student: 4\n", + "Student: 5\n", + "Set: 5\n" + ] + } + ], + "source": [ + "for i in range(1,6):\n", + " print(f\"Set: {i}\")\n", + " if i % 2 == 0:\n", + " for j in range(1,6):\n", + " print(f\"Student: {j}\")" + ] }, { "cell_type": "markdown", @@ -259,12 +446,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "id": "lppms8ctzfRI" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hog\n", + "warts\n", + "s\n" + ] + } + ], + "source": [ + "school = \"Hogwarts\"\n", + "first = school[:3]\n", + "second = school[3:]\n", + "\n", + "print(first)\n", + "print(second)\n", + "print(school[-1])" + ] }, { "cell_type": "markdown", @@ -280,12 +485,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "id": "zw2NezoM0zfl" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Thor is a character in the Marvel Cinematic Universe. She-Hulk is a character in the Marvel Cinematic Universe. Loki is a character in the Marvel Cinematic Universe. " + ] + } + ], + "source": [ + "chars = [\"Thor\", \"She-Hulk\", \"Loki\"]\n", + "\n", + "for name in chars:\n", + " print(f\"{name} is a character in the Marvel Cinematic Universe.\", end = \" \")\n" + ] }, { "cell_type": "markdown", @@ -299,12 +517,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": { "id": "rbyZif9a1b2V" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "January has 31 days. \n", + "February has 28 days. \n", + "March has 31 days. \n", + "April has 30 days. \n", + "May has 31 days. \n", + "June has 30 days. \n" + ] + } + ], + "source": [ + "months = [[\"January\", 31], [\"February\", 28], [\"March\", 31], [\"April\", 30], [\"May\", 31], [\"June\", 30]]\n", + "\n", + "for i in range(len(months)):\n", + " month, days = months[i][0], months[i][1]\n", + " print(f\"{month} has {days} days. \")" + ] }, { "cell_type": "markdown", @@ -325,8 +562,38 @@ "metadata": { "id": "p0YE0nqs4Hcz" }, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'breed': 'Corgi', 'Age Exp.': 13, 'Type': 'Cattle herding'}\n", + "Corgi\n", + "The Corgi is expected to live about 13 years.\n" + ] + } + ], + "source": [ + "dog = {\"breed\": \"Corgi\", \"Age Exp.\": 13, \"Type\": \"Cattle herding\"}\n", + "\n", + "print(dog)\n", + "\n", + "print(dog[\"breed\"])\n", + "\n", + "print(f\"The {dog['breed']} is expected to live about {dog['Age Exp.']} years.\")\n", + "\n", + "\"\"\"\n", + "I used AI to help me with this as I kept getting an error on the last print statement \n", + "because I was using double quotes for the variable I was placing inside the f-string. \n", + "I was trying to access it like this dog[\"breed\"] but kept getting an error. So I pasted \n", + "it into gpt and it explained that the interpreter was interpreting the first double \n", + "quotation mark as the end of the f-string. Thus causing the error. \n", + "\n", + "I also learned that juypter notebook is finicky about mutli-line comments and you have \n", + "to add a semi-colon after the second triple quote otherwise it will print your comment. \n", + "\"\"\";\n", + "\n" + ] }, { "cell_type": "markdown", @@ -339,11 +606,22 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import AD450_math\n", "\n", - "AD450_math.add(2,2)" + "AD450_math.add(2,2)\n" ] }, { @@ -359,9 +637,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "AttributeError", + "evalue": "module 'AD450_math' has no attribute 'multiply'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Cell with import error\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[43mAD450_math\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmultiply\u001b[49m(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m2\u001b[39m)\n", + "\u001b[0;31mAttributeError\u001b[0m: module 'AD450_math' has no attribute 'multiply'" + ] + } + ], "source": [ "# Cell with import error\n", "AD450_math.multiply(2, 2)" @@ -371,16 +661,40 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Reload cell" + "# Reload cell\n", + "import importlib\n", + "importlib.reload(AD450_math)\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Cell with correct output \n", "AD450_math.multiply(2, 2)" @@ -400,29 +714,45 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ - "# Create a" + "# Create a\n", + "a = 1" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4\n" + ] + } + ], "source": [ - "# Print a" + "# Print a\n", + "print(a)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ - "# Set a to 4" + "# Set a to 4\n", + "a = 4\n", + "\n", + "\"\"\" \n", + "It looks like after running this block that it is changing the global value of a. \n", + "so when we run the block above it prints out 4 because a has been re-assigned.\n", + "\"\"\";" ] } ], @@ -431,7 +761,7 @@ "provenance": [] }, "kernelspec": { - "display_name": "my_env_2", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -445,7 +775,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_3_numpy.ipynb b/week_3_numpy.ipynb index 1db8573..cd71e72 100644 --- a/week_3_numpy.ipynb +++ b/week_3_numpy.ipynb @@ -20,6 +20,11 @@ "* Can map data directly onto underlying disk or memory representation\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, { "cell_type": "markdown", "metadata": { @@ -57,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": { "id": "Pt63xmy1qLll" }, @@ -75,7 +80,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -83,19 +88,37 @@ "id": "AVByQUYKxtNG", "outputId": "238e50f0-366d-41de-a44a-6cf3e063650c" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[1 2 3 4]\n", + " [5 6 7 8]]\n", + "\n", + "Inspect the array\n", + "--------------\n", + "dimensions: 2\n", + "shape:\t (2, 4)\n", + "size:\t 8\n", + "datatype int64\n", + "bytes:\t 64\n" + ] + } + ], "source": [ "# create an array called numbers with 2 rows and 4 columns from literal values. Have your literal values be the integers 1-8\n", - "numbers = None #Replace None with array defintion\n", + "numbers = np.array([[1,2,3,4], [5,6,7,8]])\n", + "\n", "print(numbers)\n", "\n", "# Replace None below with each value for the array. \n", "print(\"\\nInspect the array\\n--------------\")\n", - "print(\"dimensions:\", None) # ndarrays have dimensions\n", - "print(\"shape:\\t\", None) # ndarrays have shape (numer of rows & columns)\n", - "print(\"size:\\t\", None) # number of elements in the array\n", - "print(\"datatype\", None) # numpy determines the datatype\n", - "print(\"bytes:\\t\", None) # total bytes consumed by the array" + "print(\"dimensions:\", numbers.ndim) # ndarrays have dimensions\n", + "print(\"shape:\\t\", numbers.shape) # ndarrays have shape (numer of rows & columns)\n", + "print(\"size:\\t\", numbers.size) # number of elements in the array\n", + "print(\"datatype\", numbers.dtype) # numpy determines the datatype\n", + "print(\"bytes:\\t\", numbers.nbytes) # total bytes consumed by the array" ] }, { @@ -109,7 +132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -117,34 +140,77 @@ "id": "pTXgMRYRQS3v", "outputId": "010d4702-bc29-4f87-980e-66fe9b43436a" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ones\n", + "[[1. 1. 1. 1.]\n", + " [1. 1. 1. 1.]\n", + " [1. 1. 1. 1.]] \n", + "\n", + "zeros\n", + "[[0. 0. 0. 0.]\n", + " [0. 0. 0. 0.]\n", + " [0. 0. 0. 0.]] \n", + "\n", + "random\n", + "[[0.52286842 0.27818666]\n", + " [1.20170613 0.13236204]] \n", + "\n", + "empty\n", + "[[0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]] \n", + "\n", + "full\n", + "[['x' 'x']\n", + " ['x' 'x']] \n", + "\n", + "even\n", + "[10 15 20] \n", + "\n", + "line\n", + "[0. 0.25 0.5 0.75 1. 1.25 1.5 1.75 2. ] \n", + "\n" + ] + } + ], "source": [ "# Create an 3 by 4 array of ones\n", - "ones = None\n", + "ones = np.ones((3,4))\n", + "print(\"ones\")\n", "print(ones, \"\\n\")\n", "\n", "# Create an 3 by 4 array of zeros\n", - "zeros = None\n", + "zeros = np.zeros((3,4))\n", + "print(\"zeros\")\n", "print(zeros, \"\\n\")\n", "\n", "# Create an 2 by 2 array with random values\n", - "rando = None\n", + "rando = np.random.standard_normal(size = (2,2))\n", + "print(\"random\")\n", "print(rando, \"\\n\")\n", "\n", "# Create 3 by 2 an empty array\n", - "empty = None\n", + "empty = np.empty((3,2))\n", + "print(\"empty\")\n", "print(empty, \"\\n\")\n", "\n", "# Create a 2 by 2 array full of 'x's, hint seach numpy full\n", - "full = None\n", + "full = np.full((2,2),'x')\n", + "print(\"full\")\n", "print(full, \"\\n\")\n", "\n", "# Create an array of the form [10, 15, 20] using np.arange\n", - "even = None\n", + "even = np.arange(10,21,5)\n", + "print(\"even\")\n", "print(even, \"\\n\")\n", "\n", "# Create an array of the form [0. 0.25 0.5 0.75 1. 1.25 1.5 1.75 2. ] using np.linspace\n", - "line = None\n", + "line = np.linspace(0, 2, 9)\n", + "print(\"line\")\n", "print(line, \"\\n\")\n" ] }, @@ -180,11 +246,22 @@ "id": "NSMJt_4x0qan", "outputId": "81e81c55-af1d-4149-dc7c-7edc8a1a582d" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[5 6 7]\n" + ] + } + ], "source": [ "arr1d = np.array([0,1, 2, 3, 4, 5, 6, 7, 8])\n", "\n", - "# using indexing select and output [5, 6, 7] from arr1d. Save this slice to a variable named slice_arr1d\n" + "# using indexing select and output [5, 6, 7] from arr1d. Save this slice to a variable named slice_arr1d\n", + "\n", + "slice_arr1d = arr1d[5:8]\n", + "print(slice_arr1d)\n" ] }, { @@ -204,9 +281,20 @@ "id": "Xe-PXYhBp4bn", "outputId": "cf387d7a-d51f-4540-8d9a-571a9a24f7b5" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0 1 2 3 4 5 12 12 12]\n" + ] + } + ], "source": [ - "# Replace 6, 7, and 8 with 12 in arr1d using one line of code. Then print arr1d and slice_arr1d\n" + "# Replace 6, 7, and 8 with 12 in arr1d using one line of code. Then print arr1d and slice_arr1d\n", + "\n", + "arr1d[6:] = 12\n", + "print(arr1d)\n" ] }, { @@ -226,9 +314,20 @@ "id": "Eh0My7Eaqe77", "outputId": "693ef4b3-97a0-4a42-d77a-740fa2cd81db" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0 1 2 3 4 5 12 12 12]\n" + ] + } + ], "source": [ - "# Create a copy of arr1d and name it new_array. Hint: You can't use new_array = arr1d" + "# Create a copy of arr1d and name it new_array. Hint: You can't use new_array = arr1d\n", + "\n", + "new_array = arr1d.copy()\n", + "print(new_array)" ] }, { @@ -240,13 +339,25 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3\n", + "3\n" + ] + } + ], "source": [ "arr2d = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])\n", "\n", - "# There are two ways to select 3 from the 2 dimensional array above. Use both ways to select 3 and print the results. " + "# There are two ways to select 3 from the 2 dimensional array above. Use both ways to select 3 and print the results. \n", + "\n", + "print(arr2d[0][2])\n", + "print(arr2d[0,2])" ] }, { @@ -266,16 +377,32 @@ "id": "kvMvyar216T5", "outputId": "943f42a4-469a-48f0-f4d4-546849ffa08d" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[2 3 4]\n", + " [6 7 8]] \n", + "\n", + "[3 7] \n", + "\n", + "[1 2 3 4]\n" + ] + } + ], "source": [ "# In mult-dimensional arrays, slicing that omits later indices will return a lower-dimensional ndarray\n", "# Select and print out the following:\n", "\n", "# select first two rows and all but first column\n", + "print(arr2d[:2, 1:], \"\\n\")\n", "\n", "# select first two rows and only 3rd column\n", + "print(arr2d[:2, 2], \"\\n\")\n", "\n", - "# select all columns in the first row\n" + "# select all columns in the first row\n", + "print(arr2d[0, :])\n" ] }, { @@ -298,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -306,14 +433,38 @@ "id": "IMEp_RGh_Fu5", "outputId": "45332ef8-2c42-4c40-af09-6caaf98bca6b" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "First and fourth rows of data: \n", + "[[1 0 0 0 0 1 1]\n", + " [0 1 1 1 0 0 0]] \n", + "\n", + "All of data: \n", + "[[1 0 0 0 0 1 1]\n", + " [1 1 0 1 1 1 1]\n", + " [0 1 0 1 0 0 1]\n", + " [0 1 1 1 0 0 0]\n", + " [1 0 1 0 1 1 1]\n", + " [1 1 1 1 1 0 0]\n", + " [1 0 0 1 0 1 0]]\n" + ] + } + ], "source": [ "import numpy as np\n", "names = np.array(['Bob', 'Joe', 'Will', 'Bob', 'Will', 'Joe', 'Joe'])\n", "data = np.random.randint(2, size=(7, 7)) # create an array of random values\n", "\n", "# Select and print the first and forth rows from 'data' using just the array 'names' and 'data'. Print out both the selected rows and 'data'. \n", - "# Hint\" The \"Bob\" appears in both the first and forth rows. " + "# Hint\" The \"Bob\" appears in both the first and forth rows. \n", + "\n", + "print(\"First and fourth rows of data: \")\n", + "print(data[names == \"Bob\"], \"\\n\")\n", + "print(\"All of data: \")\n", + "print(data)\n" ] }, { @@ -327,7 +478,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -335,10 +486,22 @@ "id": "BgULatpwt7X_", "outputId": "c31d49b4-92ff-4514-c91b-8eeb42573b5f" }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 0, 0, 0, 1, 1],\n", + " [0, 1, 1, 1, 0, 0, 0]])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Again output the first and fouth rows using the cond below. Meaning replace None with an expression\n", - "cond = None\n", + "cond = (names == \"Bob\")\n", "data[cond]" ] }, @@ -353,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -361,9 +524,27 @@ "id": "EP-SDDVIvK8s", "outputId": "cce4fab9-cd5e-46c2-c615-f2518f1b4a72" }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 1, 0, 1, 1, 1, 1],\n", + " [0, 1, 0, 1, 0, 0, 1],\n", + " [1, 0, 1, 0, 1, 1, 1],\n", + " [1, 1, 1, 1, 1, 0, 0],\n", + " [1, 0, 0, 1, 0, 1, 0]])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Select all rows except the first and forth" + "# Select all rows except the first and forth\n", + "\n", + "cond = ~(names == \"Bob\")\n", + "data[cond]" ] }, { @@ -377,7 +558,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -385,9 +566,23 @@ "id": "QYjmF7eFvTmc", "outputId": "172adeb5-31d7-47ad-e3af-59c352f96f97" }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 1, 1],\n", + " [1, 1, 0, 0, 0]])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Select the last 5 columns for the first and forth row" + "# Select the last 5 columns for the first and forth row\n", + "cond = (names == \"Bob\")\n", + "data[cond, 2:]" ] }, { @@ -401,7 +596,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 37, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -409,9 +604,26 @@ "id": "sciz0aprvh8u", "outputId": "24c8c092-cbe9-4665-9e01-9d193bcac8df" }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0, 0, 0, 0, 1, 1, 1],\n", + " [1, 0, 0, 0, 1, 0, 1],\n", + " [0, 1, 1, 1, 0, 1, 0],\n", + " [0, 1, 1, 1, 1, 1, 1]])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Select the first, third, forth and fifth row using similar conditioins and an OR operator" + "# Select the first, third, forth and fifth row using similar conditioins and an OR operator\n", + "\n", + "cond = (names == \"Bob\") | (names == \"Will\")\n", + "data[cond]" ] }, { @@ -436,7 +648,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -444,18 +656,39 @@ "id": "HdWTjc8CZI5R", "outputId": "e070b71e-bdee-4abc-f378-474978208ad5" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Original array: \n", + "[[1. 2. 3.]\n", + " [4. 5. 6.]] \n", + "\n", + "Adding 5: \n", + "[[ 6. 7. 8.]\n", + " [ 9. 10. 11.]] \n", + "\n", + "Multiplying by 10: \n", + "[[10. 20. 30.]\n", + " [40. 50. 60.]]\n" + ] + } + ], "source": [ "array1 = np.array([[1., 2., 3.], [4., 5., 6.]])\n", "\n", - "print(array1)\n", + "print(\"Original array: \")\n", + "print(array1, \"\\n\")\n", "\n", "# Add 5 to all values in array1 and print \n", - "print()\n", + "print(\"Adding 5: \")\n", + "print(array1 + 5, \"\\n\")\n", "\n", "\n", "# Multiple all values in array1 by 10 and print \n", - "print()\n" + "print(\"Multiplying by 10: \")\n", + "print(array1 * 10)\n" ] }, { @@ -469,7 +702,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 48, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -477,9 +710,23 @@ "id": "uHr0DxrmaOEZ", "outputId": "b0f74550-427d-4333-c010-45f886677379" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[False True False]\n", + " [ True False True]]\n" + ] + } + ], "source": [ + "# array1 = np.array([[1., 2., 3.], [4., 5., 6.]])\n", + "\n", "array2 = np.array([[0., 4., 1.], [7., 2., 12.]])\n", + "result14 = np.where(array1 < array2, True, False)\n", + "\n", + "print(result14)\n", "\n", "\n", "# Test to see if pairwise elements in array1 are less than the corresponding element in array2. Output the results.\n", @@ -519,7 +766,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 49, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -527,13 +774,25 @@ "id": "k5pIynI12dmY", "outputId": "cd39dc42-7bab-4a92-c3e0-151a287d0b07" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1. 0. 1. 1. 0.]\n" + ] + } + ], "source": [ "arr1 = np.ones(5)\n", "arr2 = np.zeros(5)\n", "cond = np.array([True, False, True, True, False])\n", "\n", - "# Output the value from `arr1` whenever the corresponding value in `cond` is True, and otherwise take the value from `arr2`. \n" + "# Output the value from `arr1` whenever the corresponding value in `cond` is True, and otherwise take the value from `arr2`. \n", + "\n", + "result15 = np.where(cond, arr1, arr2)\n", + "\n", + "print(result15)\n" ] }, { @@ -564,7 +823,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -572,12 +831,33 @@ "id": "ImvBT7NX3aY7", "outputId": "d04b3b76-91e4-4a40-e047-1e7a55bfd4ed" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0 3 3 3]\n", + " [0 3 1 0]\n", + " [1 1 1 2]\n", + " [3 3 2 0]\n", + " [1 3 2 0]] \n", + "\n", + "Mean: 1.6\n", + "Sum: 32\n" + ] + } + ], "source": [ "arr = np.random.randint(4, size=(5, 4))\n", - "print(arr)\n", + "print(arr, \"\\n\")\n", + "\n", + "# Calculate and print the mean and sum for all values in the array\n", + "\n", + "mean16 = np.mean(arr)\n", + "sum16 = arr.sum()\n", "\n", - "# Calculate and print the mean and sum for all values in the array\n" + "print(\"Mean: \", mean16)\n", + "print(\"Sum: \", sum16)\n" ] }, { @@ -589,7 +869,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -597,9 +877,32 @@ "id": "kxw7AUVm31Ea", "outputId": "b1cb6ece-5056-41b1-8c1b-f57612b9dae1" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mean across rows: [2.25 1. 1.25 2. 1.5 ]\n", + "Mean across columns: [1. 2.6 1.8 1. ]\n", + "Sum across rows: [9 4 5 8 6]\n", + "Sum across columns: [ 5 13 9 5]\n" + ] + } + ], "source": [ - "# Calculate the mean and sum across the columns and the rows. Print out both\n" + "# Calculate the mean and sum across the columns and the rows. Print out both\n", + "# axis = 0 columns \n", + "# axis = 1 rows \n", + "\n", + "mean17_rows = arr.mean(axis = 1)\n", + "mean17_columns = arr.mean(axis = 0)\n", + "sum17_rows = arr.sum(axis = 1)\n", + "sum17_columns = arr.sum(axis = 0)\n", + "\n", + "print(\"Mean across rows: \", mean17_rows)\n", + "print(\"Mean across columns: \", mean17_columns)\n", + "print(\"Sum across rows: \", sum17_rows)\n", + "print(\"Sum across columns: \", sum17_columns)\n" ] }, { @@ -611,15 +914,46 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Full cummulative sum: \n", + " [ 0 3 6 9 9 12 13 13 14 15 16 18 21 24 26 26 27 30 32 32] \n", + "\n", + "Columns cumulative sum: \n", + " [[ 0 3 3 3]\n", + " [ 0 6 4 3]\n", + " [ 1 7 5 5]\n", + " [ 4 10 7 5]\n", + " [ 5 13 9 5]] \n", + "\n", + "Rows cumulative sum: \n", + " [[0 3 6 9]\n", + " [0 3 4 4]\n", + " [1 2 3 5]\n", + " [3 6 8 8]\n", + " [1 4 6 6]]\n" + ] + } + ], "source": [ "# Print out the cumulative sum for the full array, the columns and the rows. \n", "# For example the array [[1, 1, 1], [1, 1, 1]] would have the following outputs:\n", "# full array: [1, 2, 3, 4, 5, 6]\n", "# columns: [[1, 1, 1], [2, 2, 2]]\n", - "# rows: [[1, 2, 3], [1, 2, 3]]\n" + "# rows: [[1, 2, 3], [1, 2, 3]]\n", + "\n", + "cumsum18_full = arr.cumsum()\n", + "cumsum18_columns = arr.cumsum(axis = 0)\n", + "cumsum18_rows = arr.cumsum(axis = 1)\n", + "\n", + "print(\"Full cummulative sum: \\n\", cumsum18_full, \"\\n\")\n", + "print(\"Columns cumulative sum: \\n\", cumsum18_columns, \"\\n\")\n", + "print(\"Rows cumulative sum: \\n\", cumsum18_rows)\n" ] }, { @@ -639,16 +973,34 @@ "id": "sDnJpvUR1B1W", "outputId": "c4806b83-0ba9-448e-c4b7-f9ca53a8900d" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Arr: \n", + " [0 1 2 3 4 5 6 7 8 9] \n", + "\n", + "Odds: \n", + " [1 3 5 7 9] \n", + "\n", + "Arr reversed: \n", + " [9 8 7 6 5 4 3 2 1 0]\n" + ] + } + ], "source": [ "\n", "arr = np.arange(10)\n", - "print(arr)\n", + "print(\"Arr: \\n\", arr, \"\\n\")\n", "\n", "\n", "# Print out all all odd values\n", + "odds = arr[arr % 2 == 1]\n", + "print(\"Odds: \\n\", odds, \"\\n\")\n", "\n", - "# Print out all values in reverse order\n" + "# Print out all values in reverse order\n", + "print(\"Arr reversed: \\n\", np.flip(arr))\n" ] } ], @@ -664,7 +1016,7 @@ "provenance": [] }, "kernelspec": { - "display_name": "base", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -678,7 +1030,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_4_panadas.ipynb b/week_4_panadas.ipynb index 9080a02..045cd33 100644 --- a/week_4_panadas.ipynb +++ b/week_4_panadas.ipynb @@ -23,7 +23,7 @@ "metadata": {}, "outputs": [], "source": [ - "#As allways we import pandas and numpy\n", + "#As always we import pandas and numpy\n", "import pandas as pd\n", "import numpy as np" ] @@ -52,10 +52,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "0 6\n", + "1 7\n", + "2 8\n", + "3 9\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = pd.Series([6,7,8,9])\n", + "x\n" + ] }, { "cell_type": "markdown", @@ -66,10 +84,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "d 7\n", + "dtype: int64" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = pd.Series([6,7,8,9], index = list(\"adbc\"))\n", + "x[[\"d\"]]" + ] }, { "cell_type": "markdown", @@ -85,10 +118,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "Ohio 35000\n", + "Texas 71000\n", + "Oregon 16000\n", + "Utah 5000\n", + "dtype: int64" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "states_dict = {\"Ohio\":35000, \"Texas\":71000, \"Oregon\":16000, \"Utah\":5000}\n", + "\n", + "states_series = pd.Series(states_dict)\n", + "states_series" + ] }, { "cell_type": "markdown", @@ -99,10 +152,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "OH 35000\n", + "TX 71000\n", + "OR 16000\n", + "UT 5000\n", + "dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "states_series.index = [\"OH\", \"TX\", \"OR\", \"UT\"]\n", + "\n", + "states_series" + ] }, { "cell_type": "markdown", @@ -125,9 +197,91 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
stateyearpop
0Ohio20001.5
1Ohio20011.7
2Ohio20023.6
3Nevada20012.4
4Nevada20022.9
5Nevada20033.2
\n", + "
" + ], + "text/plain": [ + " state year pop\n", + "0 Ohio 2000 1.5\n", + "1 Ohio 2001 1.7\n", + "2 Ohio 2002 3.6\n", + "3 Nevada 2001 2.4\n", + "4 Nevada 2002 2.9\n", + "5 Nevada 2003 3.2" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = {\n", " 'state': ['Ohio', 'Ohio', 'Ohio', 'Nevada', 'Nevada', 'Nevada'],\n", @@ -148,10 +302,95 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
stateyearpop
zeroOhio20001.5
oneOhio20011.7
twoOhio20023.6
threeNevada20012.4
fourNevada20022.9
fiveNevada20033.2
\n", + "
" + ], + "text/plain": [ + " state year pop\n", + "zero Ohio 2000 1.5\n", + "one Ohio 2001 1.7\n", + "two Ohio 2002 3.6\n", + "three Nevada 2001 2.4\n", + "four Nevada 2002 2.9\n", + "five Nevada 2003 3.2" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.index = [\"zero\", \"one\", \"two\", \"three\", \"four\", \"five\"]\n", + "df" + ] }, { "cell_type": "markdown", @@ -162,10 +401,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "zero Ohio\n", + "one Ohio\n", + "two Ohio\n", + "three Nevada\n", + "four Nevada\n", + "five Nevada\n", + "Name: state, dtype: object \n", + "\n", + "zero Ohio\n", + "one Ohio\n", + "two Ohio\n", + "three Nevada\n", + "four Nevada\n", + "five Nevada\n", + "Name: state, dtype: object\n" + ] + } + ], + "source": [ + "print(df[\"state\"], \"\\n\")\n", + "print(df.state)\n" + ] }, { "cell_type": "markdown", @@ -176,10 +440,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "state Ohio\n", + "year 2000\n", + "pop 1.5\n", + "Name: zero, dtype: object \n", + "\n", + "state Ohio\n", + "year 2000\n", + "pop 1.5\n", + "Name: zero, dtype: object\n" + ] + } + ], + "source": [ + "print(df.loc[\"zero\"], \"\\n\")\n", + "print(df.iloc[0])" + ] }, { "cell_type": "markdown", @@ -190,10 +473,102 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
stateyearpoprating
zeroOhio20001.55
oneOhio20011.74
twoOhio20023.63
threeNevada20012.42
fourNevada20022.91
fiveNevada20033.20
\n", + "
" + ], + "text/plain": [ + " state year pop rating\n", + "zero Ohio 2000 1.5 5\n", + "one Ohio 2001 1.7 4\n", + "two Ohio 2002 3.6 3\n", + "three Nevada 2001 2.4 2\n", + "four Nevada 2002 2.9 1\n", + "five Nevada 2003 3.2 0" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[\"rating\"] = [5,4,3,2,1,0]\n", + "df" + ] }, { "cell_type": "markdown", @@ -204,10 +579,109 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
stateyearpopratingnonsense
zeroOhio20001.557.5
oneOhio20011.746.8
twoOhio20023.6310.8
threeNevada20012.424.8
fourNevada20022.912.9
fiveNevada20033.200.0
\n", + "
" + ], + "text/plain": [ + " state year pop rating nonsense\n", + "zero Ohio 2000 1.5 5 7.5\n", + "one Ohio 2001 1.7 4 6.8\n", + "two Ohio 2002 3.6 3 10.8\n", + "three Nevada 2001 2.4 2 4.8\n", + "four Nevada 2002 2.9 1 2.9\n", + "five Nevada 2003 3.2 0 0.0" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[\"nonsense\"] = df[\"rating\"] * df[\"pop\"]\n", + "df" + ] }, { "cell_type": "markdown", @@ -224,10 +698,94 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
abcde
series_numerical0.0000001.0000002.0000003.0000004.000000
series_zeros0.0000000.0000000.0000000.0000000.000000
series_random0.3870980.2426020.3049840.6079780.380149
\n", + "
" + ], + "text/plain": [ + " a b c d e\n", + "series_numerical 0.000000 1.000000 2.000000 3.000000 4.000000\n", + "series_zeros 0.000000 0.000000 0.000000 0.000000 0.000000\n", + "series_random 0.387098 0.242602 0.304984 0.607978 0.380149" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "idx = pd.Index(list(\"abcde\"))\n", + "series_numerical = pd.Series(np.arange(5), index = idx)\n", + "series_zeros = pd.Series(np.zeros(5), index = idx)\n", + "series_random = pd.Series(np.random.rand(5), index = idx)\n", + "\n", + "series_list = list([series_numerical, series_zeros, series_random])\n", + "series_index = pd.Index([\"series_numerical\", \"series_zeros\", \"series_random\"])\n", + "numeric_df = pd.DataFrame(series_list, index = series_index)\n", + "\n", + "numeric_df\n", + "\n", + "# I did consult chatgpt on this concerning the style I wrote with declaring the few extra variables (idx, series_list, series_index) and \n", + "# potential other ways to write it\n", + "\n" + ] }, { "cell_type": "markdown", @@ -238,10 +796,89 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandom
a0.00.00.387098
b1.00.00.242602
c2.00.00.304984
d3.00.00.607978
e4.00.00.380149
\n", + "
" + ], + "text/plain": [ + " numerical zeros random\n", + "a 0.0 0.0 0.387098\n", + "b 1.0 0.0 0.242602\n", + "c 2.0 0.0 0.304984\n", + "d 3.0 0.0 0.607978\n", + "e 4.0 0.0 0.380149" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transposed_numeric_df = numeric_df.T \n", + "transposed_numeric_df.columns = [\"numerical\", \"zeros\", \"random\"]\n", + "transposed_numeric_df" + ] }, { "cell_type": "markdown", @@ -252,10 +889,88 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandom
d3.00.00.607978
a0.00.00.387098
e4.00.00.380149
c2.00.00.304984
b1.00.00.242602
\n", + "
" + ], + "text/plain": [ + " numerical zeros random\n", + "d 3.0 0.0 0.607978\n", + "a 0.0 0.0 0.387098\n", + "e 4.0 0.0 0.380149\n", + "c 2.0 0.0 0.304984\n", + "b 1.0 0.0 0.242602" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transposed_numeric_df_random_descending = transposed_numeric_df.sort_values(\"random\", ascending = False)\n", + "transposed_numeric_df_random_descending" + ] }, { "cell_type": "markdown", @@ -266,10 +981,67 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandom
d3.00.00.607978
e4.00.00.380149
\n", + "
" + ], + "text/plain": [ + " numerical zeros random\n", + "d 3.0 0.0 0.607978\n", + "e 4.0 0.0 0.380149" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "greater_than_2 = transposed_numeric_df.loc[transposed_numeric_df.numerical > 2]\n", + "greater_than_2" + ] }, { "cell_type": "markdown", @@ -280,10 +1052,88 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " numerical zeros random random5\n", + "a 0.0 0.0 0.387098 1.935491\n", + "b 1.0 0.0 0.242602 1.213010\n", + "c 2.0 0.0 0.304984 1.524922\n", + "d 3.0 0.0 0.607978 3.039889\n", + "e 4.0 0.0 0.380149 1.900745\n", + "-----------------------------------------------------------------\n", + "All rows where numerical is greater than random5:\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandomrandom5
c2.00.00.3049841.524922
e4.00.00.3801491.900745
\n", + "
" + ], + "text/plain": [ + " numerical zeros random random5\n", + "c 2.0 0.0 0.304984 1.524922\n", + "e 4.0 0.0 0.380149 1.900745" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transposed_numeric_df[\"random5\"] = transposed_numeric_df[\"random\"] * 5\n", + "greater_than_random_5 = transposed_numeric_df[transposed_numeric_df[\"numerical\"] > transposed_numeric_df[\"random5\"]]\n", + "print(transposed_numeric_df)\n", + "print(\"-----------------------------------------------------------------\")\n", + "print(\"All rows where numerical is greater than random5:\")\n", + "greater_than_random_5" + ] }, { "cell_type": "markdown", @@ -294,10 +1144,100 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandomrandom5even
a0.00.00.3870981.935491True
b1.00.00.2426021.213010False
c2.00.00.3049841.524922True
d3.00.00.6079783.039889False
e4.00.00.3801491.900745True
\n", + "
" + ], + "text/plain": [ + " numerical zeros random random5 even\n", + "a 0.0 0.0 0.387098 1.935491 True\n", + "b 1.0 0.0 0.242602 1.213010 False\n", + "c 2.0 0.0 0.304984 1.524922 True\n", + "d 3.0 0.0 0.607978 3.039889 False\n", + "e 4.0 0.0 0.380149 1.900745 True" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transposed_numeric_df[\"even\"] = transposed_numeric_df[\"numerical\"] % 2 == 0\n", + "transposed_numeric_df" + ] }, { "cell_type": "markdown", @@ -308,10 +1248,121 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
numericalzerosrandomrandom5eveneven_odd
a0.00.00.3870981.935491Trueeven
b1.00.00.2426021.213010Falseodd
c2.00.00.3049841.524922Trueeven
d3.00.00.6079783.039889Falseodd
e4.00.00.3801491.900745Trueeven
\n", + "
" + ], + "text/plain": [ + " numerical zeros random random5 even even_odd\n", + "a 0.0 0.0 0.387098 1.935491 True even\n", + "b 1.0 0.0 0.242602 1.213010 False odd\n", + "c 2.0 0.0 0.304984 1.524922 True even\n", + "d 3.0 0.0 0.607978 3.039889 False odd\n", + "e 4.0 0.0 0.380149 1.900745 True even" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\" \n", + "I wrote this two ways. I find the one that I commented out with the lambda function \n", + "is cleaner with less code as you don't need to write the separate function. I used the \n", + "second one as that is how it was shown in the book. I found the lambda version on the \n", + "geeksforgeeks website, it's in the url below this line. \n", + "https://www.geeksforgeeks.org/python/ways-to-apply-an-if-condition-in-pandas-dataframe/\n", + "\"\"\";\n", + "\n", + "def ev_odd(x):\n", + " if x == True:\n", + " return \"even\"\n", + " else:\n", + " return \"odd\"\n", + "\n", + "# transposed_numeric_df[\"even_odd\"] = transposed_numeric_df[\"even\"].apply(lambda x: \"even\" if x == True else \"odd\")\n", + "transposed_numeric_df[\"even_odd\"] = transposed_numeric_df[\"even\"].apply(ev_odd)\n", + "transposed_numeric_df" + ] }, { "cell_type": "markdown", @@ -322,10 +1373,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "numerical 10.000000\n", + "zeros 0.000000\n", + "random 1.922811\n", + "random5 9.614057\n", + "even 3.000000\n", + "dtype: float64" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "I purposely filtered out the even_odd column as calculating the sum just \n", + "creates a long string of evenoodevenoddeven. I left the even column in, \n", + "even though is just True/False as technically True == 1 and False == 0. So \n", + "you can technically add them. \n", + "\"\"\";\n", + "\n", + "columns = [\"numerical\", \"zeros\", \"random\", \"random5\", \"even\"]\n", + "\n", + "transposed_numeric_df[columns].sum(axis = 0)" + ] }, { "cell_type": "markdown", @@ -336,15 +1414,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "numerical e\n", + "zeros a\n", + "random d\n", + "random5 d\n", + "even a\n", + "dtype: object" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "transposed_numeric_df[columns].idxmax()\n", + "\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "base", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -358,7 +1455,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_5_vectors_applications.ipynb b/week_5_vectors_applications.ipynb index 11948c0..51ea02b 100644 --- a/week_5_vectors_applications.ipynb +++ b/week_5_vectors_applications.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -28,15 +28,15 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "queen = np.array([5, 6, 4])\n", "women = np.array([1, 3, 2])\n", "man = np.array([5, 5, 5])\n", - "royalty = None\n", - "king = None\n", + "royalty = queen - women\n", + "king = royalty + man\n", "\n" ] }, @@ -52,13 +52,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test passed for [5]\n", + "Test passed for [3.2 0.1]\n", + "Test passed for [-2 2 2]\n", + "Test passed for [70 2 28 36 36 7 34 99 33 82]\n" + ] + } + ], "source": [ + "\"\"\"\n", + "I wrote vector_magnitude two different ways, the commented version use \n", + "a for loop to sum the square of each element and then return the square \n", + "root of that sum. In the second version I compute everything in one line. \n", + "\"\"\"\n", + "\n", + "\n", + "# def vector_magnitude(np_vector: npt.NDArray) -> np.float64:\n", + "# sum = 0 \n", + "# for num in np_vector:\n", + "# sum += num**2 \n", + "\n", + "# return sum**0.5\n", + "\n", "def vector_magnitude(np_vector: npt.NDArray) -> np.float64:\n", - " #Write your code here\n", - " return \n", + " return sum((np_vector**2))**0.5\n", "\n", "def test_vector_magnitude(np_vector: npt.NDArray) -> None:\n", " if vector_magnitude(np_vector) == np.linalg.norm(np_vector):\n", @@ -75,7 +99,7 @@ "test_vector_magnitude(d1_vector)\n", "test_vector_magnitude(d2_vector)\n", "test_vector_magnitude(d3_vector)\n", - "test_vector_magnitude(d10_vector)" + "test_vector_magnitude(d10_vector)\n" ] }, { @@ -90,15 +114,37 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test passed for [1.]\n", + "Test passed for [0.99951208 0.03123475]\n", + "Test passed for [-0.57735027 0.57735027 0.57735027]\n" + ] + } + ], "source": [ "d1_unit_vector = np.array([1.])\n", "d2_unit_vector = np.array([0.99951208, 0.03123475])\n", "d3_unit_vector = np.array([-0.57735027, 0.57735027, 0.57735027])\n", "\n", - "#Impliment vector_magnitude and test_vector_magnitude here" + "#Impliment vector_magnitude and test_vector_magnitude here\n", + "def create_unit_vector(arr):\n", + " return arr * (1 / vector_magnitude(arr))\n", + "\n", + "def test_create_unit_vector(arr, test_arr):\n", + " if np.allclose(create_unit_vector(arr), test_arr):\n", + " print(f\"Test passed for {test_arr}\")\n", + " else:\n", + " print(f\"Test failed for {test_arr}\")\n", + "\n", + "test_create_unit_vector(create_unit_vector(d1_vector), d1_unit_vector)\n", + "test_create_unit_vector(create_unit_vector(d2_vector), d2_unit_vector)\n", + "test_create_unit_vector(create_unit_vector(d3_vector), d3_unit_vector)" ] }, { @@ -115,10 +161,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test passed for [5 6 7] and [5 6 7]\n", + "Test passed for [2 3 4] and [7. 8. 9.]\n", + "Test passed for [0.0001 0.0002 0.0003] and [100000 200000 300000]\n" + ] + } + ], + "source": [ + "vector1 = np.array([5,6,7])\n", + "vector2_1 = np.array([2,3,4])\n", + "vector2_2 = np.array([7.0, 8.0, 9.0])\n", + "vector3_1 = np.array([0.0001, 0.0002, 0.0003])\n", + "vector3_2 = np.array([100_000, 200_000, 300_000])\n", + "\n", + "def my_dot(arr1, arr2):\n", + " return sum(arr1 * arr2)\n", + "\n", + "def test_my_dot(arr1, arr2):\n", + " if my_dot(arr1, arr2) == np.dot(arr1, arr2):\n", + " print(f\"Test passed for {arr1} and {arr2}\")\n", + " else:\n", + " print(f\"Test failed\")\n", + "\n", + "test_my_dot(vector1, vector1)\n", + "test_my_dot(vector2_1, vector2_2)\n", + "test_my_dot(vector3_1, vector3_2)" + ] }, { "cell_type": "markdown", @@ -138,15 +213,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cat 1 prediction: 21.15\n", + "Cat 1 prediction error == 3.06\n", + "\n", + "\n", + "Cat 2 prediction: 15.21\n", + "Cat 2 prediction error == 1.38\n", + "\n" + ] + } + ], "source": [ "cat_1_array = np.array([28.57, 10.435])\n", "cat_1_actual_weight = 24.21\n", "\n", "cat_2_array = np.array([19.04, 6.93])\n", - "cat_2_actual_weight = 13.831" + "cat_2_actual_weight = 13.831\n", + "\n", + "def predict_weight(arr):\n", + " return 0.23 * arr[0] + 1.07 * arr[1] + 3.412\n", + "\n", + "def prediction_error(arr, actual_weight):\n", + " return abs(predict_weight(arr) - actual_weight)\n", + "\n", + "print(f\"Cat 1 prediction: {predict_weight(cat_1_array):.2f}\")\n", + "print(f\"Cat 1 prediction error == {prediction_error(cat_1_array, cat_1_actual_weight):.2f}\\n\")\n", + "print(\"\")\n", + "print(f\"Cat 2 prediction: {predict_weight(cat_2_array):.2f}\")\n", + "print(f\"Cat 2 prediction error == {prediction_error(cat_2_array, cat_2_actual_weight):.2f}\\n\")\n" ] }, { @@ -182,10 +283,51 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loop version is faster!\n" + ] + } + ], + "source": [ + "import time\n", + "\n", + "def linear_comb_loop(scalars_arr, vectors_arr):\n", + " curr = np.array(np.zeros(3))\n", + "\n", + " for i in range(len(vectors_arr)):\n", + " curr += scalars_arr[i] * vectors_arr[i]\n", + "\n", + " return curr\n", + "\n", + "scalars_array = np.array([1, 2, -3])\n", + "vectors_array = np.array([[4,5,1], [-4,0,-4], [1,3,2]])\n", + "\n", + "def linear_comb_vectorized(scalars_arr, vectors_arr):\n", + " return np.dot(scalars_arr, vectors_arr)\n", + "\n", + "def linear_comb_speed_test(scalars_arr, vectors_arr):\n", + " start1 = time.time()\n", + " linear_comb_loop(scalars_arr, vectors_arr)\n", + " end1 = time.time() - start1\n", + "\n", + " start2 = time.time()\n", + " linear_comb_vectorized(scalars_arr, vectors_arr)\n", + " end2 = time.time() - start2\n", + "\n", + " if(end1 > end2):\n", + " print(\"Loop version is faster!\")\n", + " else:\n", + " print(\"Vectorized version is faster!\")\n", + "\n", + "linear_comb_speed_test(scalars_array, vectors_array)\n", + "\n" + ] }, { "cell_type": "markdown", @@ -198,22 +340,47 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "basis_vector = np.array([1,3])\n", + "rand_dist = np.random.uniform(-4, 4, 100)\n", + "\n", + "\"\"\"\n", + "this is how I originally completed the problem\n", + "\n", + "sub_space = np.zeros((100, 2))\n", + "for i in range(len(rand_dist)):\n", + " sub_space[i] = rand_dist[i] * basis_vector\n", + "\"\"\"\n", + "sub_space = rand_dist[:, None] * basis_vector" + ] }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "def plot_vectors(vectors):\n", " plt.scatter(*zip(*vectors))\n", - " plt.show()" + " plt.show()\n", + "\n", + "plot_vectors(sub_space)" ] }, { @@ -259,13 +426,98 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Non mean-centered vector tests: \n", + "Pearson function passed.\n", + "Cosine test passed.\n", + "My functions pearson and cosine functions are NOT equal to each other.\n", + "------------------------------------------------\n", + "Mean-centered vector tests: \n", + "Pearson function passed.\n", + "Cosine test passed.\n", + "My functions pearson and cosine functions are NOT equal to each other.\n" + ] + } + ], + "source": [ + "from scipy.spatial.distance import cosine\n", + "\n", + "# non-mean centered vectors\n", + "coeff_arr1 = np.array([2,3,4])\n", + "coeff_arr2 = np.array([5,6,7])\n", + "\n", + "# mean centered vectors\n", + "arr1_mean_centered = coeff_arr1 - coeff_arr1.mean()\n", + "arr2_mean_centered = coeff_arr2 - coeff_arr2.mean()\n", + "\n", + "def pearson_corr(x_arr, y_arr):\n", + " x_mean = x_arr - np.mean(x_arr)\n", + " y_mean = y_arr - np.mean(y_arr)\n", + " numerator = np.sum((x_mean) * (y_mean)) \n", + " denominator = np.sqrt((np.sum((x_mean)**2)) * (np.sum((y_mean)**2)))\n", + " return numerator / denominator\n", + "\n", + "def cosine_simil(x_arr, y_arr):\n", + " numerator = np.dot(x_arr, y_arr)\n", + " denominator = np.linalg.norm(x_arr) * np.linalg.norm(y_arr)\n", + " return numerator / denominator\n", + "\n", + "def test_pearson(arr1, arr2):\n", + " if (pearson_corr(arr1, arr2)) == (np.corrcoef(arr1, arr2)[0,1]):\n", + " print(\"Pearson function passed.\")\n", + " else:\n", + " print(\"Pearson function failed.\")\n", + "\n", + "def test_cosine(arr1, arr2):\n", + " if np.isclose((cosine_simil(arr1, arr2)), (1 - cosine(arr1, arr2))):\n", + " print(\"Cosine test passed.\")\n", + " else:\n", + " print(\"Cosine test failed.\")\n", + "\n", + "def test_person_cosine_equality(arr1, arr2):\n", + " # if (np.isclose((pearson_corr(arr1, arr2)), (cosine_simil(arr1, arr2)))):\n", + " if pearson_corr(arr1, arr2) == cosine_simil(arr1, arr2):\n", + " print(\"Both of my functions are equal to each other.\")\n", + " else:\n", + " print(\"My functions pearson and cosine functions are NOT equal to each other.\")\n", + "\n", + "\n", + "print(\"Non mean-centered vector tests: \")\n", + "test_pearson(coeff_arr1, coeff_arr2)\n", + "test_cosine(coeff_arr1, coeff_arr2)\n", + "test_person_cosine_equality(coeff_arr1, coeff_arr2)\n", + "\n", + "print(\"------------------------------------------------\")\n", + "print(\"Mean-centered vector tests: \")\n", + "test_pearson(arr1_mean_centered, arr2_mean_centered)\n", + "test_cosine(arr1_mean_centered, arr2_mean_centered)\n", + "test_person_cosine_equality(arr1_mean_centered, arr2_mean_centered)\n", + "\n", + "\n", + "\"\"\"\n", + "I used np.isclose() in the cosine test because they are comparing two floating point \n", + "numbers. Since computers have issues with floating point numbers (especiallly in equality \n", + "comparison), I chose to use the isclose() numpy function since that is testing if they \n", + "are close, which they are. By doing this, my cosine tests passed for both non-mean and \n", + "mean centered vectors. \n", + "\n", + "For the test_person_cosine_equality is is printing that they are not equal as expected. \n", + "In the book it states that these two functions can give different results for the same data \n", + "because the functions start from different assumptions.\n", + "\"\"\";\n", + "\n", + "\n", + "\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -279,7 +531,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_6_eda_matrix.ipynb b/week_6_eda_matrix.ipynb index 1e2044d..b53ddfc 100644 --- a/week_6_eda_matrix.ipynb +++ b/week_6_eda_matrix.ipynb @@ -113,7 +113,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -137,9 +137,84 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
YearAge GroupDeath Rate
019001-4 Years1983.8
119011-4 Years1695.0
219021-4 Years1655.7
319031-4 Years1542.1
419041-4 Years1591.5
\n", + "
" + ], + "text/plain": [ + " Year Age Group Death Rate\n", + "0 1900 1-4 Years 1983.8\n", + "1 1901 1-4 Years 1695.0\n", + "2 1902 1-4 Years 1655.7\n", + "3 1903 1-4 Years 1542.1\n", + "4 1904 1-4 Years 1591.5" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get example data from pulic internet location\n", "url = \"https://data.cdc.gov/api/views/v6ab-adf5/rows.csv?accessType=DOWNLOAD\"\n", @@ -158,9 +233,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "('mortality_data.csv', )" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from urllib import request\n", "data_url = \"https://data.cdc.gov/api/views/v6ab-adf5/rows.csv?accessType=DOWNLOAD\"\n", @@ -232,9 +318,77 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'cities': [{'name': 'Anchorage', 'pop': 250000, 'region': 'south-central'},\n", + " {'name': 'Fairbanks', 'pop': 75000, 'region': 'interior'},\n", + " {'name': 'Juneau', 'pop': 25000, 'region': 'south-east'}],\n", + " 'industries': ['fishing', 'mining', 'tourism'],\n", + " 'state': 'AK'}\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
namepop
0Anchorage250000
1Fairbanks75000
2Juneau25000
\n", + "
" + ], + "text/plain": [ + " name pop\n", + "0 Anchorage 250000\n", + "1 Fairbanks 75000\n", + "2 Juneau 25000" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#\n", "json_string = \"\"\"\n", @@ -319,13 +473,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# retrieve sample data\n", "download_url = (\"https://raw.githubusercontent.com/fivethirtyeight/data/master/bechdel/movies.csv\")\n", - "movie_df = pd.read_csv(download_url)" + "movie_df = pd.read_csv(download_url)\n" ] }, { @@ -343,10 +497,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "rows/oberservations: 1794\n", + "columns/features/variables: 15\n" + ] + } + ], + "source": [ + "rows, columns = movie_df.shape\n", + "print(f\"rows/oberservations: {rows}\")\n", + "print(f\"columns/features/variables: {columns}\")" + ] }, { "cell_type": "markdown", @@ -362,10 +529,286 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
yearimdbtitletestclean_testbinarybudgetdomgrossintgrosscodebudget_2013$domgross_2013$intgross_2013$period codedecade code
02013tt171142521 &amp; OvernotalknotalkFAIL1300000025682380.042195766.02013FAIL1300000025682380.042195766.01.01.0
12012tt1343727Dredd 3Dok-disagreeokPASS4500000013414714.040868994.02012PASS4565873513611086.041467257.01.01.0
22013tt202454412 Years a Slavenotalk-disagreenotalkFAIL2000000053107035.0158607035.02013FAIL2000000053107035.0158607035.01.01.0
32013tt12728782 GunsnotalknotalkFAIL6100000075612460.0132493015.02013FAIL6100000075612460.0132493015.01.01.0
42013tt045356242menmenFAIL4000000095020213.095020213.02013FAIL4000000095020213.095020213.01.01.0
52013tt133597547 RoninmenmenFAIL22500000038362475.0145803842.02013FAIL22500000038362475.0145803842.01.01.0
62013tt1606378A Good Day to Die HardnotalknotalkFAIL9200000067349198.0304249198.02013FAIL9200000067349198.0304249198.01.01.0
72013tt2194499About Timeok-disagreeokPASS1200000015323921.087324746.02013PASS1200000015323921.087324746.01.01.0
82013tt1814621AdmissionokokPASS1300000018007317.018007317.02013PASS1300000018007317.018007317.01.01.0
92013tt1815862After EarthnotalknotalkFAIL13000000060522097.0244373198.02013FAIL13000000060522097.0244373198.01.01.0
\n", + "
" + ], + "text/plain": [ + " year imdb title test clean_test binary \\\n", + "0 2013 tt1711425 21 & Over notalk notalk FAIL \n", + "1 2012 tt1343727 Dredd 3D ok-disagree ok PASS \n", + "2 2013 tt2024544 12 Years a Slave notalk-disagree notalk FAIL \n", + "3 2013 tt1272878 2 Guns notalk notalk FAIL \n", + "4 2013 tt0453562 42 men men FAIL \n", + "5 2013 tt1335975 47 Ronin men men FAIL \n", + "6 2013 tt1606378 A Good Day to Die Hard notalk notalk FAIL \n", + "7 2013 tt2194499 About Time ok-disagree ok PASS \n", + "8 2013 tt1814621 Admission ok ok PASS \n", + "9 2013 tt1815862 After Earth notalk notalk FAIL \n", + "\n", + " budget domgross intgross code budget_2013$ domgross_2013$ \\\n", + "0 13000000 25682380.0 42195766.0 2013FAIL 13000000 25682380.0 \n", + "1 45000000 13414714.0 40868994.0 2012PASS 45658735 13611086.0 \n", + "2 20000000 53107035.0 158607035.0 2013FAIL 20000000 53107035.0 \n", + "3 61000000 75612460.0 132493015.0 2013FAIL 61000000 75612460.0 \n", + "4 40000000 95020213.0 95020213.0 2013FAIL 40000000 95020213.0 \n", + "5 225000000 38362475.0 145803842.0 2013FAIL 225000000 38362475.0 \n", + "6 92000000 67349198.0 304249198.0 2013FAIL 92000000 67349198.0 \n", + "7 12000000 15323921.0 87324746.0 2013PASS 12000000 15323921.0 \n", + "8 13000000 18007317.0 18007317.0 2013PASS 13000000 18007317.0 \n", + "9 130000000 60522097.0 244373198.0 2013FAIL 130000000 60522097.0 \n", + "\n", + " intgross_2013$ period code decade code \n", + "0 42195766.0 1.0 1.0 \n", + "1 41467257.0 1.0 1.0 \n", + "2 158607035.0 1.0 1.0 \n", + "3 132493015.0 1.0 1.0 \n", + "4 95020213.0 1.0 1.0 \n", + "5 145803842.0 1.0 1.0 \n", + "6 304249198.0 1.0 1.0 \n", + "7 87324746.0 1.0 1.0 \n", + "8 18007317.0 1.0 1.0 \n", + "9 244373198.0 1.0 1.0 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "The data has information about various movies with the year it came out, IMBD number, \n", + "budget, domestic gross, internation gross along with some information about codes and test. \n", + "\n", + "No variables have yet to be defined as dependent, so it depends on what we may or may \n", + "not be trying to predict. \n", + "\"\"\";\n", + "\n", + "movie_df.head(10)" + ] }, { "cell_type": "markdown", @@ -381,17 +824,221 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1794 entries, 0 to 1793\n", + "Data columns (total 15 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 year 1794 non-null int64 \n", + " 1 imdb 1794 non-null object \n", + " 2 title 1794 non-null object \n", + " 3 test 1794 non-null object \n", + " 4 clean_test 1794 non-null object \n", + " 5 binary 1794 non-null object \n", + " 6 budget 1794 non-null int64 \n", + " 7 domgross 1777 non-null float64\n", + " 8 intgross 1783 non-null float64\n", + " 9 code 1794 non-null object \n", + " 10 budget_2013$ 1794 non-null int64 \n", + " 11 domgross_2013$ 1776 non-null float64\n", + " 12 intgross_2013$ 1783 non-null float64\n", + " 13 period code 1615 non-null float64\n", + " 14 decade code 1615 non-null float64\n", + "dtypes: float64(6), int64(3), object(6)\n", + "memory usage: 210.4+ KB\n" + ] + } + ], + "source": [ + "\"\"\" \n", + "Yes, there is some missing information as we can see from 'Non-Null Count' column below. We \n", + "can see that domgross, intgross, domgross_2013$ and intgross_2013$ are all missing around 18 or \n", + "fewer data points. While period code and decade code are both missing 179 data points. \n", + "\"\"\"\n", + "\n", + "movie_df.info()" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
yearbudgetdomgrossintgrossbudget_2013$domgross_2013$intgross_2013$period codedecade code
count1794.0000001.794000e+031.777000e+031.783000e+031.794000e+031.776000e+031.783000e+031615.0000001615.000000
mean2002.5523974.482646e+076.913205e+071.503857e+085.546461e+079.517478e+071.978380e+082.4198141.937461
std8.9797314.818603e+078.036731e+072.103353e+085.491864e+071.259653e+082.835079e+081.1946200.690116
min1970.0000007.000000e+030.000000e+008.280000e+028.632000e+038.990000e+028.990000e+021.0000001.000000
25%1998.0000001.200000e+071.631157e+072.612947e+071.606892e+072.054659e+073.323260e+071.0000001.000000
50%2005.0000002.800000e+074.219406e+077.648246e+073.699579e+075.599364e+079.623964e+072.0000002.000000
75%2009.0000006.000000e+079.335492e+071.898509e+087.833790e+071.216784e+082.414790e+083.0000002.000000
max2013.0000004.250000e+087.605076e+082.783919e+094.614359e+081.771683e+093.171931e+095.0000003.000000
\n", + "
" + ], + "text/plain": [ + " year budget domgross intgross budget_2013$ \\\n", + "count 1794.000000 1.794000e+03 1.777000e+03 1.783000e+03 1.794000e+03 \n", + "mean 2002.552397 4.482646e+07 6.913205e+07 1.503857e+08 5.546461e+07 \n", + "std 8.979731 4.818603e+07 8.036731e+07 2.103353e+08 5.491864e+07 \n", + "min 1970.000000 7.000000e+03 0.000000e+00 8.280000e+02 8.632000e+03 \n", + "25% 1998.000000 1.200000e+07 1.631157e+07 2.612947e+07 1.606892e+07 \n", + "50% 2005.000000 2.800000e+07 4.219406e+07 7.648246e+07 3.699579e+07 \n", + "75% 2009.000000 6.000000e+07 9.335492e+07 1.898509e+08 7.833790e+07 \n", + "max 2013.000000 4.250000e+08 7.605076e+08 2.783919e+09 4.614359e+08 \n", + "\n", + " domgross_2013$ intgross_2013$ period code decade code \n", + "count 1.776000e+03 1.783000e+03 1615.000000 1615.000000 \n", + "mean 9.517478e+07 1.978380e+08 2.419814 1.937461 \n", + "std 1.259653e+08 2.835079e+08 1.194620 0.690116 \n", + "min 8.990000e+02 8.990000e+02 1.000000 1.000000 \n", + "25% 2.054659e+07 3.323260e+07 1.000000 1.000000 \n", + "50% 5.599364e+07 9.623964e+07 2.000000 2.000000 \n", + "75% 1.216784e+08 2.414790e+08 3.000000 2.000000 \n", + "max 1.771683e+09 3.171931e+09 5.000000 3.000000 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "I would consider the primary statistics to be count, mean and standard deviation. Those would \n", + "let me know how much data and information about how it is distributed.\n", + "\"\"\"\n", + "\n", + "movie_df.describe()" + ] }, { "cell_type": "markdown", @@ -407,10 +1054,50 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1794 entries, 0 to 1793\n", + "Data columns (total 15 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 year 1794 non-null int64 \n", + " 1 imdb 1794 non-null object \n", + " 2 title 1794 non-null object \n", + " 3 test 1794 non-null object \n", + " 4 clean_test 1794 non-null object \n", + " 5 binary 1794 non-null object \n", + " 6 budget 1794 non-null int64 \n", + " 7 domgross 1777 non-null float64\n", + " 8 intgross 1783 non-null float64\n", + " 9 code 1794 non-null object \n", + " 10 budget_2013$ 1794 non-null int64 \n", + " 11 domgross_2013$ 1776 non-null float64\n", + " 12 intgross_2013$ 1783 non-null float64\n", + " 13 period code 1615 non-null float64\n", + " 14 decade code 1615 non-null float64\n", + "dtypes: float64(6), int64(3), object(6)\n", + "memory usage: 210.4+ KB\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "There are int64, object and float64 data types. \n", + "\n", + "The data types for year, budget, domgross, intgross, budget_2013$, domgross_2013$, ingross_2013$, \n", + "period code and decade code are numerical. \n", + "\n", + "IMBD, title, test, clean_test, binary and code are categorical. \n", + "\"\"\"\n", + "\n", + "movie_df.info()" + ] }, { "cell_type": "markdown", @@ -452,10 +1139,56 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "NUMERIC FEATURES: \n", + "Index(['year', 'budget', 'domgross', 'intgross', 'budget_2013$',\n", + " 'domgross_2013$', 'intgross_2013$', 'period code', 'decade code'],\n", + " dtype='object')\n", + "Index(['year', 'budget', 'domgross', 'intgross', 'budget_2013$',\n", + " 'domgross_2013$', 'intgross_2013$', 'period code', 'decade code'],\n", + " dtype='object')\n", + "\n", + "Both numeric objects are equal\n", + "------------------------------------------------------------------------------------\n", + "CATEGORICAL FEATURES: \n", + "Index(['imdb', 'title', 'test', 'clean_test', 'binary', 'code'], dtype='object')\n", + "Index(['imdb', 'title', 'test', 'clean_test', 'binary', 'code'], dtype='object')\n", + "\n", + "Both categorical objects are equal\n" + ] + } + ], + "source": [ + "# using dtypes and columns\n", + "numeric_features1 = movie_df.columns[movie_df.dtypes.isin([np.dtype(\"int64\"), np.dtype(\"float64\")])]\n", + "categorical_features1 = movie_df.columns[movie_df.dtypes.isin([np.dtype(\"object\")])]\n", + "\n", + "# using select_dtypes and columns\n", + "numeric_features2 = movie_df.select_dtypes(include=['int64', 'float64']).columns\n", + "categorical_features2 = movie_df.select_dtypes(include=['object']).columns\n", + "\n", + "print(\"NUMERIC FEATURES: \")\n", + "print(numeric_features1)\n", + "print(numeric_features2)\n", + "if numeric_features1.equals(numeric_features2):\n", + " print(\"\\nBoth numeric objects are equal\")\n", + "else:\n", + " print(\"\\nBoth numeric objects are NOT equal\")\n", + "print(\"------------------------------------------------------------------------------------\")\n", + "print(\"CATEGORICAL FEATURES: \")\n", + "print(categorical_features1)\n", + "print(categorical_features2)\n", + "if categorical_features1.equals(categorical_features2):\n", + " print(\"\\nBoth categorical objects are equal\")\n", + "else:\n", + " print(\"\\nBoth categorical objects are NOT equal\")\n" + ] }, { "cell_type": "markdown", @@ -467,10 +1200,53 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "test (unique = 10)\n", + "test\n", + "ok 696\n", + "notalk 379\n", + "notalk-disagree 135\n", + "men 125\n", + "ok-disagree 107\n", + "nowomen 88\n", + "dubious 81\n", + "men-disagree 69\n", + "dubious-disagree 61\n", + "nowomen-disagree 53\n", + "Name: count, dtype: int64\n", + "\n", + "clean_test (unique = 5)\n", + "clean_test\n", + "ok 803\n", + "notalk 514\n", + "men 194\n", + "dubious 142\n", + "nowomen 141\n", + "Name: count, dtype: int64\n", + "\n", + "binary (unique = 2)\n", + "binary\n", + "FAIL 991\n", + "PASS 803\n", + "Name: count, dtype: int64\n" + ] + } + ], + "source": [ + "for col in categorical_features2:\n", + " n_unique = movie_df[col].nunique() # number of distinct categories\n", + " if n_unique <= 10:\n", + " print(f\"\\n{col} (unique = {n_unique})\")\n", + " print(movie_df[col].value_counts())\n", + "\n" + ] }, { "cell_type": "markdown", @@ -490,10 +1266,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "movie_df[numeric_features2].plot.hist()\n", + "plt.show()\n", + "\n" + ] }, { "cell_type": "markdown", @@ -514,17 +1305,62 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from pandas.plotting import scatter_matrix\n", + "\n", + "numerical_subset = pd.Index(['budget', 'domgross', 'intgross', 'budget_2013$', 'domgross_2013$', 'intgross_2013$'])\n", + "\"\"\" \n", + "The two lines commented out below were my original code. The plots were really messy and column names overlapped each other. \n", + "I got the code below from AI to clean it up. \n", + "\"\"\"\n", + "# scatter_matrix(movie_df[numerical_subset])\n", + "# plt.show()\n", + "\n", + "scatter_matrix(\n", + " movie_df[numerical_subset],\n", + " figsize=(12, 12),\n", + " diagonal=\"hist\",\n", + " alpha=0.5,\n", + " s=10\n", + ")\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.pairplot(movie_df[numerical_subset])\n", + "plt.show()" + ] }, { "cell_type": "markdown", @@ -548,8 +1384,81 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using a for loop: \n", + "[[ 2. 6. 5.]\n", + " [ 0. -2. 6.]]\n", + "----------------------------------\n", + "Using numpy vectorization: \n", + "[[ 2 6 5]\n", + " [ 0 -2 6]]\n", + "----------------------------------\n", + "\n", + "\n", + "\n" + ] + }, + { + "ename": "ValueError", + "evalue": "operands could not be broadcast together with shapes (3,3) (2,3) ", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[51], line 43\u001b[0m\n\u001b[1;32m 36\u001b[0m add4 \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([ [\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m3\u001b[39m,\u001b[38;5;241m4\u001b[39m], \n\u001b[1;32m 37\u001b[0m [\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m4\u001b[39m], \n\u001b[1;32m 38\u001b[0m [\u001b[38;5;241m7\u001b[39m,\u001b[38;5;241m8\u001b[39m,\u001b[38;5;241m9\u001b[39m] ])\n\u001b[1;32m 40\u001b[0m add5 \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([ [\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m3\u001b[39m,\u001b[38;5;241m1\u001b[39m], \n\u001b[1;32m 41\u001b[0m [\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m4\u001b[39m,\u001b[38;5;241m2\u001b[39m] ])\n\u001b[0;32m---> 43\u001b[0m add6 \u001b[38;5;241m=\u001b[39m \u001b[43madd4\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43madd5\u001b[49m\n", + "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (3,3) (2,3) " + ] + } + ], + "source": [ + "def add_loop(arr1, arr2):\n", + " if arr1.shape == arr2.shape:\n", + " sol = np.zeros(arr1.shape)\n", + " for i in range(arr1.shape[0]):\n", + " for j in range(len(arr2[0])):\n", + " sol[i][j] = arr1[i][j] + arr2[i][j]\n", + "\n", + " return sol\n", + " else:\n", + " print(\"You cannot add two arrays of different sizes.\")\n", + " return -1\n", + "\n", + "\n", + "add1 = np.array([ [2,3,4], [1,2,4] ])\n", + "add2 = np.array([ [0,3,1], [-1,-4,2] ])\n", + "add3 = add1 + add2\n", + "print(\"Using a for loop: \")\n", + "print(add_loop(add1, add2))\n", + "print(\"----------------------------------\")\n", + "print(\"Using numpy vectorization: \")\n", + "print(add3)\n", + "print(\"----------------------------------\\n\\n\\n\")\n", + "\n", + "\n", + "\"\"\"\n", + "You cannot add two matrices together of different sizes. add4 is a 3 element \n", + "array while add5 is a two element array. When you attempt to add them an error \n", + "is throw because it takes the third element of add4 and tries to add it to the \n", + "third element in add5, but that element does not exist. Thus the error is thrown.\n", + "\n", + "In consideration of the for loop above, I did not attempt to add two matrices of \n", + "differing sizes together as the function has a built in check and returns a print \n", + "statement indicating an error along with a return value of -1. \n", + "\"\"\";\n", + "\n", + "add4 = np.array([ [2,3,4], \n", + " [1,2,4], \n", + " [7,8,9] ])\n", + "\n", + "add5 = np.array([ [0,3,1], \n", + " [-1,-4,2] ])\n", + "\n", + "add6 = add4 + add5" + ] }, { "cell_type": "markdown", @@ -562,10 +1471,79 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Vectorized matrix multiplication: \n", + "[[ 58 64]\n", + " [139 154]]\n", + "-------------------------\n", + "For loop matrix multiplication: \n" + ] + }, + { + "data": { + "text/plain": [ + "array([[ 58., 64.],\n", + " [139., 154.]])" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"\n", + "This function below is super hacky, but it works. I created the flag variable \n", + "as I needed to ability to use an index that was separate from the i and j variables \n", + "in the for loops. This will also only work if the first array is 2 dimensional. \n", + "\"\"\"\n", + "def mult_loop(arr1, arr2):\n", + " length = arr1.shape[1]\n", + " flag1 = 1\n", + " curr1 = 0\n", + " curr2 = 0\n", + " curr_arr = np.array([])\n", + "\n", + " for i in range(length - 1):\n", + " for j in range(length):\n", + " curr1 += ( arr1[i][j] * arr2[j][i] )\n", + " curr2 += ( arr1[i][j] * arr2[j][flag1] )\n", + " flag1 = 0\n", + " curr_arr = np.append(curr_arr, np.array([curr1, curr2]))\n", + " curr1 = 0\n", + " curr2 = 0\n", + " if i == 0:\n", + " sol = curr_arr.copy()\n", + " if i == 1:\n", + " sol2 = np.vstack([sol, curr_arr])\n", + " curr_arr = np.array([])\n", + "\n", + " sol2[1] = sol2[1][::-1]\n", + " return sol2\n", + "\n", + "# shape = (2,3)\n", + "mult1 = np.array([ [1,2,3], \n", + " [4,5,6] ])\n", + "\n", + "# shape = (3,2)\n", + "mult2 = np.array([ [7,8], \n", + " [9,10],\n", + " [11,12] ])\n", + "\n", + "print(\"Vectorized matrix multiplication: \")\n", + "print(mult1@mult2)\n", + "print(\"-------------------------\")\n", + "print(\"For loop matrix multiplication: \")\n", + "sol = mult_loop(mult1, mult2)\n", + "sol\n", + "\n" + ] }, { "cell_type": "markdown", @@ -584,10 +1562,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 123, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Success! Everything worked correctly.\n" + ] + } + ], + "source": [ + "A = np.random.rand(3)\n", + "B = np.random.rand(3)\n", + "scalar = 5\n", + "eq1 = scalar * (A + B)\n", + "eq2 = scalar * A + scalar * B\n", + "eq3 = A * scalar + B * scalar\n", + "\n", + "if np.allclose(eq1, eq2) and np.allclose(eq2, eq3):\n", + " print(\"Success! Everything worked correctly.\")\n", + "else:\n", + " print(\"Everything is NOT matching up.\")" + ] }, { "cell_type": "markdown", @@ -600,15 +1598,45 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Testing a symetrix matrix, should print True: True\n", + "Testing a non-symetric matrix, should print False: False\n" + ] + } + ], + "source": [ + "def check_symetry(arr):\n", + " if np.allclose(arr, arr.T):\n", + " return True \n", + " else:\n", + " return False\n", + " \n", + " \n", + "\n", + "sym_arr1 = np.array([ [1,2,3], \n", + " [2,5,8], \n", + " [3,8,9] ])\n", + "\n", + "sym_arr2 = np.array([ [1,2,3], \n", + " [4,5,6], \n", + " [7,8,9] ])\n", + "\n", + "\n", + "\n", + "print(\"Testing a symetrix matrix, should print True:\", check_symetry(sym_arr1))\n", + "print(\"Testing a non-symetric matrix, should print False:\", check_symetry(sym_arr2))" + ] } ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -622,7 +1650,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_7_data_cleaning_matrix.ipynb b/week_7_data_cleaning_matrix.ipynb index 7c066ef..1156738 100644 --- a/week_7_data_cleaning_matrix.ipynb +++ b/week_7_data_cleaning_matrix.ipynb @@ -56,9 +56,260 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
IMBD title IDOriginal titlÊRelease yearGenrë¨DurationCountryContent RatingDirectorUnnamed: 8IncomeVotesScore
count10010010010099100771000.0100100100
unique10010099597118764NaN10010028
toptt0111161The Shawshank Redemption2000-05-19Drama130USARChristopher NolanNaN$ 288152452.278.8458.6
freq1129362456NaN1111
meanNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
stdNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
minNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
25%NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
50%NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
75%NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
maxNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", + "
" + ], + "text/plain": [ + " IMBD title ID Original titlÊ Release year Genrë¨ Duration \\\n", + "count 100 100 100 100 99 \n", + "unique 100 100 99 59 71 \n", + "top tt0111161 The Shawshank Redemption 2000-05-19 Drama 130 \n", + "freq 1 1 2 9 3 \n", + "mean NaN NaN NaN NaN NaN \n", + "std NaN NaN NaN NaN NaN \n", + "min NaN NaN NaN NaN NaN \n", + "25% NaN NaN NaN NaN NaN \n", + "50% NaN NaN NaN NaN NaN \n", + "75% NaN NaN NaN NaN NaN \n", + "max NaN NaN NaN NaN NaN \n", + "\n", + " Country Content Rating Director Unnamed: 8 Income \\\n", + "count 100 77 100 0.0 100 \n", + "unique 18 7 64 NaN 100 \n", + "top USA R Christopher Nolan NaN $ 28815245 \n", + "freq 62 45 6 NaN 1 \n", + "mean NaN NaN NaN NaN NaN \n", + "std NaN NaN NaN NaN NaN \n", + "min NaN NaN NaN NaN NaN \n", + "25% NaN NaN NaN NaN NaN \n", + "50% NaN NaN NaN NaN NaN \n", + "75% NaN NaN NaN NaN NaN \n", + "max NaN NaN NaN NaN NaN \n", + "\n", + " Votes Score \n", + "count 100 100 \n", + "unique 100 28 \n", + "top 2.278.845 8.6 \n", + "freq 1 11 \n", + "mean NaN NaN \n", + "std NaN NaN \n", + "min NaN NaN \n", + "25% NaN NaN \n", + "50% NaN NaN \n", + "75% NaN NaN \n", + "max NaN NaN " + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import pandas as pd \n", "import importlib\n", @@ -95,13 +346,159 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
imbd_title_idoriginal_titlerelease_yeargenredurationcountrycontent_ratingdirectorunnamed:_8incomevotesscore
0tt0111161The Shawshank Redemption1995-02-10Drama142USARFrank DarabontNaN$ 288152452.278.8459.3
1tt0068646The Godfather09 21 1972Crime, Drama175USARFrancis Ford CoppolaNaN$ 2461209741.572.6749.2
2tt0468569The Dark Knight23 -07-2008Action, Crime, Drama152USPG-13Christopher NolanNaN$ 10054552112.241.6159.
3tt0071562The Godfather: Part II1975-09-25Crime, Drama220USARFrancis Ford CoppolaNaN$ 4o8,035,7831.098.7149,.0
4tt0110912Pulp Fiction1994-10-28Crime, DramaUSARQuentin TarantinoNaN$ 2228318171.780.1478,9f
\n", + "
" + ], + "text/plain": [ + " imbd_title_id original_title release_year genre \\\n", + "0 tt0111161 The Shawshank Redemption 1995-02-10 Drama \n", + "1 tt0068646 The Godfather 09 21 1972 Crime, Drama \n", + "2 tt0468569 The Dark Knight 23 -07-2008 Action, Crime, Drama \n", + "3 tt0071562 The Godfather: Part II 1975-09-25 Crime, Drama \n", + "4 tt0110912 Pulp Fiction 1994-10-28 Crime, Drama \n", + "\n", + " duration country content_rating director unnamed:_8 \\\n", + "0 142 USA R Frank Darabont NaN \n", + "1 175 USA R Francis Ford Coppola NaN \n", + "2 152 US PG-13 Christopher Nolan NaN \n", + "3 220 USA R Francis Ford Coppola NaN \n", + "4 USA R Quentin Tarantino NaN \n", + "\n", + " income votes score \n", + "0 $ 28815245 2.278.845 9.3 \n", + "1 $ 246120974 1.572.674 9.2 \n", + "2 $ 1005455211 2.241.615 9. \n", + "3 $ 4o8,035,783 1.098.714 9,.0 \n", + "4 $ 222831817 1.780.147 8,9f " + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ + "importlib.reload(data_processing)\n", "from data_processing import rename_columns\n", "df_columns_renamed = rename_columns(df_raw)\n", - "df_columns_renamed.head()" + "df_columns_renamed.head()\n", + "\n", + "\n" ] }, { @@ -150,9 +547,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(100, 11)" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "importlib.reload(data_processing)\n", "from data_processing import remove_fully_null_columns_rows\n", @@ -191,9 +599,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "content_rating\n", + "R 45\n", + "Unrated 25\n", + "PG-13 12\n", + "PG 11\n", + "G 6\n", + "Approved 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "importlib.reload(data_processing)\n", "from data_processing import clean_and_fill_content_rating\n", @@ -220,9 +646,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 52, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 100 entries, 0 to 100\n", + "Data columns (total 11 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 imbd_title_id 100 non-null object\n", + " 1 original_title 100 non-null object\n", + " 2 release_year 100 non-null object\n", + " 3 genre 100 non-null object\n", + " 4 duration 99 non-null object\n", + " 5 country 100 non-null object\n", + " 6 content_rating 100 non-null object\n", + " 7 director 100 non-null object\n", + " 8 income 100 non-null object\n", + " 9 votes 100 non-null object\n", + " 10 score 100 non-null object\n", + "dtypes: object(11)\n", + "memory usage: 9.4+ KB\n" + ] + } + ], "source": [ "df_clean_content_rating.info()" ] @@ -245,22 +696,163 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "importlib.reload(data_processing)\n", "from data_processing import clean_release_year\n", "\n", - "\n", "df_clean_release_year_temp = clean_release_year(df_clean_content_rating)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
release_yearrelease_year_coercerelease_year_mixedoriginal_title
109 21 1972NaT1972-09-21The Godfather
223 -07-2008NaT2008-07-23The Dark Knight
522 Feb 04NaT2004-02-22The Lord of the Rings: The Return of the King
910-29-99NaT1999-10-29Fight Club
1223rd December of 1966NaT1966-12-23Il buono, il brutto, il cattivo
1501/16-03NaT2003-01-16The Lord of the Rings: The Two Towers
1818/11/1976NaT1976-11-18One Flew Over the Cuckoo's Nest
4521-11-46NaT2046-11-21Casablanca
70The 6th of marzo, year 1951NaTNaTSunset Blvd.
831984-02-34NaTNaTScarface
841976-13-24NaTNaTTaxi Driver
\n", + "
" + ], + "text/plain": [ + " release_year release_year_coerce release_year_mixed \\\n", + "1 09 21 1972 NaT 1972-09-21 \n", + "2 23 -07-2008 NaT 2008-07-23 \n", + "5 22 Feb 04 NaT 2004-02-22 \n", + "9 10-29-99 NaT 1999-10-29 \n", + "12 23rd December of 1966 NaT 1966-12-23 \n", + "15 01/16-03 NaT 2003-01-16 \n", + "18 18/11/1976 NaT 1976-11-18 \n", + "45 21-11-46 NaT 2046-11-21 \n", + "70 The 6th of marzo, year 1951 NaT NaT \n", + "83 1984-02-34 NaT NaT \n", + "84 1976-13-24 NaT NaT \n", + "\n", + " original_title \n", + "1 The Godfather \n", + "2 The Dark Knight \n", + "5 The Lord of the Rings: The Return of the King \n", + "9 Fight Club \n", + "12 Il buono, il brutto, il cattivo \n", + "15 The Lord of the Rings: The Two Towers \n", + "18 One Flew Over the Cuckoo's Nest \n", + "45 Casablanca \n", + "70 Sunset Blvd. \n", + "83 Scarface \n", + "84 Taxi Driver " + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_clean_release_year_temp[df_fully_null_removed['release_year_coerce'].isna()\n", " ][['release_year', 'release_year_coerce', \n", @@ -269,7 +861,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 109, "metadata": {}, "outputs": [], "source": [ @@ -288,21 +880,52 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 110, "metadata": {}, "outputs": [], "source": [ "importlib.reload(data_processing)\n", "from data_processing import clean_income\n", "\n", - "df_clean_income = clean_income(df_clean_release_year)" + "df_clean_income = clean_income(df_clean_release_year)\n", + "# I ran the code below as a test\n", + "# print(df_clean_income.iloc[0:50][\"income\"])\n", + "# print(df_clean_income.iloc[51:][\"income\"])\n", + "\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 111, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 96 entries, 0 to 100\n", + "Data columns (total 13 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 imbd_title_id 96 non-null object \n", + " 1 original_title 96 non-null object \n", + " 2 release_year 96 non-null object \n", + " 3 genre 96 non-null object \n", + " 4 duration 95 non-null object \n", + " 5 country 96 non-null object \n", + " 6 content_rating 96 non-null object \n", + " 7 director 96 non-null object \n", + " 8 income 96 non-null Int64 \n", + " 9 votes 96 non-null object \n", + " 10 score 96 non-null object \n", + " 11 release_year_coerce 89 non-null datetime64[ns]\n", + " 12 release_year_mixed 96 non-null datetime64[ns]\n", + "dtypes: Int64(1), datetime64[ns](2), object(10)\n", + "memory usage: 10.6+ KB\n" + ] + } + ], "source": [ "df_clean_income.info()" ] @@ -339,28 +962,313 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAGzCAYAAADaCpaHAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjUsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvWftoOwAAAAlwSFlzAAAPYQAAD2EBqD+naQAARhJJREFUeJzt3XlcVPX+x/H3gDAgwuACogWIS5q5r2Gbllf0pqmZ2nJTstTKMtMWvZVLqbh0q1u3MlvQNrNNK2+W5nq7oWVXMk1NDbcU1wBXEOf7+2N+TI6gAjIMB17Px2Meeb5zzpnPmRmdd+d8zjk2Y4wRAACARfn5ugAAAICLQZgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgByhibzabx48f7ugyfmT59uurWrSt/f3+1aNHC1+WUmI4dO6pjx44XnM9ms+mBBx7wfkFAOUKYAcq4o0ePaty4ceratauqVasmm82mWbNmFXr5L7/80jLhaNGiRXrsscd01VVXKTk5WZMnT/Z1SRXaq6++qr59+yomJkY2m02JiYm+LgkoUCVfFwDg/A4ePKinn35aMTExat68uZYvX16k5b/88ku9/PLLlgg0S5culZ+fn958800FBgb6upwKb+rUqTpy5IjatWunvXv3+roc4JwIM8B5HDt2TCEhIT6toVatWtq7d6+ioqK0Zs0atW3b1muvlZubK6fT6bMgsX//fgUHB5fY6xtjdPLkSQUHB5fI+iqaFStWuPfKVKlSxdflAOfEYSbg/40fP142m02//PKLbr/9dlWtWlVXX321JGndunVKTExU3bp1FRQUpKioKA0aNEiHDh0qcB1bt25VYmKiwsPD5XA4dNddd+n48eMe82ZnZ+vhhx9WRESEQkNDddNNN2n37t356rLb7YqKiirWNiUmJurll1+W5OrFyHtI0vbt22Wz2fTss8/qhRdeUL169WS32/XLL78oJydHY8eOVevWreVwOBQSEqJrrrlGy5Yt81j/meuYOXOmex1t27bVDz/84DFvenq67rrrLl166aWy2+2qVauWevbsqe3bt7vrS05O1rFjx9x15h1Oy83N1TPPPONef506dfT3v/9d2dnZHq9Rp04dde/eXV9//bXatGmj4OBgvfbaa1q+fLlsNps+/PBDTZgwQZdccolCQ0N1yy23KDMzU9nZ2RoxYoQiIyNVpUoV3XXXXfnWLUnvvvuuWrdureDgYFWrVk233nqrdu3alW++vPciODhY7dq103/+858if3bvvfeeGjZsqKCgILVu3VorV650P7ds2TLZbDbNmzcv33Lvv/++bDabUlJSzrv+jIwMPfzww6pTp47sdrsuvfRSDRgwQAcPHnTPExsb6/6+AGUZe2aAs/Tt21cNGjTQ5MmTZYyRJC1evFi//fab7rrrLkVFRWnDhg2aOXOmNmzYoFWrVuX7B79fv36Ki4tTUlKS/ve//+mNN95QZGSkpk6d6p7nnnvu0bvvvqvbb79dHTp00NKlS3XjjTeW6LYMHTpUe/bs0eLFi/XOO+8UOE9ycrJOnjypIUOGyG63q1q1asrKytIbb7yh2267TYMHD9aRI0f05ptvKiEhQd9//32+xtz3339fR44c0dChQ2Wz2TRt2jTdfPPN+u233xQQECBJ6tOnjzZs2KAHH3xQderU0f79+7V48WLt3LlTderU0TvvvKOZM2fq+++/1xtvvCFJ6tChg/u9mj17tm655RaNGjVKq1evVlJSkjZu3JjvB33z5s267bbbNHToUA0ePFgNGzZ0P5eUlKTg4GCNHj1aW7du1UsvvaSAgAD5+fnpjz/+0Pjx47Vq1SrNmjVLcXFxGjt2rHvZSZMm6amnnlK/fv10zz336MCBA3rppZd07bXXau3atQoPD5ckvfnmmxo6dKg6dOigESNG6LffftNNN92katWqKTo6ulCf24oVKzR37lwNHz5cdrtdr7zyirp27arvv/9eTZo0UceOHRUdHa333ntPvXv39lj2vffeU7169RQfH3/O9R89elTXXHONNm7cqEGDBqlVq1Y6ePCgPv/8c+3evVs1atQoVJ1AmWEAGGOMGTdunJFkbrvttnzPHT9+PN/YnDlzjCSzcuXKfOsYNGiQx7y9e/c21atXd0+npqYaSeb+++/3mO/22283ksy4ceMKrPGHH34wkkxycnKht2vYsGGmoL/qaWlpRpIJCwsz+/fv93guNzfXZGdne4z98ccfpmbNmh7blreO6tWrm8OHD7vHP/vsMyPJfPHFF+5lJZnp06eft9aBAweakJAQj7G89+qee+7xGH/kkUeMJLN06VL3WGxsrJFkvvrqK495ly1bZiSZJk2amJycHPf4bbfdZmw2m+nWrZvH/PHx8SY2NtY9vX37duPv728mTZrkMd/PP/9sKlWq5B7PyckxkZGRpkWLFh7v38yZM40kc9111513+40xRpKRZNasWeMe27FjhwkKCjK9e/d2j40ZM8bY7XaTkZHhHtu/f7+pVKnSOb8/ecaOHWskmU8//TTfc06ns8BlQkJCzMCBAy9YP+ALHGYCznLvvffmGzuz5+LkyZM6ePCgrrzySknS//73vwuu45prrtGhQ4eUlZUlydWUK0nDhw/3mG/EiBEXVXtx9OnTRxERER5j/v7+7r4Vp9Opw4cPKzc3V23atClwe/v376+qVau6p6+55hpJ0m+//SZJ7j6Y5cuX648//ihSfXnv1ciRIz3GR40aJUn697//7TEeFxenhISEAtc1YMAA954iSWrfvr2MMRo0aJDHfO3bt9euXbuUm5srSfr000/ldDrVr18/HTx40P2IiopSgwYN3Iff1qxZo/379+vee+/16PtJTEyUw+Eo9DbHx8erdevW7umYmBj17NlTX3/9tU6fPu3eluzsbH388cfu+ebOnavc3Fz97W9/O+/6P/nkEzVv3jzfXh1JHFaCJRFmgLPExcXlGzt8+LAeeugh1axZU8HBwYqIiHDPl5mZmW/+mJgYj+m8H/q8H/IdO3bIz89P9erV85jvzEMipaWg7ZWk2bNnq1mzZgoKClL16tUVERGhf//738XaXrvdrqlTp2rhwoWqWbOmrr32Wk2bNk3p6ekXrC/vvapfv77HeFRUlMLDw7Vjx45CbU9BdeYFjLMP/zgcDjmdTve2btmyRcYYNWjQQBERER6PjRs3av/+/e5aJalBgwYe6wsICFDdunUvuK15zl5eki677DIdP35cBw4ckCQ1atRIbdu21Xvvveee57333tOVV16Z770627Zt29SkSZNC1wOUdfTMAGcp6MyXfv366bvvvtOjjz6qFi1aqEqVKnI6nerataucTme++f39/Qtct/n/HpyypKDtfffdd5WYmKhevXrp0UcfVWRkpPz9/ZWUlKRt27blm78w2ztixAj16NFD8+fP19dff62nnnpKSUlJWrp0qVq2bHnBOgu7x+B8Zy6dq84L1e90OmWz2bRw4cIC5/XVmT4DBgzQQw89pN27dys7O1urVq3Sv/71L5/UAvgSYQa4gD/++ENLlizRhAkTPBpCt2zZUux1xsbGyul0atu2bR57YzZv3nxRtRakOIcNPv74Y9WtW1effvqpx/Ljxo27qFrq1aunUaNGadSoUdqyZYtatGihf/zjH3r33XfPuUzee7VlyxZdfvnl7vF9+/YpIyNDsbGxF1VTYes2xiguLk6XXXbZeWuVXN+N66+/3j1+6tQppaWlqXnz5oV6vYK+W7/++qsqV67scUjw1ltv1ciRIzVnzhydOHFCAQEB6t+/f6G2Z/369YWqBbACDjMBF5D3f+Jn71V54YUXir3Obt26SZJefPHFElvnueRdJycjI6PQyxS0zatXr77g6b7ncvz4cZ08edJjrF69egoNDS3wFOgz/fWvf5WU/7157rnnJKnEzwAryM033yx/f39NmDAh3/fAGOM+Rb9NmzaKiIjQjBkzlJOT455n1qxZRXr/U1JSPHqTdu3apc8++0xdunTx2DNUo0YNdevWTe+++67ee+89de3atVBnIvXp00c//fRTgad2l8W9h8CFsGcGuICwsDB3j8epU6d0ySWXaNGiRUpLSyv2Olu0aKHbbrtNr7zyijIzM9WhQwctWbJEW7duLXD+f/3rX8rIyNCePXskSV988YX7mjQPPvjgeZtL8xpJhw8froSEBPn7++vWW289b33du3fXp59+qt69e+vGG29UWlqaZsyYocaNG+vo0aNF3t5ff/1VN9xwg/r166fGjRurUqVKmjdvnvbt23fBWpo3b66BAwdq5syZysjI0HXXXafvv/9es2fPVq9evdSpU6ci11NU9erV08SJEzVmzBht375dvXr1UmhoqNLS0jRv3jwNGTJEjzzyiAICAjRx4kQNHTpU119/vfr376+0tDQlJycXqWemSZMmSkhI8Dg1W5ImTJiQb94BAwbolltukSQ988wzhVr/o48+qo8//lh9+/bVoEGD1Lp1ax0+fFiff/65ZsyY4d6D9MUXX+inn36S5Nq7tG7dOk2cOFGSdNNNN6lZs2aF3ibAq3x0FhVQ5uSdVn3gwIF8z+3evdv07t3bhIeHG4fDYfr27Wv27NmT7zTqc60jOTnZSDJpaWnusRMnTpjhw4eb6tWrm5CQENOjRw+za9euAk/NzjvluKDHmessSG5urnnwwQdNRESEsdls7tO0806rLuh0aafTaSZPnmxiY2ON3W43LVu2NAsWLDADBw70OGX5fOs4czsOHjxohg0bZho1amRCQkKMw+Ew7du3Nx9++KHHMgWdmm2MMadOnTITJkwwcXFxJiAgwERHR5sxY8aYkydP5nufbrzxxnzL552a/dFHH3mM530uP/zwg8f4uT7HTz75xFx99dUmJCTEhISEmEaNGplhw4aZzZs3e8z3yiuvmLi4OGO3202bNm3MypUrzXXXXVfoU7OHDRtm3n33XdOgQQP3+79s2bIC58/OzjZVq1Y1DofDnDhx4oLrz3Po0CHzwAMPmEsuucQEBgaaSy+91AwcONAcPHjQPc/AgQPP+b0ryuUBAG+zGcM+RQCwqtzcXNWuXVs9evTQm2++6etyAJ+gZwYALGz+/Pk6cOCABgwY4OtSAJ9hzwwAWNDq1au1bt06PfPMM6pRo0aBFzMEKgr2zACABb366qu67777FBkZqbffftvX5QA+5dUwk5SUpLZt2yo0NFSRkZHq1atXvutonDx5UsOGDVP16tVVpUoV9enTR/v27fNmWQBgebNmzVJubq7WrFnD1XxR4Xk1zKxYsULDhg3TqlWrtHjxYp06dUpdunTRsWPH3PM8/PDD+uKLL/TRRx9pxYoV2rNnj26++WZvlgUAAMqRUu2ZOXDggCIjI7VixQpde+21yszMVEREhN5//333dRI2bdqkyy+/XCkpKe4b+QEAAJxLqV40L++mbdWqVZMk/fjjjzp16pQ6d+7snqdRo0aKiYk5Z5jJzs72uGJo3h19q1evzt1eAQCwCGOMjhw5otq1a8vP7+IOFJVamHE6nRoxYoSuuuoq9/Hd9PR0BQYGKjw83GPemjVrnvNuuklJSQVeBRMAAFjPrl27dOmll17UOkotzAwbNkzr16/Xt99+e1HrGTNmjEaOHOmezszMVExMjHbt2qWwsLCLLRMAAJSCrKwsRUdHKzQ09KLXVSph5oEHHtCCBQu0cuVKj/QVFRWlnJwcZWRkeOyd2bdvn6Kiogpcl91ul91uzzceFhZGmAEAwGJKokXEq2czGWP0wAMPaN68eVq6dKni4uI8nm/durUCAgK0ZMkS99jmzZu1c+dOxcfHe7M0AABQTnh1z8ywYcP0/vvv67PPPlNoaKi7D8bhcCg4OFgOh0N33323Ro4cqWrVqiksLEwPPvig4uPjOZMJAAAUildPzT7XrqPk5GQlJiZKcl00b9SoUZozZ46ys7OVkJCgV1555ZyHmc6WlZUlh8OhzMxMDjMBAGARJfn7bfl7MxFmAMC3jDHKzc3V6dOnfV0KyhB/f39VqlTpnDs2SvL3u1SvMwMAKF9ycnK0d+9eHT9+3NeloAyqXLmyatWqpcDAQK++DmEGAFAsTqdTaWlp8vf3V+3atRUYGMjFSyHJtbcuJydHBw4cUFpamho0aHDRF8Y7H8IMAKBYcnJy5HQ6FR0drcqVK/u6HJQxwcHBCggI0I4dO5STk6OgoCCvvZZXT80GAJR/3vw/blhbaX03+AYCAABLI8wAAABLI8wAAEqczVa6j9K2fft22Ww2paamFnqZWbNm5buxsi/qKI8IMwCACmvXrl0aNGiQ+2ys2NhYPfTQQzp06NB5l4uOjtbevXvVpEmTQr9W//799euvv15sySgAYQYAUCH99ttvatOmjbZs2aI5c+Zo69atmjFjhpYsWaL4+HgdPny4wOVycnLk7++vqKgoVapU+JOCg4ODFRkZWVLl4wyEGQBAhTRs2DAFBgZq0aJFuu666xQTE6Nu3brpm2++0e+//64nnnhCklSnTh0988wzGjBggMLCwjRkyJACD+98/vnnatCggYKCgtSpUyfNnj1bNptNGRkZkvIfZho/frxatGihd955R3Xq1JHD4dCtt96qI0eOuOf56quvdPXVVys8PFzVq1dX9+7dtW3bttJ4eyyFMAMAqHAOHz6sr7/+Wvfff7+Cg4M9nouKitIdd9yhuXPnKu+OP88++6yaN2+utWvX6qmnnsq3vrS0NN1yyy3q1auXfvrpJw0dOtQdhs5n27Ztmj9/vhYsWKAFCxZoxYoVmjJlivv5Y8eOaeTIkVqzZo2WLFkiPz8/9e7dW06n8yLfgfKFi+YBACqcLVu2yBijyy+/vMDnL7/8cv3xxx86cOCAJOn666/XqFGj3M9v377dY/7XXntNDRs21PTp0yVJDRs21Pr16zVp0qTz1uF0OjVr1iyFhoZKku68804tWbLEvVyfPn085n/rrbcUERGhX375pUj9OuUde2YAABVWYe+13KZNm/M+v3nzZrVt29ZjrF27dhdcb506ddxBRpJq1aql/fv3u6e3bNmi2267TXXr1lVYWJjq1KkjSdq5c2eh6q4oCDMAgAqnfv36stls2rhxY4HPb9y4UVWrVlVERIQkKSQkxCt1BAQEeEzbbDaPQ0g9evTQ4cOH9frrr2v16tVavXq1JFcTMv5EmAEAVDjVq1fXX/7yF73yyis6ceKEx3Pp6el677331L9//0LfOLNhw4Zas2aNx9gPP/xwUTUeOnRImzdv1pNPPqkbbrjBfegL+RFmAAAV0r/+9S9lZ2crISFBK1eu1K5du/TVV1/pL3/5iy655JIL9rucaejQodq0aZMef/xx/frrr/rwww81a9YsSSr2ncSrVq2q6tWra+bMmdq6dauWLl2qkSNHFmtd5R1hBgBQ4owp3UdxNGjQQGvWrFHdunXVr18/1atXT0OGDFGnTp2UkpKiatWqFXpdcXFx+vjjj/Xpp5+qWbNmevXVV91nM9nt9mLV5+fnpw8++EA//vijmjRpoocfftjdYAxPNlPY7qcyKisrSw6HQ5mZmQoLC/N1OQBQYZw8eVJpaWmKi4tTUFCQr8spcyZNmqQZM2Zo165dvi7FZ873HSnJ329OzQYAoAS88soratu2rapXr67//ve/mj59uh544AFfl1UhEGYAACgBW7Zs0cSJE3X48GHFxMRo1KhRGjNmjK/LqhAIMwAAlIDnn39ezz//vK/LqJBoAAYAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAlDybrXQf5UB6err+8pe/KCQkROHh4b4up9BsNpvmz5/v0xoIMwCACsVms533MX78eJ/U9fzzz2vv3r1KTU3Vr7/+6pMarIqL5gEAKpS9e/e6/zx37lyNHTtWmzdvdo9VqVLF/WdjjE6fPq1Klbz/c7lt2za1bt1aDRo0KPY6cnJyFBgYWIJVWQN7ZgAAFUpUVJT74XA4ZLPZ3NObNm1SaGioFi5cqNatW8tut+vbb7/Vtm3b1LNnT9WsWVNVqlRR27Zt9c0333ist06dOpo8ebIGDRqk0NBQxcTEaObMme7nc3Jy9MADD6hWrVoKCgpSbGyskpKS3Mt+8sknevvtt2Wz2ZSYmChJ2rlzp3r27KkqVaooLCxM/fr10759+9zrHD9+vFq0aKE33njD42aONptNr732mrp3767KlSvr8ssvV0pKirZu3aqOHTsqJCREHTp00LZt2zy24bPPPlOrVq0UFBSkunXrasKECcrNzXU/v2XLFl177bUKCgpS48aNtXjx4hL9bIqLMAMAwFlGjx6tKVOmaOPGjWrWrJmOHj2qv/71r1qyZInWrl2rrl27qkePHtq5c6fHcv/4xz/Upk0brV27Vvfff7/uu+8+916fF198UZ9//rk+/PBDbd68We+9957q1KkjSfrhhx/UtWtX9evXT3v37tU///lPOZ1O9ezZU4cPH9aKFSu0ePFi/fbbb+rfv7/Ha27dulWffPKJPv30U6WmprrHn3nmGQ0YMECpqalq1KiRbr/9dg0dOlRjxozRmjVrZIzxuBHmf/7zHw0YMEAPPfSQfvnlF7322muaNWuWJk2aJElyOp26+eabFRgYqNWrV2vGjBl6/PHHvfDuF4OxuMzMTCPJZGZm+roUAKhQTpw4YX755Rdz4sSJ/E9KpfsopuTkZONwONzTy5YtM5LM/PnzL7jsFVdcYV566SX3dGxsrPnb3/7mnnY6nSYyMtK8+uqrxhhjHnzwQXP99dcbp9NZ4Pp69uxpBg4c6J5etGiR8ff3Nzt37nSPbdiwwUgy33//vTHGmHHjxpmAgACzf/9+j3VJMk8++aR7OiUlxUgyb775pntszpw5JigoyD19ww03mMmTJ3us55133jG1atUyxhjz9ddfm0qVKpnff//d/fzChQuNJDNv3rwCt+l835GS/P1mzwwAAGdp06aNx/TRo0f1yCOP6PLLL1d4eLiqVKmijRs35tsz06xZM/ef8w5f7d+/X5KUmJio1NRUNWzYUMOHD9eiRYvOW8PGjRsVHR2t6Oho91jjxo0VHh6ujRs3usdiY2MVERGRb/kza6lZs6YkqWnTph5jJ0+eVFZWliTpp59+0tNPP60qVaq4H4MHD9bevXt1/Phxdz21a9d2ryM+Pv6821BaaAAGAOAsISEhHtOPPPKIFi9erGeffVb169dXcHCwbrnlFuXk5HjMFxAQ4DFts9nkdDolSa1atVJaWpoWLlyob775Rv369VPnzp318ccfl2itBdVi+//T1wsay6vv6NGjmjBhgm6++eZ868rrxSmrvLpnZuXKlerRo4dq165d4HnoiYmJ+U6J69q1qzdLAgCgyP773/8qMTFRvXv3VtOmTRUVFaXt27cXeT1hYWHq37+/Xn/9dc2dO1effPKJDh8+XOC8l19+uXbt2qVdu3a5x3755RdlZGSocePGxd2Uc2rVqpU2b96s+vXr53v4+fm56znzbLBVq1aVeB3F4dU9M8eOHVPz5s01aNCgApOeJHXt2lXJycnuabvd7s2SAAAosgYNGujTTz9Vjx49ZLPZ9NRTT7n3aBTWc889p1q1aqlly5by8/PTRx99pKioqHNeIK9z585q2rSp7rjjDr3wwgvKzc3V/fffr+uuuy7fYbCSMHbsWHXv3l0xMTG65ZZb5Ofnp59++knr16/XxIkT1blzZ1122WUaOHCgpk+frqysLD3xxBMlXkdxeHXPTLdu3TRx4kT17t37nPPY7XaP0+SqVq3qzZIAAKWhtFuAvey5555T1apV1aFDB/Xo0UMJCQlq1apVkdYRGhqqadOmqU2bNmrbtq22b9+uL7/8Un5+Bf8U22w2ffbZZ6pataquvfZade7cWXXr1tXcuXNLYpPySUhI0IIFC7Ro0SK1bdtWV155pZ5//nnFxsZKkvz8/DRv3jydOHFC7dq10z333OM+08nXbMaUwrdArg9l3rx56tWrl3ssMTFR8+fPV2BgoKpWrarrr79eEydOVPXq1c+5nuzsbGVnZ7uns7KyFB0drczMTIWFhXlzEwAAZzh58qTS0tI8rm8CnOl835GsrCw5HI4S+f326dlMXbt21dtvv60lS5Zo6tSpWrFihbp166bTp0+fc5mkpCQ5HA7348wubwAAUPH49GymW2+91f3npk2bqlmzZqpXr56WL1+uG264ocBlxowZo5EjR7qn8/bMAACAiqlMXWembt26qlGjhrZu3XrOeex2u8LCwjweAACg4ipTYWb37t06dOiQatWq5etSAACARXj1MNPRo0c99rKkpaUpNTVV1apVU7Vq1TRhwgT16dNHUVFR2rZtmx577DHVr19fCQkJ3iwLAFCCSuk8ElhQaX03vLpnZs2aNWrZsqVatmwpSRo5cqRatmypsWPHyt/fX+vWrdNNN92kyy67THfffbdat26t//znP1xrBgAsIO9qssePH/dxJSir8r4bZ18ZuaR5dc9Mx44dz5vKvv76a2++PADAi/z9/RUeHu6+91DlypXdl8hHxWaM0fHjx7V//36Fh4fL39/fq6/HvZkAAMUWFRUlSe5AA5wpPDzc/R3xJsIMAKDYbDabatWqpcjISJ06dcrX5aAMCQgI8PoemTyEGQDARfP39y+1Hy7gbGXq1GwAAICiIswAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABL82qYWblypXr06KHatWvLZrNp/vz5Hs8bYzR27FjVqlVLwcHB6ty5s7Zs2eLNkgAAQDnj1TBz7NgxNW/eXC+//HKBz0+bNk0vvviiZsyYodWrVyskJEQJCQk6efKkN8sCAADlSCVvrrxbt27q1q1bgc8ZY/TCCy/oySefVM+ePSVJb7/9tmrWrKn58+fr1ltv9WZpAACgnPBZz0xaWprS09PVuXNn95jD4VD79u2VkpJyzuWys7OVlZXl8QAAABWXz8JMenq6JKlmzZoe4zVr1nQ/V5CkpCQ5HA73Izo62qt1AgCAss1yZzONGTNGmZmZ7seuXbt8XRIAAPAhn4WZqKgoSdK+ffs8xvft2+d+riB2u11hYWEeDwAAUHH5LMzExcUpKipKS5YscY9lZWVp9erVio+P91VZAADAYrx6NtPRo0e1detW93RaWppSU1NVrVo1xcTEaMSIEZo4caIaNGiguLg4PfXUU6pdu7Z69erlzbIAAEA54tUws2bNGnXq1Mk9PXLkSEnSwIEDNWvWLD322GM6duyYhgwZooyMDF199dX66quvFBQU5M2yAABAOWIzxhhfF3ExsrKy5HA4lJmZSf8MAAAWUZK/35Y7mwkAAOBMhBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBplXxdAAAAyG/mTOmFF6SgINcjONj138qVpZAQ16NKFdd/w8Kk0FDJ4XA9wsKk8HCpalWpWjWpUjn/tbcZY4yvi7gYWVlZcjgcyszMVFhYmK/LAYDiczqlqVOlH36QPv3U19XAx3Jzpfr1pR07Lm49wcHS669Ld9xRMnWVlJL8/S7nWQ0ALCAnR3r8cem116QTJ6Rvv/V1RSgDKlWS1q2TYmOljIziraNPH+ndd117dMozemYAwFcyMlz/uxwS4jqecOKE1LWrdNVVvq4MZcTOna6vRFHFxkpr10off1z+g4zEnhkAKH07d0pDh0qLFrkOLeWx26WPPvJdXfC5PXukGTOkBQukjRulkyeLtnxAgDRpkvToo96pr6wizABAaVm3zhViVq0q+Pnp010dnagwjh6VkpNdGTY1VTpypPjr6txZ+uQTV/NvRePzw0zjx4+XzWbzeDRq1MjXZQFAyVm6VLriCql583MHmXr1pAcfLN26UOpyc6U5c6Tu3aUaNVxnIA0fLv3nP8UPMhER0rJl0uLFFTPISGVkz8wVV1yhb775xj1dqbyfQwagYpg7V3rsMddhpfOx2aQvviidmlCqnE5X0HjrLWnlSun336WinEMcGiq1auXa6/LUU57P+fu7DidNmiT5+XzXhG+VidRQqVIlRUVF+boMALh4Tqf00kvSxInSwYOFW+a226TLL/duXSg169dLr77q2lPy22/S6dOFXzYoSGrcWLrpJmnwYKl2bdf4Sy95zteunfTZZxI/nS5lIsxs2bJFtWvXVlBQkOLj45WUlKSYmJgC583OzlZ2drZ7Oisrq7TKBIALW7BAeuYZ6dChws0fEiLNnu3dmuBVu3e7LnD3xReupt0zfqIuqFIl1xHGLl1c7VRXXFHwfF9/7fpvWJg0a5bUu/dFl12u+PyieQsXLtTRo0fVsGFD7d27VxMmTNDvv/+u9evXKzQ0NN/848eP14QJE/KNc9E8AGXKt99Kf/+7qxnifN5/37VnBpaRleVq2v3kE9fpz0ePFn5Zm0269FKpY0dp0CDXfwujWTPpyitdZzqVl0NKJXnRPJ+HmbNlZGQoNjZWzz33nO6+++58zxe0ZyY6OpowA6BscTqlq6+WUlLOPU+LFq5fQ5Rpubmu9qf335dWry78Trc8ERFSfLzrkkI331y8WwscP+66jUF5Uq6vABweHq7LLrtMW7duLfB5u90uu91eylUBQBEcP+76X+lt2849j58fTb9lVF7T7ptvupp29+wpWtNuWJjUsqXUr580YEDJnG1f3oJMSStzYebo0aPatm2b7rzzTl+XAgBFl54uNW2av/nX39+zE3T4cNfxBpQJ69a57iZR3KbdK66QevRw9b3QlFv6fB5mHnnkEfXo0UOxsbHas2ePxo0bJ39/f93GMWQAVrNhg+s0k+PHPcdr15aWL5cuu8w1Xb269I9/lHp5+NPu3a7wknel3aI27dav72raHTLk3E27KD0+DzO7d+/WbbfdpkOHDikiIkJXX321Vq1apYiICF+XBgCFt2SJ6yY6ubme402bSmvWSIGBUni4635Mc+eWny5Oi8jKcl3r5ZNPXFfaLU7TbqdO0t13S9de67UyUUw+DzMffPCBr0sAgIvz9ttSYmL+xoouXaSFC/8MLu3auXYB3HBDqZdY0eTkSB9+6Gra/f774jft3nmn1KtX8Zp2UXr4eADgYkycmP/SrJJ0zz3S6697jj3xhKsxGCXO6XTtHEtOLn7TbqtWUt++Jde0i9JDmAGA4ho8WHrjjfzjzzwjPflk/nGOT5Sodetc11355puiN+0GB/95pd0hQ2jatTrCDAAUldPp6o9ZvNhz3GZzXZ51wACflFXe7dzpatr997+lTZuK17TbtasrvHD3iPKFMAMARZGTI7Vu7boBz5kqVZK++op+mBKU17T78cfSTz8VvWk3Otp1hV2adss/wgwAFNbhw66zk/bs8RyvXNnVZco5uhflzKbd1atdb3dRREa6mnb/9jeadisaPmoAKIy0NNftB86+uW2NGtLPP9N0UQxOp+tI3axZrltYFbVp1+H4s2l34ECukluREWYA4EJWr5auuy5/k0a9eq4uVH5FCy011dX38s03rnxYnKbdXr1cfS+Rkd6qElZDmAGA8/nkE9dNdpxOz/EOHVy7E7j43Xnt3Ok64+jf/5Y2b6ZpF95BmAGAc/nnP6URI/KP9+8vccHPAmVk/Hml3Z9+ko4dK/yyNpsUE+Nq2r3nHtdNx4HCIMwAQEFGjpSefz7/+KOPStOmlX49ZVROjivXzZnj6oEuTtNuhw6upt3evdnRheIhzADA2W65xbVr4Uw2m/Tii9IDD/impjLC6ZS+/lqaPdt1lG3v3qI37bZu7Tpyd+edtBuhZBBmACBPbq501VWuXQxn8vd3hZuePX1Tl4/973/SzJmupt3t24vetHvFFa6m3cGDadqFdxBmAEByXZGtWTPXKTZnsttduyDatvVNXT6Q17S7YIGraTcnp/DLVqokNWjgatodOlRq2NB7dQJ5CDMAsGePK8icfWtlh8PVxRob65u6SklGhvTmm9Knnxa9adfPz3Wl3U6dXE27V13ltTKBcyLMAKjY1q2TrrxSOnHCc/zSS10XwwsP90lZ3pST42rYnTNH+uGH4jXtXnWVq+elZ0+aduF7hBkAFdfixdJf/+rqlTlT8+bSmjXl5nr4eU27ycnSt99K6enFa9rt39911hFNuyhrysffVAAoquRk1x0Iz/5V79bN1Sxi8d0NeU27ixe7mnbPvubf+QQHS02auPa60LQLKyDMAKh4xo+XJkzIPz50qKvz1YJ27PC80m5RmnYDAv5s2r33XtefASshzACoWO66y3Vnw7NNniyNGVPq5RRXRob0+uvSvHmutp/iNO1ef71rz0t8vNfKBEoFYQZAxeB0Sl26SEuWeI7bbNI770h33OGbugopr2n3/fddTbt//FG05WvWdF1pd+BAqUcPyx9FAzwQZgCUfzk5UsuW0i+/eI4HBEiLFrluBlTGOJ3SV1+5diIVp2k3PPzPK+0OGCAFBXmrUsD3CDMAyrfDh12XoE1P9xwPCXHt4ihDt2Jes8bVtLtkSfGadps2/fNKuzVqeKtKoOwhzAAov7Ztc+2ROXLEczwiQlq/3uen6aSluZp2Fy4sftPuX/8qDRlC0y4qNsIMgPLpv/91dbienRAaNHB1zPrguMvhw39eaffnn4vetBsT47rSLk27gCfCDIDy5+OPXVd4O/s4zTXXSMuXl1r3a06O9N570gcfFK9pNyrK1bQ7YABNu8D5EGYAlC/PPSeNGpV//PbbXcnCi5xO6csvpdmz/2zaLYrwcKlNmz+vtEvTLlA4hBkA5cdDD0kvvph/fPRoKSnJKy/5ww+upt2lS4vetFu5sutKu717u27SSNMuUDyEGQDlQ+/e0vz5nmM2m/Tyy9J995XYy6SlSa++6mra/fXXojftXnaZq2l36FCpXr0SKwuo0AgzAKwtN9d11+sff/Qc9/d3hZvu3S9q9YcPS2+88WfT7vHjhV/Wz0+Kjf3zSrvt219UKQDOgTADwLqOHnUdp9mxw3M8KMh1NlOrVkVe5cmTrtaauXNd130pTtPuVVe5mna7d6dpFygNhBkA1rR7t9SsWf60ER4u/fST6zzmQnA6XTfJfvttV/4pTtNu27aupt077qBpF/AFwgwA60lNdZ2zfOKE53h0tOtieGFh51189WrXTRqXLnXt1Clq027TptLNN7uadqtVK3r5AEoWYQaAtSxcKN10k6tX5kytWrlSSqX8/6yd2bS7ebN06lThXy4w0NW0260bTbtAWUWYAWAdb7zhunb/2Xdc7N5d+uIL9+Thw67TpefPL17Tbp06rqbdIUNch5AAlG2EGQDW8NRT0sSJ+cfvv18n//Gy3n3jz6bdjIyirToqSrr6amngQNdp0zTtAtZCmAFQ9g0c6OrQPYOR9HaTaRr96aNKf6Voq6ta9c8r7dK0C1hfmfj/j5dffll16tRRUFCQ2rdvr++//97XJQEoC5xO150Vzwoyp+WnW/WBEtc/Wqizj0JCXJeimTpVOnTIdRhq0SLp7rsJMkB54PM9M3PnztXIkSM1Y8YMtW/fXi+88IISEhK0efNmRUZG+ro8AL5y8qSy6rVU2J5NHsM5CtAN+kbf6tpzLhoYKDVs6GravfdeKS7O28UC8CWbMWd30pWu9u3bq23btvrXv/4lSXI6nYqOjtaDDz6o0aNH55s/Oztb2dnZ7umsrCxFR0crMzNTYRc4HROAhezYodx6l6nS6T/vF3BEVdRaa7RFDT1mzWvaveEG15V2adoFyr6srCw5HI4S+f326WGmnJwc/fjjj+rcubN7zM/PT507d1ZKSkqByyQlJcnhcLgf0dHRpVUugNIUG6uM+ct1+v//mUpXpOoozR1katWSbrlF+ve/Xadab9vmOoOJIANUPD4NMwcPHtTp06dVs2ZNj/GaNWsq/RwHwseMGaPMzEz3Y9euXaVRKgAfqNE9XgODP9RatVALxw616VJDb73lulbenj3SRx9x9hGAMtAzU1R2u112u93XZQAoJfcu6qPYxn2UzpV2AZyDT8NMjRo15O/vr3379nmM79u3T1FRUT6qCkBZcvXVvq4AQFnn052zgYGBat26tZYsWeIeczqdWrJkieLj431YGQAAsAqfH2YaOXKkBg4cqDZt2qhdu3Z64YUXdOzYMd11112+Lg0AAFiAz8NM//79deDAAY0dO1bp6elq0aKFvvrqq3xNwQAAAAXx+XVmLlZJnqcOAABKR7m5zgwAAMDFIswAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABL82mYqVOnjmw2m8djypQpviwJAABYTCVfF/D0009r8ODB7unQ0FAfVgMAAKzG52EmNDRUUVFRvi4DAABYlM97ZqZMmaLq1aurZcuWmj59unJzc887f3Z2trKysjweAACg4vLpnpnhw4erVatWqlatmr777juNGTNGe/fu1XPPPXfOZZKSkjRhwoRSrBIAAJRlNmOMKckVjh49WlOnTj3vPBs3blSjRo3yjb/11lsaOnSojh49KrvdXuCy2dnZys7Odk9nZWUpOjpamZmZCgsLu7jiAQBAqcjKypLD4SiR3+8SDzMHDhzQoUOHzjtP3bp1FRgYmG98w4YNatKkiTZt2qSGDRsW6vVK8s0AAACloyR/v0v8MFNERIQiIiKKtWxqaqr8/PwUGRlZwlUBAIDyymc9MykpKVq9erU6deqk0NBQpaSk6OGHH9bf/vY3Va1a1VdlAQAAi/FZmLHb7frggw80fvx4ZWdnKy4uTg8//LBGjhzpq5IAAIAF+SzMtGrVSqtWrfLVywMAgHLC59eZAQAAuBiEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGleCzOTJk1Shw4dVLlyZYWHhxc4z86dO3XjjTeqcuXKioyM1KOPPqrc3FxvlQQAAMqhSt5acU5Ojvr27av4+Hi9+eab+Z4/ffq0brzxRkVFRem7777T3r17NWDAAAUEBGjy5MneKgsAAJQzNmOM8eYLzJo1SyNGjFBGRobH+MKFC9W9e3ft2bNHNWvWlCTNmDFDjz/+uA4cOKDAwMBCrT8rK0sOh0OZmZkKCwsr6fIBAIAXlOTvt896ZlJSUtS0aVN3kJGkhIQEZWVlacOGDedcLjs7W1lZWR4PAABQcfkszKSnp3sEGUnu6fT09HMul5SUJIfD4X5ER0d7tU4AAFC2FSnMjB49Wjab7byPTZs2eatWSdKYMWOUmZnpfuzatcurrwcAAMq2IjUAjxo1SomJieedp27duoVaV1RUlL7//nuPsX379rmfOxe73S673V6o1wAAAOVfkcJMRESEIiIiSuSF4+PjNWnSJO3fv1+RkZGSpMWLFyssLEyNGzcukdcAAADln9dOzd65c6cOHz6snTt36vTp00pNTZUk1a9fX1WqVFGXLl3UuHFj3XnnnZo2bZrS09P15JNPatiwYex5AQAAhea1U7MTExM1e/bsfOPLli1Tx44dJUk7duzQfffdp+XLlyskJEQDBw7UlClTVKlS4TMWp2YDAGA9Jfn77fXrzHgbYQYAAOspF9eZAQAAKAmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGmEGQAAYGleCzOTJk1Shw4dVLlyZYWHhxc4j81my/f44IMPvFUSAAAohyp5a8U5OTnq27ev4uPj9eabb55zvuTkZHXt2tU9fa7gAwAAUBCvhZkJEyZIkmbNmnXe+cLDwxUVFeWtMgAAQDnn856ZYcOGqUaNGmrXrp3eeustGWPOO392draysrI8HgAAoOLy2p6Zwnj66ad1/fXXq3Llylq0aJHuv/9+HT16VMOHDz/nMklJSe69PgAAADZzoV0hZxg9erSmTp163nk2btyoRo0auadnzZqlESNGKCMj44LrHzt2rJKTk7Vr165zzpOdna3s7Gz3dFZWlqKjo5WZmamwsLALbwQAAPC5rKwsORyOEvn9LtKemVGjRikxMfG889StW7fYxbRv317PPPOMsrOzZbfbC5zHbref8zkAAFDxFCnMREREKCIiwlu1KDU1VVWrViWsAACAQvNaz8zOnTt1+PBh7dy5U6dPn1ZqaqokqX79+qpSpYq++OIL7du3T1deeaWCgoK0ePFiTZ48WY888oi3SgIAAOWQ18LM2LFjNXv2bPd0y5YtJUnLli1Tx44dFRAQoJdfflkPP/ywjDGqX7++nnvuOQ0ePNhbJQEAgHKoSA3AZVFJNhABAIDSUZK/3z6/zgwAAMDFIMwAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABLI8wAAABL81qY2b59u+6++27FxcUpODhY9erV07hx45STk+Mx37p163TNNdcoKChI0dHRmjZtmrdKAgAA5VAlb61406ZNcjqdeu2111S/fn2tX79egwcP1rFjx/Tss89KkrKystSlSxd17txZM2bM0M8//6xBgwYpPDxcQ4YM8VZpAACgHLEZY0xpvdj06dP16quv6rfffpMkvfrqq3riiSeUnp6uwMBASdLo0aM1f/58bdq0qVDrzMrKksPhUGZmpsLCwrxWOwAAKDkl+fvttT0zBcnMzFS1atXc0ykpKbr22mvdQUaSEhISNHXqVP3xxx+qWrVqvnVkZ2crOzvbY52S600BAADWkPe7XRL7VEotzGzdulUvvfSS+xCTJKWnpysuLs5jvpo1a7qfKyjMJCUlacKECfnGo6OjS7hiAADgbYcOHZLD4biodRQ5zIwePVpTp0497zwbN25Uo0aN3NO///67unbtqr59+2rw4MFFr/IMY8aM0ciRI93TGRkZio2N1c6dOy/6zbCSrKwsRUdHa9euXRXq8BrbzXZXBGw3210RZGZmKiYmxuOITXEVOcyMGjVKiYmJ552nbt267j/v2bNHnTp1UocOHTRz5kyP+aKiorRv3z6PsbzpqKioAtdtt9tlt9vzjTscjgr1JcgTFhbGdlcgbHfFwnZXLBV1u/38Lv7E6iKHmYiICEVERBRq3t9//12dOnVS69atlZycnK/g+Ph4PfHEEzp16pQCAgIkSYsXL1bDhg0LPMQEAABwNq9dZ+b3339Xx44dFRMTo2effVYHDhxQenq60tPT3fPcfvvtCgwM1N13360NGzZo7ty5+uc//+lxGAkAAOB8vNYAvHjxYm3dulVbt27VpZde6vFcXueyw+HQokWLNGzYMLVu3Vo1atTQ2LFji3SNGbvdrnHjxhV46Kk8Y7vZ7oqA7Wa7KwK2++K3u1SvMwMAAFDSuDcTAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMuGme3bt+vuu+9WXFycgoODVa9ePY0bN045OTke861bt07XXHONgoKCFB0drWnTpvmo4pIzadIkdejQQZUrV1Z4eHiB89hstnyPDz74oHQLLWGF2e6dO3fqxhtvVOXKlRUZGalHH31Uubm5pVuol9WpUyffZztlyhRfl1XiXn75ZdWpU0dBQUFq3769vv/+e1+X5HXjx4/P99meeWuY8mLlypXq0aOHateuLZvNpvnz53s8b4zR2LFjVatWLQUHB6tz587asmWLb4otQRfa7sTExHyff9euXX1TbAlJSkpS27ZtFRoaqsjISPXq1UubN2/2mOfkyZMaNmyYqlevripVqqhPnz757g5wIZYNM5s2bZLT6dRrr72mDRs26Pnnn9eMGTP097//3T1PVlaWunTpotjYWP3444+aPn26xo8fn++2ClaTk5Ojvn376r777jvvfMnJydq7d6/70atXr9Ip0EsutN2nT5/WjTfeqJycHH333XeaPXu2Zs2apbFjx5Zypd739NNPe3y2Dz74oK9LKlFz587VyJEjNW7cOP3vf/9T8+bNlZCQoP379/u6NK+74oorPD7bb7/91tcllbhjx46pefPmevnllwt8ftq0aXrxxRc1Y8YMrV69WiEhIUpISNDJkydLudKSdaHtlqSuXbt6fP5z5swpxQpL3ooVKzRs2DCtWrVKixcv1qlTp9SlSxcdO3bMPc/DDz+sL774Qh999JFWrFihPXv26Oabby7aC5lyZNq0aSYuLs49/corr5iqVaua7Oxs99jjjz9uGjZs6IvySlxycrJxOBwFPifJzJs3r1TrKS3n2u4vv/zS+Pn5mfT0dPfYq6++asLCwjy+A1YXGxtrnn/+eV+X4VXt2rUzw4YNc0+fPn3a1K5d2yQlJfmwKu8bN26cad68ua/LKFVn/1vldDpNVFSUmT59unssIyPD2O12M2fOHB9U6B0F/Rs9cOBA07NnT5/UU1r2799vJJkVK1YYY1yfbUBAgPnoo4/c82zcuNFIMikpKYVer2X3zBQkMzPT4+6bKSkpuvbaaxUYGOgeS0hI0ObNm/XHH3/4osRSNWzYMNWoUUPt2rXTW2+95b7ycnmVkpKipk2bqmbNmu6xhIQEZWVlacOGDT6srORNmTJF1atXV8uWLTV9+vRydSgtJydHP/74ozp37uwe8/PzU+fOnZWSkuLDykrHli1bVLt2bdWtW1d33HGHdu7c6euSSlVaWprS09M9Pn+Hw6H27dtXiM9/+fLlioyMVMOGDXXffffp0KFDvi6pRGVmZkqS+7f6xx9/1KlTpzw+70aNGikmJqZIn7fXbmdQ2rZu3aqXXnpJzz77rHssPT1dcXFxHvPl/dClp6eX65tZPv3007r++utVuXJlLVq0SPfff7+OHj2q4cOH+7o0r0lPT/cIMpLn511eDB8+XK1atVK1atX03XffacyYMdq7d6+ee+45X5dWIg4ePKjTp08X+Flu2rTJR1WVjvbt22vWrFlq2LCh9u7dqwkTJuiaa67R+vXrFRoa6uvySkXe39WCPv/y9Pe4IF27dtXNN9+suLg4bdu2TX//+9/VrVs3paSkyN/f39flXTSn06kRI0boqquuUpMmTSS5Pu/AwMB8fZBF/bzL3J6Z0aNHF9i8eubj7H/Qfv/9d3Xt2lV9+/bV4MGDfVT5xSnOdp/PU089pauuukotW7bU448/rscee0zTp0/34hYUT0lvt1UV5X0YOXKkOnbsqGbNmunee+/VP/7xD7300kvKzs728VbgYnXr1k19+/ZVs2bNlJCQoC+//FIZGRn68MMPfV0aSsGtt96qm266SU2bNlWvXr20YMEC/fDDD1q+fLmvSysRw4YN0/r1671yMkqZ2zMzatQoJSYmnneeunXruv+8Z88ederUSR06dMjX2BsVFZWvIzpvOioqqmQKLiFF3e6iat++vZ555hllZ2eXqZuZleR2R0VF5Tvjpax+3me7mPehffv2ys3N1fbt29WwYUMvVFe6atSoIX9//wL/7pb1z7GkhYeH67LLLtPWrVt9XUqpyfuM9+3bp1q1arnH9+3bpxYtWvioKt+oW7euatSooa1bt+qGG27wdTkX5YEHHtCCBQu0cuVKj5tPR0VFKScnRxkZGR57Z4r6973MhZmIiAhFREQUat7ff/9dnTp1UuvWrZWcnCw/P88dTfHx8XriiSd06tQpBQQESHLdzbthw4Zl7hBTUba7OFJTU1W1atUyFWSkkt3u+Ph4TZo0Sfv371dkZKQk1+cdFhamxo0bl8hreMvFvA+pqany8/Nzb7PVBQYGqnXr1lqyZIn7DDyn06klS5bogQce8G1xpezo0aPatm2b7rzzTl+XUmri4uIUFRWlJUuWuMNLVlaWVq9efcEzOMub3bt369ChQx6hzmqMMXrwwQc1b948LV++PF/rR+vWrRUQEKAlS5aoT58+kqTNmzdr586dio+PL9ILWdLu3btN/fr1zQ033GB2795t9u7d637kycjIMDVr1jR33nmnWb9+vfnggw9M5cqVzWuvvebDyi/ejh07zNq1a82ECRNMlSpVzNq1a83atWvNkSNHjDHGfP755+b11183P//8s9myZYt55ZVXTOXKlc3YsWN9XPnFudB25+bmmiZNmpguXbqY1NRU89VXX5mIiAgzZswYH1decr777jvz/PPPm9TUVLNt2zbz7rvvmoiICDNgwABfl1aiPvjgA2O3282sWbPML7/8YoYMGWLCw8M9zlQrj0aNGmWWL19u0tLSzH//+1/TuXNnU6NGDbN//35fl1aijhw54v77K8k899xzZu3atWbHjh3GGGOmTJliwsPDzWeffWbWrVtnevbsaeLi4syJEyd8XPnFOd92HzlyxDzyyCMmJSXFpKWlmW+++ca0atXKNGjQwJw8edLXpRfbfffdZxwOh1m+fLnH7/Tx48fd89x7770mJibGLF261KxZs8bEx8eb+Pj4Ir2OZcNMcnKykVTg40w//fSTufrqq43dbjeXXHKJmTJlio8qLjkDBw4scLuXLVtmjDFm4cKFpkWLFqZKlSomJCTENG/e3MyYMcOcPn3at4VfpAtttzHGbN++3XTr1s0EBwebGjVqmFGjRplTp075rugS9uOPP5r27dsbh8NhgoKCzOWXX24mT55s6X/szuWll14yMTExJjAw0LRr186sWrXK1yV5Xf/+/U2tWrVMYGCgueSSS0z//v3N1q1bfV1WiVu2bFmBf5cHDhxojHGdnv3UU0+ZmjVrGrvdbm644QazefNm3xZdAs633cePHzddunQxERERJiAgwMTGxprBgwdbPsCf63c6OTnZPc+JEyfM/fffb6pWrWoqV65sevfu7bFjojBs//9iAAAAllTmzmYCAAAoCsIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwtP8DPW22r9DmvKwAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", + "k = 2\n", "\n", + "a1 = np.array([ [0,1], [1,0] ]) # refliction in line y = x\n", + "a2 = np.array([ [1,0], [0,-1] ]) # reflection in y-axis\n", + "a3 = np.array([ [-1,0], [0,1] ]) # reflection in the line x = 0\n", "\n", + "b1 = np.array([ [k,0], [0,1] ]) # enlarges x in first array by k\n", + "b2 = np.array([ [1,0], [0,k] ]) # enlarges y in second array by k\n", + "b3 = np.array([ [k, 0], [0, k] ])\n", "\n", + "c1 = np.array([ [1,k], [0,1] ]) # second vector moves to the right (along x-axis) k times\n", + "c2 = np.array([ [1,0], [k,1] ]) # first vector moves up (along y-axis) k times\n", "\n", - "quiver = plt.quiver([0, 0], # Sets the x-cordinate of the start of the vectors\n", - " [0, 0], # Sets the y-cordinate of the start of the vectors\n", - " [1, -1], # Sets the x-cordinate of the end of the vectors\n", - " [1, -1], # Sets the y-cordinate of the end of the vectors\n", - " angles='xy', \n", - " scale_units='xy', \n", - " scale=1,\n", - " color=['r','b'])\n", - "plt.xlim(-2, 2)\n", - "plt.ylim(-2, 2)\n", - "plt.quiverkey(quiver, 1, 1, 1, 'orginal vector', coordinates='data')\n", - "plt.quiverkey(quiver, -1, -1.5, 1, 'transformed vector', coordinates='data')\n", - "plt.title('Description of Transformation')\n", - "plt.show()" + "d1 = np.array([ [-1,0], [0,-1] ]) # 180 degree rotation\n", + "d2 = np.array([ [0,1], [-1,0] ]) # 90 degrees clockwise\n", + "d3 = np.array([ [0,-1], [1,0] ]) # 90 degrees counter clockwise\n", + "\n", + "rand1 = np.random.randint(0,9, size=(2,1))\n", + "rand2 = np.random.randint(0,9, size=(2,1))\n", + "\n", + "# THIS IS THE ORIGNIAL CODE FROM THE ASSIGNMENT\n", + "# quiver = plt.quiver([0, 0], # Sets the x-cordinate of the start of the vectors\n", + "# [0, 0], # Sets the y-cordinate of the start of the vectors\n", + "# [1, -1], # Sets the x-cordinate of the end of the vectors\n", + "# [1, -1], # Sets the y-cordinate of the end of the vectors\n", + "# angles='xy', \n", + "# scale_units='xy', \n", + "# scale=1,\n", + "# color=['r','b'])\n", + "# plt.xlim(-2, 2)\n", + "# plt.ylim(-2, 2)\n", + "# plt.quiverkey(quiver, 1, 1, 1, 'orginal vector', coordinates='data')\n", + "# plt.quiverkey(quiver, -1, -1.5, 1, 'transformed vector', coordinates='data')\n", + "# plt.title('Description of Transformation')\n", + "# plt.show()\n", + "\n", + "matrices = [a1, a2, a3, b1, b2, b3, c1, c2, d1, d2, d3]\n", + "matrices_strings = [\"a1\", \"a2\", \"a3\", \"b1\", \"b2\", \"b3\", \"c1\", \"c2\", \"d1\", \"d2\", \"d3\"]\n", + "randoms = [rand1, rand2]\n", + "\n", + "for i in range(len(matrices)):\n", + " for j in range(len(randoms)):\n", + " curr_matrix = matrices[i]\n", + " curr_rand = randoms[j]\n", + " transformed = curr_matrix @ curr_rand\n", + " \n", + " # quiver = plt.quiver(\n", + " # [0, 0], [0, 0], \n", + " # [curr_rand[0, 0], transformed[0, 0]], \n", + " # [curr_rand[1, 0], transformed[1, 0]], \n", + " # angles=\"xy\", scale_units=\"xy\", scale=1,\n", + " # color=[\"r\", \"b\"]\n", + " # )\n", + "\n", + " quiver = plt.quiver(\n", + " [0, 0], [0, 0], \n", + " transformed[0, 0], \n", + " transformed[1, 0], \n", + " angles=\"xy\", scale_units=\"xy\", scale=1,\n", + " color=\"b\",\n", + " label=\"Original\"\n", + " )\n", + "\n", + " quiver = plt.quiver(\n", + " [0, 0], [0, 0], \n", + " curr_rand[0, 0], \n", + " curr_rand[1, 0], \n", + " angles=\"xy\", scale_units=\"xy\", scale=1,\n", + " color=\"r\",\n", + " label=\"Transformed\"\n", + " )\n", + "\n", + " plt.xlim(-20, 20)\n", + " plt.ylim(-20, 20)\n", + "\n", + " plt.quiverkey(quiver, 6, 9, 1, \"\", coordinates=\"data\")\n", + " plt.quiverkey(quiver, 6, 8, 1, \"\", coordinates=\"data\")\n", + "\n", + " plt.title(f\"rand{j+1} transformed by {matrices_strings[i]}\")\n", + " plt.legend()\n", + " plt.show()\n", + "\n" ] }, { @@ -383,15 +1291,99 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 159, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Live transposed: \n", + " [[-1.16892322 -5.17937728]\n", + " [-0.13395911 5.57947295]] \n", + "\n", + "This thows an error becuase L has a shape of (2,6) and I has a shape of (6,3) \n", + "if you tranpose them then you are trying to perform matrix multiplication on two matrices \n", + "where the inner shapes do not match. L transposed has a shape of (6,2) and I transposed has \n", + "a shape of (3,6). You cannot perform matrix multiplication a (6,2) and a (3,6) matrix.\n", + "\n", + "Evil individually transposed \n", + " [[-1.16892322 -5.17937728]\n", + " [-0.13395911 5.57947295]]\n", + "You can see that this has the same result as live_transposed.\n", + "\n", + "Squares live transposed: \n", + " [[ 1.81055355 -0.64153822]\n", + " [-1.45006407 0.50700586]] \n", + "\n", + "Live squares individual transposed: \n", + " [[-0.76817289 -2.26482368]\n", + " [-0.38549051 -1.1205261 ]]\n", + "This does not match squares_transposed or evil_squares_individual. Although it does \n", + "not throw an error like the other set above because regardless of whether or not you transpose \n", + "you can still perform matrix multiplication on all of the differen square matrices. \n", + "\n", + "Evil squares individually transposed: \n", + " [[ 1.81055355 -0.64153822]\n", + " [-1.45006407 0.50700586]]\n", + "You can see that this has the same result as squares_transposed.\n", + "\n" + ] + } + ], + "source": [ + "# 1\n", + "L = np.random.randn(2,6)\n", + "I = np.random.randn(6,3)\n", + "V = np.random.randn(3,5)\n", + "E = np.random.randn(5,2)\n", + "\n", + "# 2\n", + "live_transposed = (L @ I @ V @ E).T\n", + "print(\"Live transposed:\", \"\\n\",live_transposed, \"\\n\")\n", + "\n", + "# 3\n", + "try:\n", + " live_individual_transposed = L.T @ I.T @ V.T @ E.T\n", + " print()\n", + "except:\n", + " print(\"This thows an error becuase L has a shape of (2,6) and I has a shape of (6,3) \\n\" \\\n", + " \"if you tranpose them then you are trying to perform matrix multiplication on two matrices \\n\" \\\n", + " \"where the inner shapes do not match. L transposed has a shape of (6,2) and I transposed has \\n\" \\\n", + " \"a shape of (3,6). You cannot perform matrix multiplication a (6,2) and a (3,6) matrix.\\n\")\n", + "\n", + "# 4\n", + "evil_individual = E.T @ V.T @ I.T @ L.T \n", + "print(\"Evil individually transposed\", \"\\n\", evil_individual)\n", + "print(\"You can see that this has the same result as live_transposed.\\n\")\n", + "\n", + "# 5 (1)\n", + "L_square = np.random.randn(2,2)\n", + "I_square = np.random.randn(2,2)\n", + "V_square = np.random.randn(2,2)\n", + "E_square = np.random.randn(2,2)\n", + "\n", + "# 5 (2)\n", + "squares_transposed = (L_square @ I_square @ V_square @ E_square).T\n", + "print(\"Squares live transposed: \", \"\\n\", squares_transposed, \"\\n\")\n", + "\n", + "#5 (3)\n", + "live_squares_individual_transposed = L_square.T @ I_square.T @ V_square.T @ E_square.T\n", + "print(\"Live squares individual transposed: \\n\", live_squares_individual_transposed)\n", + "print(\"This does not match squares_transposed or evil_squares_individual. Although it does \\n\" \\\n", + "\"not throw an error like the other set above because regardless of whether or not you transpose \\n\" \\\n", + "\"you can still perform matrix multiplication on all of the differen square matrices. \\n\")\n", + "\n", + "#5 (4)\n", + "evil_squares_individual = E_square.T @ V_square.T @ I_square.T @ L_square.T \n", + "print(\"Evil squares individually transposed: \", \"\\n\", evil_squares_individual)\n", + "print(\"You can see that this has the same result as squares_transposed.\\n\")\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -405,7 +1397,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_8_joining.ipynb b/week_8_joining.ipynb index 4b2d34a..327bc8c 100644 --- a/week_8_joining.ipynb +++ b/week_8_joining.ipynb @@ -94,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -104,9 +104,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "df_1: \n", + " ints threes\n", + "0 0 0.0\n", + "1 1 0.0\n", + "2 2 0.0\n", + "3 3 3.0\n", + "4 4 3.0\n", + ".. ... ...\n", + "95 95 93.0\n", + "96 96 96.0\n", + "97 97 96.0\n", + "98 98 96.0\n", + "99 99 99.0\n", + "\n", + "[100 rows x 2 columns] \n", + "\n", + "\n", + "df_2: \n", + " ints evens threes\n", + "-10 -10 -20 -12.0\n", + "-9 -9 -18 -9.0\n", + "-8 -8 -16 -9.0\n", + "-7 -7 -14 -9.0\n", + "-6 -6 -12 -6.0\n", + "-5 -5 -10 -6.0\n", + "-4 -4 -8 -6.0\n", + "-3 -3 -6 -3.0\n", + "-2 -2 -4 -3.0\n", + "-1 -1 -2 -3.0\n", + "0 0 0 0.0\n", + "1 1 2 0.0\n", + "2 2 4 0.0\n", + "3 3 6 3.0\n", + "4 4 8 3.0\n", + "5 5 10 3.0\n", + "6 6 12 6.0\n", + "7 7 14 6.0\n", + "8 8 16 6.0\n", + "9 9 18 9.0\n" + ] + } + ], "source": [ "df_1 = pd.DataFrame({\"ints\": range(100)})\n", "df_2 = pd.DataFrame({\"ints\": range(-10, 10)}, index=range(-10, 10))\n", @@ -115,7 +161,12 @@ "df_1['threes'] = np.floor(df_1['ints']/3) * 3\n", "\n", "df_2['evens'] = df_2['ints']*2\n", - "df_2['threes'] = np.floor(df_2['ints']/3) * 3" + "df_2['threes'] = np.floor(df_2['ints']/3) * 3\n", + "\n", + "print(\"df_1: \")\n", + "print(df_1,\"\\n\\n\")\n", + "print(\"df_2: \")\n", + "print(df_2)" ] }, { @@ -131,17 +182,288 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
intsthrees_xevensthrees_y
000.000.0
110.020.0
220.040.0
333.063.0
443.083.0
553.0103.0
666.0126.0
776.0146.0
886.0166.0
999.0189.0
\n", + "
" + ], + "text/plain": [ + " ints threes_x evens threes_y\n", + "0 0 0.0 0 0.0\n", + "1 1 0.0 2 0.0\n", + "2 2 0.0 4 0.0\n", + "3 3 3.0 6 3.0\n", + "4 4 3.0 8 3.0\n", + "5 5 3.0 10 3.0\n", + "6 6 6.0 12 6.0\n", + "7 7 6.0 14 6.0\n", + "8 8 6.0 16 6.0\n", + "9 9 9.0 18 9.0" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_3 = pd.merge(df_1, df_2, on=\"ints\")\n", + "df_3" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
intsints_leftthrees_leftints_rightevensthrees_right
0000.0000.0
1110.0120.0
2220.0240.0
3333.0363.0
4443.0483.0
5553.05103.0
6666.06126.0
7776.07146.0
8886.08166.0
9999.09189.0
\n", + "
" + ], + "text/plain": [ + " ints ints_left threes_left ints_right evens threes_right\n", + "0 0 0 0.0 0 0 0.0\n", + "1 1 1 0.0 1 2 0.0\n", + "2 2 2 0.0 2 4 0.0\n", + "3 3 3 3.0 3 6 3.0\n", + "4 4 4 3.0 4 8 3.0\n", + "5 5 5 3.0 5 10 3.0\n", + "6 6 6 6.0 6 12 6.0\n", + "7 7 7 6.0 7 14 6.0\n", + "8 8 8 6.0 8 16 6.0\n", + "9 9 9 9.0 9 18 9.0" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_4 = df_1.join(df_2, on=\"ints\", how=\"inner\", lsuffix=\"_left\", rsuffix=\"_right\")\n", + "\n", + "df_4" + ] }, { "cell_type": "markdown", @@ -163,24 +485,498 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
intsthrees_xevensthrees_y
000.00.00.0
110.02.00.0
220.04.00.0
333.06.03.0
443.08.03.0
...............
959593.0NaNNaN
969696.0NaNNaN
979796.0NaNNaN
989896.0NaNNaN
999999.0NaNNaN
\n", + "

100 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " ints threes_x evens threes_y\n", + "0 0 0.0 0.0 0.0\n", + "1 1 0.0 2.0 0.0\n", + "2 2 0.0 4.0 0.0\n", + "3 3 3.0 6.0 3.0\n", + "4 4 3.0 8.0 3.0\n", + ".. ... ... ... ...\n", + "95 95 93.0 NaN NaN\n", + "96 96 96.0 NaN NaN\n", + "97 97 96.0 NaN NaN\n", + "98 98 96.0 NaN NaN\n", + "99 99 99.0 NaN NaN\n", + "\n", + "[100 rows x 4 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_5 = pd.merge(df_1, df_2, on=\"ints\", how=\"left\")\n", + "df_5" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
intsthrees_xevensthrees_y
0-10NaN-20-12.0
1-9NaN-18-9.0
2-8NaN-16-9.0
3-7NaN-14-9.0
4-6NaN-12-6.0
5-5NaN-10-6.0
6-4NaN-8-6.0
7-3NaN-6-3.0
8-2NaN-4-3.0
9-1NaN-2-3.0
1000.000.0
1110.020.0
1220.040.0
1333.063.0
1443.083.0
1553.0103.0
1666.0126.0
1776.0146.0
1886.0166.0
1999.0189.0
\n", + "
" + ], + "text/plain": [ + " ints threes_x evens threes_y\n", + "0 -10 NaN -20 -12.0\n", + "1 -9 NaN -18 -9.0\n", + "2 -8 NaN -16 -9.0\n", + "3 -7 NaN -14 -9.0\n", + "4 -6 NaN -12 -6.0\n", + "5 -5 NaN -10 -6.0\n", + "6 -4 NaN -8 -6.0\n", + "7 -3 NaN -6 -3.0\n", + "8 -2 NaN -4 -3.0\n", + "9 -1 NaN -2 -3.0\n", + "10 0 0.0 0 0.0\n", + "11 1 0.0 2 0.0\n", + "12 2 0.0 4 0.0\n", + "13 3 3.0 6 3.0\n", + "14 4 3.0 8 3.0\n", + "15 5 3.0 10 3.0\n", + "16 6 6.0 12 6.0\n", + "17 7 6.0 14 6.0\n", + "18 8 6.0 16 6.0\n", + "19 9 9.0 18 9.0" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_6 = pd.merge(df_1, df_2, on=\"ints\", how=\"right\")\n", + "df_6" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
intsthrees_xevensthrees_y
0-10NaN-20.0-12.0
1-9NaN-18.0-9.0
2-8NaN-16.0-9.0
3-7NaN-14.0-9.0
4-6NaN-12.0-6.0
...............
1059593.0NaNNaN
1069696.0NaNNaN
1079796.0NaNNaN
1089896.0NaNNaN
1099999.0NaNNaN
\n", + "

110 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " ints threes_x evens threes_y\n", + "0 -10 NaN -20.0 -12.0\n", + "1 -9 NaN -18.0 -9.0\n", + "2 -8 NaN -16.0 -9.0\n", + "3 -7 NaN -14.0 -9.0\n", + "4 -6 NaN -12.0 -6.0\n", + ".. ... ... ... ...\n", + "105 95 93.0 NaN NaN\n", + "106 96 96.0 NaN NaN\n", + "107 97 96.0 NaN NaN\n", + "108 98 96.0 NaN NaN\n", + "109 99 99.0 NaN NaN\n", + "\n", + "[110 rows x 4 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_7 = pd.merge(df_1, df_2, on=\"ints\", how=\"outer\")\n", + "df_7\n" + ] }, { "cell_type": "markdown", @@ -203,31 +999,607 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ints_xthrees_xints_yevensthrees_y
0NaNNaN-10.0-20.0-12.0
1NaNNaN-9.0-18.0-9.0
2NaNNaN-8.0-16.0-9.0
3NaNNaN-7.0-14.0-9.0
4NaNNaN-6.0-12.0-6.0
..................
10595.093.0NaNNaNNaN
10696.096.0NaNNaNNaN
10797.096.0NaNNaNNaN
10898.096.0NaNNaNNaN
10999.099.0NaNNaNNaN
\n", + "

110 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " ints_x threes_x ints_y evens threes_y\n", + "0 NaN NaN -10.0 -20.0 -12.0\n", + "1 NaN NaN -9.0 -18.0 -9.0\n", + "2 NaN NaN -8.0 -16.0 -9.0\n", + "3 NaN NaN -7.0 -14.0 -9.0\n", + "4 NaN NaN -6.0 -12.0 -6.0\n", + ".. ... ... ... ... ...\n", + "105 95.0 93.0 NaN NaN NaN\n", + "106 96.0 96.0 NaN NaN NaN\n", + "107 97.0 96.0 NaN NaN NaN\n", + "108 98.0 96.0 NaN NaN NaN\n", + "109 99.0 99.0 NaN NaN NaN\n", + "\n", + "[110 rows x 5 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_8 = pd.merge(df_1, df_2, left_on=\"ints\", right_on=\"evens\", how=\"outer\")\n", + "df_8" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ints_xthrees_xints_yevensthrees_y
0NaNNaN-10.0-20.0-12.0
1NaNNaN-9.0-18.0-9.0
2NaNNaN-8.0-16.0-9.0
3NaNNaN-7.0-14.0-9.0
4NaNNaN-6.0-12.0-6.0
..................
11195.093.0NaNNaNNaN
11296.096.0NaNNaNNaN
11397.096.0NaNNaNNaN
11498.096.0NaNNaNNaN
11599.099.0NaNNaNNaN
\n", + "

116 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " ints_x threes_x ints_y evens threes_y\n", + "0 NaN NaN -10.0 -20.0 -12.0\n", + "1 NaN NaN -9.0 -18.0 -9.0\n", + "2 NaN NaN -8.0 -16.0 -9.0\n", + "3 NaN NaN -7.0 -14.0 -9.0\n", + "4 NaN NaN -6.0 -12.0 -6.0\n", + ".. ... ... ... ... ...\n", + "111 95.0 93.0 NaN NaN NaN\n", + "112 96.0 96.0 NaN NaN NaN\n", + "113 97.0 96.0 NaN NaN NaN\n", + "114 98.0 96.0 NaN NaN NaN\n", + "115 99.0 99.0 NaN NaN NaN\n", + "\n", + "[116 rows x 5 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_9 = pd.merge(df_1, df_2, left_on=\"ints\", right_on=\"threes\", how=\"outer\")\n", + "df_9" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ints_xthrees_xints_yevensthrees_y
000.00.00.00.0
100.01.02.00.0
200.02.04.00.0
310.0NaNNaNNaN
420.0NaNNaNNaN
..................
1019593.0NaNNaNNaN
1029696.0NaNNaNNaN
1039796.0NaNNaNNaN
1049896.0NaNNaNNaN
1059999.0NaNNaNNaN
\n", + "

106 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " ints_x threes_x ints_y evens threes_y\n", + "0 0 0.0 0.0 0.0 0.0\n", + "1 0 0.0 1.0 2.0 0.0\n", + "2 0 0.0 2.0 4.0 0.0\n", + "3 1 0.0 NaN NaN NaN\n", + "4 2 0.0 NaN NaN NaN\n", + ".. ... ... ... ... ...\n", + "101 95 93.0 NaN NaN NaN\n", + "102 96 96.0 NaN NaN NaN\n", + "103 97 96.0 NaN NaN NaN\n", + "104 98 96.0 NaN NaN NaN\n", + "105 99 99.0 NaN NaN NaN\n", + "\n", + "[106 rows x 5 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_10 = pd.merge(df_1, df_2, left_on=\"ints\", right_on=\"threes\", how=\"left\")\n", + "df_10" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ints_xthreesints_yevens
0NaN-12.0-10.0-20.0
1NaN-9.0-9.0-18.0
2NaN-9.0-8.0-16.0
3NaN-9.0-7.0-14.0
4NaN-6.0-6.0-12.0
...............
12395.093.0NaNNaN
12496.096.0NaNNaN
12597.096.0NaNNaN
12698.096.0NaNNaN
12799.099.0NaNNaN
\n", + "

128 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " ints_x threes ints_y evens\n", + "0 NaN -12.0 -10.0 -20.0\n", + "1 NaN -9.0 -9.0 -18.0\n", + "2 NaN -9.0 -8.0 -16.0\n", + "3 NaN -9.0 -7.0 -14.0\n", + "4 NaN -6.0 -6.0 -12.0\n", + ".. ... ... ... ...\n", + "123 95.0 93.0 NaN NaN\n", + "124 96.0 96.0 NaN NaN\n", + "125 97.0 96.0 NaN NaN\n", + "126 98.0 96.0 NaN NaN\n", + "127 99.0 99.0 NaN NaN\n", + "\n", + "[128 rows x 4 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_11 = pd.merge(df_1, df_2, left_on=\"threes\", right_on=\"threes\", how=\"outer\")\n", + "df_11" + ] }, { "cell_type": "markdown", @@ -240,10 +1612,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "\"\"\" \n", + "You cannot merge these two dataframes on df_1.threes and df_2.threes_string as they are \n", + "incompatible data types. \n", + "\"\"\";\n", + "\n", + "df_2[\"threes_string\"] = df_2[\"threes\"].astype(str)\n", + "# df_12 = pd.merge(df_1,df_2, left_on=\"threes\", right_on=\"threes_string\", how=\"inner\")\n", + "# df_12\n", + "\n" + ] }, { "cell_type": "markdown", @@ -260,10 +1642,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ints threes evens threes_string\n", + "0 0 0.0 NaN NaN\n", + "1 1 0.0 NaN NaN\n", + "2 2 0.0 NaN NaN\n", + "3 3 3.0 NaN NaN\n", + "4 4 3.0 NaN NaN\n", + ".. ... ... ... ...\n", + "5 5 3.0 10.0 3.0\n", + "6 6 6.0 12.0 6.0\n", + "7 7 6.0 14.0 6.0\n", + "8 8 6.0 16.0 6.0\n", + "9 9 9.0 18.0 9.0\n", + "\n", + "[120 rows x 4 columns]\n", + "------------------------------------------------\n" + ] + } + ], + "source": [ + "df_concat = pd.concat([df_1, df_2], ignore_index=False)\n", + "print(df_concat)\n", + "print(\"------------------------------------------------\")" + ] }, { "cell_type": "markdown", @@ -284,10 +1692,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The matrix ranks are equal\n" + ] + } + ], + "source": [ + "matrix_1 = np.arange(12).reshape((3,4))\n", + "matrix_1_rank = np.linalg.matrix_rank(matrix_1)\n", + "\n", + "matrix_3 = np.arange(8).reshape(4,matrix_1_rank)\n", + "matrix_4 = np.arange(8).reshape(matrix_1_rank,4)\n", + "\n", + "matrix_5 = matrix_3 @ matrix_4\n", + "matrix_5_rank = np.linalg.matrix_rank(matrix_5)\n", + "\n", + "try:\n", + " if matrix_1_rank == matrix_5_rank:\n", + " print(\"The matrix ranks are equal\")\n", + "except: \n", + " print(\"The matrix ranks are NOT equal.\")" + ] }, { "cell_type": "markdown", @@ -299,10 +1730,45 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Each matrix has the same rank as its transpose. Marix multipliation of A @ A.T and A.T @ A all have the same rank as the orignial matrix.\n" + ] + } + ], + "source": [ + "matrix_6 = np.random.randint(1,20,(7,2))\n", + "matrix_7 = np.random.randint(1,20,(3,7))\n", + "matrix_8 = np.random.randint(1,20,(3,4))\n", + "matrix_9 = np.random.randint(1,20,(4,5))\n", + "matrix_10 = np.random.randint(1,20,(5,3))\n", + "matrix_11 = np.random.randint(1,20,(3,6))\n", + "\n", + "def same_rank(arr: np.array) -> bool:\n", + " assert np.linalg.matrix_rank(arr) == np.linalg.matrix_rank(arr.T)\n", + " assert np.linalg.matrix_rank(arr) == np.linalg.matrix_rank(arr.T @ arr)\n", + " assert np.linalg.matrix_rank(arr) == np.linalg.matrix_rank((arr @ arr.T))\n", + " return True\n", + "\n", + "def all_ranks_are_equal() -> None:\n", + " assert same_rank(matrix_6) == True\n", + " assert same_rank(matrix_7) == True\n", + " assert same_rank(matrix_8) == True\n", + " assert same_rank(matrix_9) == True\n", + " assert same_rank(matrix_10) == True\n", + " assert same_rank(matrix_11) == True\n", + " print(\"Each matrix has the same rank as its transpose. Marix multipliation of A @ A.T and A.T @ A \" \\\n", + " \"all have the same rank as the orignial matrix.\")\n", + "\n", + "all_ranks_are_equal()\n", + "\n", + "\n" + ] }, { "cell_type": "markdown", @@ -318,12 +1784,119 @@ "Then repeat this exercise using matrix multiplication instead of addition." ] }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rank_zero_1 = np.array([ [1,2,3], \n", + " [2,4,6] ])\n", + "rank_zero_2 = rank_zero_1 * -1\n", + "\n", + "rank_one_1 = np.array([ [3,4,5], \n", + " [6,8,10] ])\n", + "rank_one_2 = rank_one_1 * 3\n", + "\n", + "rank_two_1 = np.array([ [7,8,9], \n", + " [14,16,18] ])\n", + "rank_two_2 = np.array( [ [1,4,5],\n", + " [3,12,15]])\n", + "\n", + "\n", + "\n", + "def rank(arr: np.array) -> int:\n", + " return np.linalg.matrix_rank(arr)\n", + "\n", + "def matrix_addition(arr1: np.array, arr2: np.array) -> np.array:\n", + " return arr1 + arr2\n", + "\n", + "def marix_addition_rank_rule(arr1: np.array, arr2: np.array) -> bool:\n", + " assert (rank(arr1 + arr2)) <= (rank(arr1) + rank(arr2))\n", + " return True\n", + "\n", + "display(marix_addition_rank_rule(rank_zero_1, rank_zero_2))\n", + "display(marix_addition_rank_rule(rank_one_1, rank_one_2))\n", + "display(marix_addition_rank_rule(rank_two_1, rank_two_2))\n", + "\n", + "\n" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# I created a separate box for the matrix multiplication part of problem # 8\n", + "\n", + "def matrix_multiplication(arr1: np.array, arr2: np.array) -> np.array:\n", + " return arr1 @ arr2\n", + "\n", + "def marix_multiplication_rank_rule(arr1: np.array, arr2: np.array) -> bool:\n", + " assert (rank(arr1 @ arr2.T)) <= min(rank(arr1), rank(arr2))\n", + " return True\n", + "\n", + "display(marix_multiplication_rank_rule(rank_one_1, rank_one_2))\n", + "display(marix_multiplication_rank_rule(rank_zero_1, rank_zero_2))\n", + "display(marix_multiplication_rank_rule(rank_two_1, rank_two_2))\n" + ] }, { "cell_type": "markdown", @@ -347,12 +1920,96 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "A = np.random.randint(1,20,(4,3))\n", + "v = np.random.randint(1,20,(4,1))\n", + "A_v = np.hstack([A,v])\n", + "\n", + "# check if a vector (v) is in the column space of a matrix (A)\n", + "def in_column_space(A: np.array, v: np.array) -> bool:\n", + " A_rank = rank(A)\n", + " Av = np.hstack([A,v])\n", + " Av_rank = rank(Av)\n", + " if A_rank == Av_rank:\n", + " return True \n", + " elif A_rank < Av_rank:\n", + " return False \n", + "\n", + "\n", + "def cp_test1(arr: np.array, vector: np.array) -> None:\n", + " for i in range(1000000):\n", + " cp = in_column_space(arr, vector)\n", + " assert cp == False\n", + "\n", + "# display(cp_test1(A,v))\n", + "\n", + "\"\"\" \n", + "I ran the above test (1 million loops, takes around 16 seconds) and not once did the assertion fail. \n", + "Thus regardless of the random distribution of A and v, v is NEVER in the column space of A for this test. \n", + "In order for this to fail, all 3 columns of A would need to lie in a 2D or 1D subspace.\n", + "\n", + "A has a rank of 3 as it contains 4 rows and 3 columns, thus resulting in a rank of 3. While \n", + "the augmented matrix, A_v has a rank of 4 since as it contains 4 rows and 4 columns, resulting \n", + "in a rank of 4. \n", + "\n", + "Initiallly I did not have the cp_test1 function above and was running the for loop by return \n", + "True/False in an if/elif conditional. After running it many times I noticed that it always \n", + "failed. So, I created the above test so I could run it many times and would only generate an \n", + "output if it failed. I did the same thing below but change the assert to checking for a return \n", + "value of True.\n", + "\"\"\";\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 319, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "My final conclusion is that in a random distribution if a matrix M (of shape j x n) has linearly \n", + "independent columns and vector v (of shape j x 1) is not a linear combination of any of the column vectors within M then \n", + "v is not in the column space of M. If j == n and M has linearly independent columns then v will be within the column \n", + "space of M.\n" + ] + } + ], + "source": [ + "B = np.random.randint(1,20,(4,4))\n", + "v2 = np.random.randint(1,20,(4,1))\n", + "B_v2 = np.hstack([B, v2])\n", + "\n", + "def cp_test2(arr: np.array, vector: np.array) -> None:\n", + " for i in range(1000000):\n", + " cp = in_column_space(arr, vector)\n", + " assert cp == True\n", + "\n", + "# uncomment the line below if you would like to run the test, it will take around 16 seconds\n", + "# display(cp_test2(B,v2))\n", + "\n", + "\"\"\" \n", + "I ran the above test (1 million loops, takes around 16 seconds) and not once did the \n", + "assertion fail. Regardless of the random distribution of B and v2, v2 is ALWAYS \n", + "in the column space of B during this test. There is the very minimal possiblity of \n", + "linear dependence within the resulting matrix. If that were to occur, it would result \n", + "in failure of the test. \n", + "\"\"\";\n", + "\n", + "print(\"My final conclusion is that in a random distribution if a matrix M (of shape j x n) has linearly \\n\" \\\n", + "\"independent columns and vector v (of shape j x 1) is not a linear combination of any of the column vectors within M then \\n\" \\\n", + "\"v is not in the column space of M. If j == n and M has linearly independent columns then v will be within the column \\n\" \\\n", + "\"space of M.\")\n", + "\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -366,7 +2023,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/week_9_viz_determ.ipynb b/week_9_viz_determ.ipynb index 3c638e0..dc85150 100644 --- a/week_9_viz_determ.ipynb +++ b/week_9_viz_determ.ipynb @@ -210,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -254,10 +254,862 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "'Disability and health insurance'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
OBJECTIDNEIGH_NONeighborhood_NameNeighborhood_TypeNeighborhood_SubtypeACS_VinatagePopulation_18_years_and_OverPopulation_18_to_64_yearsPopulation_18_to_64_years_Below_Poverty_with_a_DisabilityPopulation_18_to_64_years_Below_Poverty_without_a_Disability...Population_65_years_and_Over_with_Health_InsurancePopulation_65_years_and_Over_without_Health_InsurancePopulation_without_Health_InsurancePopulation_under_19_yearsPopulation_19_to_34_yearsPopulation_35_to_64_yearsPopulation_65_years_and_Over.1HouseholdsHouseholds_with_1_or_more_persons_with_a_disabilityNeighborhood_Type_(outside_comp_plan_areas_id)
011.4Alki/AdmiralCRASouthwest5Y23101317910105323...2221044718622231560622215595865CRA
122.1North DelridgeCRADelridge Neighborhoods5Y235213462928408...5840520558178428175843079452CRA
232.2High PointCRADelridge Neighborhoods5Y2368286084128584...74402792407259534487443709756CRA
342.3RiverviewCRADelridge Neighborhoods5Y233940349729147...4376781115108823684431878329CRA
452.4Roxhill/WestwoodCRADelridge Neighborhoods5Y231160210014397454...1540481043255936056212158858251171CRA
\n", + "

5 rows × 37 columns

\n", + "
" + ], + "text/plain": [ + " OBJECTID NEIGH_NO Neighborhood_Name Neighborhood_Type \\\n", + "0 1 1.4 Alki/Admiral CRA \n", + "1 2 2.1 North Delridge CRA \n", + "2 3 2.2 High Point CRA \n", + "3 4 2.3 Riverview CRA \n", + "4 5 2.4 Roxhill/Westwood CRA \n", + "\n", + " Neighborhood_Subtype ACS_Vinatage Population_18_years_and_Over \\\n", + "0 Southwest 5Y23 10131 \n", + "1 Delridge Neighborhoods 5Y23 5213 \n", + "2 Delridge Neighborhoods 5Y23 6828 \n", + "3 Delridge Neighborhoods 5Y23 3940 \n", + "4 Delridge Neighborhoods 5Y23 11602 \n", + "\n", + " Population_18_to_64_years \\\n", + "0 7910 \n", + "1 4629 \n", + "2 6084 \n", + "3 3497 \n", + "4 10014 \n", + "\n", + " Population_18_to_64_years_Below_Poverty_with_a_Disability \\\n", + "0 105 \n", + "1 28 \n", + "2 128 \n", + "3 29 \n", + "4 397 \n", + "\n", + " Population_18_to_64_years_Below_Poverty_without_a_Disability ... \\\n", + "0 323 ... \n", + "1 408 ... \n", + "2 584 ... \n", + "3 147 ... \n", + "4 454 ... \n", + "\n", + " Population_65_years_and_Over_with_Health_Insurance \\\n", + "0 2221 \n", + "1 584 \n", + "2 744 \n", + "3 437 \n", + "4 1540 \n", + "\n", + " Population_65_years_and_Over_without_Health_Insurance \\\n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 6 \n", + "4 48 \n", + "\n", + " Population_without_Health_Insurance Population_under_19_years \\\n", + "0 447 1862 \n", + "1 520 558 \n", + "2 279 2407 \n", + "3 78 1115 \n", + "4 1043 2559 \n", + "\n", + " Population_19_to_34_years Population_35_to_64_years \\\n", + "0 2231 5606 \n", + "1 1784 2817 \n", + "2 2595 3448 \n", + "3 1088 2368 \n", + "4 3605 6212 \n", + "\n", + " Population_65_years_and_Over.1 Households \\\n", + "0 2221 5595 \n", + "1 584 3079 \n", + "2 744 3709 \n", + "3 443 1878 \n", + "4 1588 5825 \n", + "\n", + " Households_with_1_or_more_persons_with_a_disability \\\n", + "0 865 \n", + "1 452 \n", + "2 756 \n", + "3 329 \n", + "4 1171 \n", + "\n", + " Neighborhood_Type_(outside_comp_plan_areas_id) \n", + "0 CRA \n", + "1 CRA \n", + "2 CRA \n", + "3 CRA \n", + "4 CRA \n", + "\n", + "[5 rows x 37 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'Poverty and employment status'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
OBJECTIDNEIGH_NONeighborhood_NameNeighborhood_TypeNeighborhood_SubtypeACS_VinatageAggregate_income_in_the_past_12_months_(in_2022_inflation-adjusted_dollars)Total_PopulationTotal_HouseholdsHousehold_Income_Less_than_$10,000...Family_Household_Income_$100,000_or_moreNonfamily_Household_Income_$100,000_or_moreEarnings_$50,000_or_More_Male_WorkersEarnings_$50,000_or_More_Female_WorkersPopulation_16_years_and_over_with_earningsMales_16_years_and_over_with_earningsFemales_16_years_and_over_with_earningsEarnings_$50,000_or_More_All_WorkersAggregate_Household_IncomeNeighborhood_Type_(outside_comp_plan_areas_id)
011.0Council District 1CDNaN5Y23796508400010859448209NaN...1830694602536819332690223659932423447007797458400CD
122.0Council District 2CDNaN5Y23635539480010805343824NaN...1426364862096114994662983563630662359556177651600CD
233.0Council District 3CDNaN5Y231076393720010801260156NaN...141021883130371224527905743795352625282310593211500CD
344.0Council District 4CDNaN5Y23769229850010429942569NaN...1543879022181715841705023577834724376587471995100CD
455.0Council District 5CDNaN5Y23732486510010620847887NaN...1611082662373918286680253681531210420257154789000CD
\n", + "

5 rows × 69 columns

\n", + "
" + ], + "text/plain": [ + " OBJECTID NEIGH_NO Neighborhood_Name Neighborhood_Type \\\n", + "0 1 1.0 Council District 1 CD \n", + "1 2 2.0 Council District 2 CD \n", + "2 3 3.0 Council District 3 CD \n", + "3 4 4.0 Council District 4 CD \n", + "4 5 5.0 Council District 5 CD \n", + "\n", + " Neighborhood_Subtype ACS_Vinatage \\\n", + "0 NaN 5Y23 \n", + "1 NaN 5Y23 \n", + "2 NaN 5Y23 \n", + "3 NaN 5Y23 \n", + "4 NaN 5Y23 \n", + "\n", + " Aggregate_income_in_the_past_12_months_(in_2022_inflation-adjusted_dollars) \\\n", + "0 7965084000 \n", + "1 6355394800 \n", + "2 10763937200 \n", + "3 7692298500 \n", + "4 7324865100 \n", + "\n", + " Total_Population Total_Households Household_Income_Less_than_$10,000 \\\n", + "0 108594 48209 NaN \n", + "1 108053 43824 NaN \n", + "2 108012 60156 NaN \n", + "3 104299 42569 NaN \n", + "4 106208 47887 NaN \n", + "\n", + " ... Family_Household_Income_$100,000_or_more \\\n", + "0 ... 18306 \n", + "1 ... 14263 \n", + "2 ... 14102 \n", + "3 ... 15438 \n", + "4 ... 16110 \n", + "\n", + " Nonfamily_Household_Income_$100,000_or_more \\\n", + "0 9460 \n", + "1 6486 \n", + "2 18831 \n", + "3 7902 \n", + "4 8266 \n", + "\n", + " Earnings_$50,000_or_More_Male_Workers \\\n", + "0 25368 \n", + "1 20961 \n", + "2 30371 \n", + "3 21817 \n", + "4 23739 \n", + "\n", + " Earnings_$50,000_or_More_Female_Workers \\\n", + "0 19332 \n", + "1 14994 \n", + "2 22452 \n", + "3 15841 \n", + "4 18286 \n", + "\n", + " Population_16_years_and_over_with_earnings \\\n", + "0 69022 \n", + "1 66298 \n", + "2 79057 \n", + "3 70502 \n", + "4 68025 \n", + "\n", + " Males_16_years_and_over_with_earnings \\\n", + "0 36599 \n", + "1 35636 \n", + "2 43795 \n", + "3 35778 \n", + "4 36815 \n", + "\n", + " Females_16_years_and_over_with_earnings \\\n", + "0 32423 \n", + "1 30662 \n", + "2 35262 \n", + "3 34724 \n", + "4 31210 \n", + "\n", + " Earnings_$50,000_or_More_All_Workers Aggregate_Household_Income \\\n", + "0 44700 7797458400 \n", + "1 35955 6177651600 \n", + "2 52823 10593211500 \n", + "3 37658 7471995100 \n", + "4 42025 7154789000 \n", + "\n", + " Neighborhood_Type_(outside_comp_plan_areas_id) \n", + "0 CD \n", + "1 CD \n", + "2 CD \n", + "3 CD \n", + "4 CD \n", + "\n", + "[5 rows x 69 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'Occupations and earnings'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
OBJECTIDNEIGH_NONeighborhood_NameNeighborhood_TypeNeighborhood_SubtypeACS_VinatagePopulation_16_years_and_overPopulation_16_years_and_over_not_in_labor_forcePopulation_16_years_and_over_in_civilian_labor_forcePopulation_16_years_and_over_in_civilian_labor_force_unemployed...Population_20_to_64_years_employedPopulation_20_to_64_years_below_poverty_employedPeople_with_Income_to_Poverty_below_2.00Population_20_to_64_years_in_civilian_labor_forcePopulation_20_to_64_years_in_civilian_labor_force_below_povertyPopulation_20_to_64_years_not_in_labor_forcePopulation_20_to_64_years_not_in_labor_force_below_povertyPopulation_20_to_64_years_unemployedPopulation_20_to_64_years_unemployed_below_povertyNeighborhood_Type_(outside_comp_plan_areas_id)
018.2Olympic Hills/Victory HeightsCRANorth5Y2314516375110745574...96373922951101655941448293528202CRA
128.3Cedar Park/MeadowbrookCRANorth5Y231251336778836259...777425028077985321140452221171CRA
239.1Broadview/Bitter LakeCRANorthwest5Y231326047538507356...745428532617776371151949032286CRA
349.2Licton SpringsCRANorthwest5Y23879818956903267...6339201208166013011008411262100CRA
459.3Greenwood/Phinney RidgeCRANorthwest5Y2323396498518381565...166293242613171054562188430476132CRA
\n", + "

5 rows × 36 columns

\n", + "
" + ], + "text/plain": [ + " OBJECTID NEIGH_NO Neighborhood_Name Neighborhood_Type \\\n", + "0 1 8.2 Olympic Hills/Victory Heights CRA \n", + "1 2 8.3 Cedar Park/Meadowbrook CRA \n", + "2 3 9.1 Broadview/Bitter Lake CRA \n", + "3 4 9.2 Licton Springs CRA \n", + "4 5 9.3 Greenwood/Phinney Ridge CRA \n", + "\n", + " Neighborhood_Subtype ACS_Vinatage Population_16_years_and_over \\\n", + "0 North 5Y23 14516 \n", + "1 North 5Y23 12513 \n", + "2 Northwest 5Y23 13260 \n", + "3 Northwest 5Y23 8798 \n", + "4 Northwest 5Y23 23396 \n", + "\n", + " Population_16_years_and_over_not_in_labor_force \\\n", + "0 3751 \n", + "1 3677 \n", + "2 4753 \n", + "3 1895 \n", + "4 4985 \n", + "\n", + " Population_16_years_and_over_in_civilian_labor_force \\\n", + "0 10745 \n", + "1 8836 \n", + "2 8507 \n", + "3 6903 \n", + "4 18381 \n", + "\n", + " Population_16_years_and_over_in_civilian_labor_force_unemployed ... \\\n", + "0 574 ... \n", + "1 259 ... \n", + "2 356 ... \n", + "3 267 ... \n", + "4 565 ... \n", + "\n", + " Population_20_to_64_years_employed \\\n", + "0 9637 \n", + "1 7774 \n", + "2 7454 \n", + "3 6339 \n", + "4 16629 \n", + "\n", + " Population_20_to_64_years_below_poverty_employed \\\n", + "0 392 \n", + "1 250 \n", + "2 285 \n", + "3 201 \n", + "4 324 \n", + "\n", + " People_with_Income_to_Poverty_below_2.00 \\\n", + "0 2951 \n", + "1 2807 \n", + "2 3261 \n", + "3 2081 \n", + "4 2613 \n", + "\n", + " Population_20_to_64_years_in_civilian_labor_force \\\n", + "0 10165 \n", + "1 7985 \n", + "2 7776 \n", + "3 6601 \n", + "4 17105 \n", + "\n", + " Population_20_to_64_years_in_civilian_labor_force_below_poverty \\\n", + "0 594 \n", + "1 321 \n", + "2 371 \n", + "3 301 \n", + "4 456 \n", + "\n", + " Population_20_to_64_years_not_in_labor_force \\\n", + "0 1448 \n", + "1 1404 \n", + "2 1519 \n", + "3 1008 \n", + "4 2188 \n", + "\n", + " Population_20_to_64_years_not_in_labor_force_below_poverty \\\n", + "0 293 \n", + "1 522 \n", + "2 490 \n", + "3 411 \n", + "4 430 \n", + "\n", + " Population_20_to_64_years_unemployed \\\n", + "0 528 \n", + "1 211 \n", + "2 322 \n", + "3 262 \n", + "4 476 \n", + "\n", + " Population_20_to_64_years_unemployed_below_poverty \\\n", + "0 202 \n", + "1 71 \n", + "2 86 \n", + "3 100 \n", + "4 132 \n", + "\n", + " Neighborhood_Type_(outside_comp_plan_areas_id) \n", + "0 CRA \n", + "1 CRA \n", + "2 CRA \n", + "3 CRA \n", + "4 CRA \n", + "\n", + "[5 rows x 36 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(\"Disability and health insurance\")\n", + "display(dis_health_df.head())\n", + "display(\"Poverty and employment status\")\n", + "display(income_df.head())\n", + "display(\"Occupations and earnings\")\n", + "display(poverty_df.head())\n", + "\n", + "\"\"\"\n", + "How does poverty correlate with employment? \n", + "\n", + "How does income correlate with disability? \n", + "\"\"\";\n" + ] }, { "cell_type": "markdown", @@ -281,10 +1133,481 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
OBJECTIDNEIGH_NONeighborhood_NameNeighborhood_TypeNeighborhood_SubtypeACS_VinatagePopulation_18+Population_18-64Population_18_to_64_years_Below_Poverty_with_a_DisabilityPopulation_18_to_64_years_Below_Poverty_without_a_Disability...Population_65_years_and_Over_with_Health_InsurancePopulation_65_years_and_Over_without_Health_InsurancePopulation_without_Health_InsurancePopulation_under_19_yearsPopulation_19_to_34_yearsPopulation_35_to_64_yearsPopulation_65_years_and_Over.1HouseholdsHouseholds_with_1_or_more_persons_with_a_disabilityNeighborhood_Type_(outside_comp_plan_areas_id)
011.4Alki/AdmiralCRASouthwest5Y23101317910105323...2221044718622231560622215595865CRA
122.1North DelridgeCRADelridge Neighborhoods5Y235213462928408...5840520558178428175843079452CRA
232.2High PointCRADelridge Neighborhoods5Y2368286084128584...74402792407259534487443709756CRA
342.3RiverviewCRADelridge Neighborhoods5Y233940349729147...4376781115108823684431878329CRA
452.4Roxhill/WestwoodCRADelridge Neighborhoods5Y231160210014397454...1540481043255936056212158858251171CRA
..................................................................
8081414.0First Hill/Capitol HillUCUVUrban Center5Y2346082419358353822...4129182360180128222146414147329315854UCUV
8182502.0Greater DuwamishUCUVManufacturing Industrial5Y23469394130...75083331672227532253UCUV
89901.1Arbor HeightsCRASouthwest5Y234736363840130...10980991446695290410982693536CRA
90911.2Fauntleroy/SeaviewCRASouthwest5Y23123329907134504...2425030228342435738424256879869CRA
91921.3West Seattle Junction/Genesee HillCRASouthwest5Y231958216724177814...2858041140665360112372858112401836CRA
\n", + "

85 rows × 37 columns

\n", + "
" + ], + "text/plain": [ + " OBJECTID NEIGH_NO Neighborhood_Name Neighborhood_Type \\\n", + "0 1 1.4 Alki/Admiral CRA \n", + "1 2 2.1 North Delridge CRA \n", + "2 3 2.2 High Point CRA \n", + "3 4 2.3 Riverview CRA \n", + "4 5 2.4 Roxhill/Westwood CRA \n", + ".. ... ... ... ... \n", + "80 81 414.0 First Hill/Capitol Hill UCUV \n", + "81 82 502.0 Greater Duwamish UCUV \n", + "89 90 1.1 Arbor Heights CRA \n", + "90 91 1.2 Fauntleroy/Seaview CRA \n", + "91 92 1.3 West Seattle Junction/Genesee Hill CRA \n", + "\n", + " Neighborhood_Subtype ACS_Vinatage Population_18+ Population_18-64 \\\n", + "0 Southwest 5Y23 10131 7910 \n", + "1 Delridge Neighborhoods 5Y23 5213 4629 \n", + "2 Delridge Neighborhoods 5Y23 6828 6084 \n", + "3 Delridge Neighborhoods 5Y23 3940 3497 \n", + "4 Delridge Neighborhoods 5Y23 11602 10014 \n", + ".. ... ... ... ... \n", + "80 Urban Center 5Y23 46082 41935 \n", + "81 Manufacturing Industrial 5Y23 469 394 \n", + "89 Southwest 5Y23 4736 3638 \n", + "90 Southwest 5Y23 12332 9907 \n", + "91 Southwest 5Y23 19582 16724 \n", + "\n", + " Population_18_to_64_years_Below_Poverty_with_a_Disability \\\n", + "0 105 \n", + "1 28 \n", + "2 128 \n", + "3 29 \n", + "4 397 \n", + ".. ... \n", + "80 835 \n", + "81 13 \n", + "89 40 \n", + "90 134 \n", + "91 177 \n", + "\n", + " Population_18_to_64_years_Below_Poverty_without_a_Disability ... \\\n", + "0 323 ... \n", + "1 408 ... \n", + "2 584 ... \n", + "3 147 ... \n", + "4 454 ... \n", + ".. ... ... \n", + "80 3822 ... \n", + "81 0 ... \n", + "89 130 ... \n", + "90 504 ... \n", + "91 814 ... \n", + "\n", + " Population_65_years_and_Over_with_Health_Insurance \\\n", + "0 2221 \n", + "1 584 \n", + "2 744 \n", + "3 437 \n", + "4 1540 \n", + ".. ... \n", + "80 4129 \n", + "81 75 \n", + "89 1098 \n", + "90 2425 \n", + "91 2858 \n", + "\n", + " Population_65_years_and_Over_without_Health_Insurance \\\n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 6 \n", + "4 48 \n", + ".. ... \n", + "80 18 \n", + "81 0 \n", + "89 0 \n", + "90 0 \n", + "91 0 \n", + "\n", + " Population_without_Health_Insurance Population_under_19_years \\\n", + "0 447 1862 \n", + "1 520 558 \n", + "2 279 2407 \n", + "3 78 1115 \n", + "4 1043 2559 \n", + ".. ... ... \n", + "80 2360 1801 \n", + "81 83 33 \n", + "89 99 1446 \n", + "90 302 2834 \n", + "91 411 4066 \n", + "\n", + " Population_19_to_34_years Population_35_to_64_years \\\n", + "0 2231 5606 \n", + "1 1784 2817 \n", + "2 2595 3448 \n", + "3 1088 2368 \n", + "4 3605 6212 \n", + ".. ... ... \n", + "80 28222 14641 \n", + "81 167 222 \n", + "89 695 2904 \n", + "90 2435 7384 \n", + "91 5360 11237 \n", + "\n", + " Population_65_years_and_Over.1 Households \\\n", + "0 2221 5595 \n", + "1 584 3079 \n", + "2 744 3709 \n", + "3 443 1878 \n", + "4 1588 5825 \n", + ".. ... ... \n", + "80 4147 32931 \n", + "81 75 322 \n", + "89 1098 2693 \n", + "90 2425 6879 \n", + "91 2858 11240 \n", + "\n", + " Households_with_1_or_more_persons_with_a_disability \\\n", + "0 865 \n", + "1 452 \n", + "2 756 \n", + "3 329 \n", + "4 1171 \n", + ".. ... \n", + "80 5854 \n", + "81 53 \n", + "89 536 \n", + "90 869 \n", + "91 1836 \n", + "\n", + " Neighborhood_Type_(outside_comp_plan_areas_id) \n", + "0 CRA \n", + "1 CRA \n", + "2 CRA \n", + "3 CRA \n", + "4 CRA \n", + ".. ... \n", + "80 UCUV \n", + "81 UCUV \n", + "89 CRA \n", + "90 CRA \n", + "91 CRA \n", + "\n", + "[85 rows x 37 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dis_health_df.dropna()\n", + "# income_df.dropna() if you do this it deletes all of the rows\n", + "dis_health_df = dis_health_df.rename(columns = {\"Population_18_years_and_Over\": \"Population_18+\", \"Population_18_to_64_years\": \"Population_18-64\"})\n", + "dis_health_df.dropna()" + ] }, { "cell_type": "markdown", @@ -492,7 +1815,7 @@ ], "metadata": { "kernelspec": { - "display_name": "AD_450_env", + "display_name": "ml-env", "language": "python", "name": "python3" }, @@ -506,7 +1829,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.16" + "version": "3.10.18" } }, "nbformat": 4,