Zekunov Vladislav АТ-18

homework.py

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+import sqlite3
+import pandas as pd
+import re
+
+
+def get_out_tags(field):
+    return re.sub(r'\<[^>]*\>', '', str(field))
+
+
+con = sqlite3.connect('works.sqlite')
+cursor = con.cursor()
+cursor.execute('drop table if exists works')
+cursor.execute(
+    'create table if not exists works (ID INTEGER PRIMARY KEY AUTOINCREMENT,salary INTEGER,educationType TEXT,'
+    'jobTitle TEXT,qualification TEXT,gender TEXT,dateModify TEXT,skills TEXT,otherInfo TEXT)')
+con.commit()
+
+# Скиллы и otherInfo
+df = pd.read_csv('works.csv')
+df['skills'] = df['skills'].apply(get_out_tags)
+df['otherInfo'] = df['otherInfo'].apply(get_out_tags)
+df.to_sql('works', con, if_exists='append', index=False)
+con.commit()
+
+# ДЗ Пробуем нормализовать базу данных и немного почистить поля.
+cursor.execute('drop table if exists genders')
+cursor.execute('create table genders(id INTEGER PRIMARY KEY AUTOINCREMENT, gender_val TEXT)')
+con.commit()
+
+cursor.execute('INSERT INTO genders(gender_val) SELECT DISTINCT gender FROM works WHERE gender IS NOT NULL')
+con.commit()
+
+cursor.execute('ALTER TABLE works ADD COLUMN gender_id INTEGER REFERENCES genders(id)')
+con.commit()
+
+cursor.execute('UPDATE works SET gender_id = (SELECT id FROM genders WHERE gender_val = works.gender)')
+con.commit()
+
+cursor.execute('ALTER TABLE works DROP COLUMN gender')
+con.commit()
+
+# Проверка вывода
+# cursor.execute('SELECT * FROM genders')
+# print(cursor.fetchall())
+# cursor.execute('SELECT gender_val FROM genders,works WHERE genders.id = works.gender_id')
+# print(cursor.fetchall())
+
+
+cursor.execute('drop table if exists education')
+cursor.execute('create table education(id INTEGER PRIMARY KEY AUTOINCREMENT, edu_val TEXT)')
+con.commit()
+
+cursor.execute('INSERT INTO education(edu_val) SELECT DISTINCT educationType FROM works WHERE educationType IS NOT NULL')
+con.commit()
+
+cursor.execute('ALTER TABLE works ADD COLUMN educationType_id INTEGER REFERENCES education(id)')
+con.commit()
+
+cursor.execute('UPDATE works SET educationType_id = (SELECT id FROM education WHERE edu_val = works.educationType)')
+con.commit()
+
+cursor.execute('ALTER TABLE works DROP COLUMN educationType')
+con.commit()
+
+# Проверка вывода
+# cursor.execute('SELECT * FROM education')
+# print(cursor.fetchall())
+# cursor.execute('SELECT edu_val FROM education,works WHERE education.id = works.educationType_id')
+# print(cursor.fetchall())
+

tasks_on_lesson.py

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+import sqlite3
+import numpy as np
+import pandas as pd
+from matplotlib import pyplot as plt
+
+con = sqlite3.connect('works.sqlite')
+cursor = con.cursor()
+cursor.execute('drop table if exists works')
+# 1
+cursor.execute(
+    'create table if not exists works (ID INTEGER PRIMARY KEY AUTOINCREMENT,salary INTEGER,educationType TEXT,'
+    'jobTitle TEXT,qualification TEXT,gender TEXT,dateModify TEXT,skills TEXT,otherInfo TEXT)')
+con.commit()
+
+df = pd.read_csv('works.csv')
+df.to_sql('works', con, if_exists='append', index=False)
+con.commit()
+
+# 2 6.3 kb
+cursor.execute('create index salary_index on works (salary)')
+con.commit()
+# 6.6 kb
+
+# 3
+cursor.execute('SELECT COUNT(*) FROM works')
+# print(cursor.fetchall()[0][0])
+
+# 4
+cursor.execute("SELECT COUNT(*) FROM works WHERE gender = 'Мужской'")
+# print(cursor.fetchall()[0][0])
+
+cursor.execute("SELECT COUNT(*) FROM works WHERE gender = 'Женский'")
+# print(cursor.fetchall()[0][0])
+
+# 5
+cursor.execute("SELECT COUNT(*) FROM works WHERE skills NOT NULL")
+# print(cursor.fetchall()[0][0])
+
+# 6
+cursor.execute("SELECT skills FROM works WHERE skills NOT NULL")
+# print(cursor.fetchall())
+
+# 7
+cursor.execute("SELECT salary FROM works WHERE skills LIKE '%Python%'")
+# print(cursor.fetchall())
+
+# 8
+cursor.execute("SELECT salary FROM works WHERE gender = 'Мужской'")
+m_salary = [t[0] for t in cursor.fetchall()]
+# print(m_salary)
+
+cursor.execute("SELECT salary FROM works WHERE gender = 'Женский'")
+w_salary = [t[0] for t in cursor.fetchall()]
+# print(w_salary)
+
+# 9
+m_salary = np.quantile(m_salary, np.linspace(0.1, 1, 10))
+w_salary = np.quantile(w_salary, np.linspace(0.1, 1, 10))
+
+plt.hist(m_salary, bins=100, color='blue')
+plt.show()
+plt.hist(w_salary, bins=100, color='red')
+plt.show()