Любов Никита АТ-06

lesson.py

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+import sqlite3 as sql
+import pandas as pd
+
+# Задача 1
+con = sql.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)')
+# print(cursor.execute("pragma table_info(works)").fetchall())
+
+df = pd.read_csv('works.csv')
+df.to_sql('works', con, if_exists="append", index=False)
+#print(cursor.execute("select * from works limit 5").fetchall())  +++++++++++++++++++++++++
+
+# Задача 2
+# Сейчас размер файла составляет 6.3MB
+cursor.execute('create index salary_index on works (salary)')
+# Размер файла увеличился до 6.6MB
+
+# Задача 3
+# 32683
+print(cursor.execute("select count(*) from works").fetchone()[0])
+
+# Задача 4
+# Количество мужчин
+# 13386
+print(cursor.execute("select count(*) from works where gender = 'Мужской'").fetchall()[0][0])
+# Количество женщин
+# 17910
+print(cursor.execute("select count(*) from works where gender = 'Женский'").fetchall()[0][0])
+
+# Задача 5
+# У скольки записей заполнены скиллы
+# 8972
+print(cursor.execute('select count(*) from works where skills not null').fetchall()[0][0])
+
+# Задача 6
+# Получить заполненные скиллы
+print(cursor.execute('SELECT skills FROM works where skills not null').fetchall())
+
+# Задача 7
+# Вывести зарплату только у тех, у кого в скилах есть Python
+print(cursor.execute('SELECT salary FROM works where skills LIKE "%Python%"').fetchall())

sql_task.py

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+import sqlite3 as sql
+import pandas as pd
+import re
+
+con = sql.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()
+df = pd.read_csv('works.csv')
+
+def clean(file):
+    return re.sub(r'\<[^>]*\>', '', str(file))
+
+df.to_sql("works", con, if_exists='append', index=False)
+con.commit()
+
+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()
+
+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()
+
+df['skills'] = df['skills'].apply(clean)
+df['otherInfo'] = df['otherInfo'].apply(clean)