45353

import pandas as pd

path1  = r'path to the csv table'
path2  = r'path to the csv table'

#1
ins_left = pd.read_csv(path1)
ins_right = pd.read_csv(path2)
print(ins_left.head())

#2
print(ins_left.info(), ins_right.info(), sep='\n')
print(ins_right.isnull.any(), ins_left.isnull.any(), sep='\n')

#3
ins_right = ins_right.dropna()
ins_left = ins_left.dropna()

#4
ins_left = ins_left.drop_duplicates()
ins_right = ins_right.drop_duplicates()
df = pd.merge('column name from the first table', 'column name from the second table')
print(df.info())

#5
female = pd.DataFrame(ins_left[(15 <= ins_left.age) & (ins_left.age <= 75)])
print(female.head(20))

#6
df['cigs2'] = df['cigs2'].mask(df['cigs'] < 10, 1)
df['cigs2'] = df['cigs2'].mask((df['cigs'] >= 10) & (df['cigs'] < 20), 2)
df['cigs2'] = df['cigs2'].mask(df['cigs'] > 20, 3)
print(df.loc[df['cigs2'] == 1, df['age'].mean()])
print(df.loc[df['cigs2'] == 2, df['age'].mean()])
print(df.loc[df['cigs2'] == 3, df['age'].mean()])

#8
df1 = df[]