df

import pandas as pd
import numpy as np

path_right = r"C:\Users\Max-13700kf\PycharmProjects\pythonProject\right_fix.csv"
path_left = r"C:\Users\Max-13700kf\PycharmProjects\pythonProject\left_fix.csv"

elagin_right_df = pd.read_csv(path_right) # иногда нужно указать sep
elagin_left_df = pd.read_csv(path_left)
#
# 1
print(elagin_left_df.head())
print('---------------------')
# 2
print(elagin_right_df.isnull().any(), end='\n-------------\n')
print(elagin_right_df.info(), end='\n-------------\n')
print(elagin_left_df.isnull().any(), end='\n-------------\n')
print(elagin_left_df.info(), end='\n-------------\n')

# 3
print(elagin_right_df.duplicated(), end='\n-------------\n')
print(elagin_left_df.duplicated(), end='\n-------------\n')

#
# #4
elagin_left_df = elagin_left_df.drop_duplicates()
df = pd.merge(elagin_left_df, elagin_right_df, how='outer',
              on=['id', 'male', 'age', 'is_spb', 'married', 'children', 'elagin_attractiv'])
print(df.info())

# 5
df = df.sort_values(['education', 'age'], ascending=[True, True])
print(df.head(20))

# 6
group = df.groupby(['elagin_attractiv'])
print(group.groups)
for i in group.groups.keys():
    print(f'{i}:{len(group.groups[i])}')
print('-------')

# 7
df['att2'] = np.nan
df['att2'] = df['att2'].mask(df['elagin_attractiv'] < 4, 0)
df['att2'] = df['att2'].mask(df['elagin_attractiv'] >= 4, 1)
group = df.groupby(['att2'])
for i in group.groups.keys():
    print(f'{i}:{len(group.groups[i])}')

#8
print(round(df.groupby(['elagin_attractiv']).age.mean(), 2))

df.to_csv('res.csv')