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pandas dataframe map

df.applymap(lambda x: x**2)

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

pandas series map

s.map({'cat': 'kitten', 'dog': 'puppy'})
0   kitten
1    puppy
2      NaN
3      NaN
dtype: object

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

Syntax of pandas map()

# Syntax of Series.map()
Series.map(arg, na_action=None)

Comment

map dataframe

>>> s.map({'cat': 'kitten', 'dog': 'puppy'})
0   kitten
1    puppy
2      NaN
3      NaN
dtype: object

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

map column dataframe python

df = pd.DataFrame({'col1':pd.date_range('2015-01-02 15:00:07', periods=3),
                   'col2':pd.date_range('2015-05-02 15:00:07', periods=3),
                   'col3':pd.date_range('2015-04-02 15:00:07', periods=3),
                   'col4':pd.date_range('2015-09-02 15:00:07', periods=3),
                   'col5':[5,3,6],
                   'col6':[7,4,3]})

print (df)
                 col1                col2                col3  
0 2015-01-02 15:00:07 2015-05-02 15:00:07 2015-04-02 15:00:07   
1 2015-01-03 15:00:07 2015-05-03 15:00:07 2015-04-03 15:00:07   
2 2015-01-04 15:00:07 2015-05-04 15:00:07 2015-04-04 15:00:07   

                 col4  col5  col6  
0 2015-09-02 15:00:07     5     7  
1 2015-09-03 15:00:07     3     4  
2 2015-09-04 15:00:07     6     3  

list_of_cols_to_change = ['col1','col2','col3','col4']
df[list_of_cols_to_change] = df[list_of_cols_to_change].apply(lambda x: x.dt.date)
print (df)
         col1        col2        col3        col4  col5  col6
0  2015-01-02  2015-05-02  2015-04-02  2015-09-02     5     7
1  2015-01-03  2015-05-03  2015-04-03  2015-09-03     3     4
2  2015-01-04  2015-05-04  2015-04-04  2015-09-04     6     3

Comment

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pandas dataframe map

map column dataframe python

pandas series map

map column dataframe python

Syntax of pandas map()

map dataframe

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

map column dataframe python

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