“Pandas Karte” Code-Antworten

Mapping -Wert zu Daten in Pandas DataFrame

note: u can assigne values in each of the common values in the dataframe 

df['new_coloum'] = df['coloum'].map({'value_1':1,'value_2':0})
JAKKA9

MAP DataFrame

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

Pandas Karte

def f(x):
    return Series([x.min(), x.max()], index=['min', 'max'])
Cruel Cockroach

MAP -Spaltendatenrahmen 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
Mike Rocket

Pandas Series Map

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

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