“nan vs Nat pandas” Respostas de código

Conde Nan Pandas

#Python, pandas
#Count missing values for each column of the dataframe df

df.isnull().sum()
Ahh the negotiatior

Valores de nan pandas na coluna

df['your column name'].isnull()
Perro Fiel

nan vs Nat pandas

>>> import pandas as pd, datetime, numpy as np
>>> df = pd.DataFrame({'a': [datetime.datetime.now(), np.nan], 'b': [5, np.nan], 'c': [1, 2]})
>>> df
                           a    b  c
0 2019-02-17 18:06:15.231557  5.0  1
1                        NaT  NaN  2
>>> fill_dt = datetime.datetime.now()
>>> fill_value = 4
>>> dt_filled_df = df.select_dtypes('datetime').fillna(fill_dt)
>>> dt_filled_df
                           a
0 2019-02-17 18:06:15.231557
1 2019-02-17 18:06:36.040404
>>> value_filled_df = df.select_dtypes('int').fillna(fill_value)
>>> value_filled_df
   c
0  1
1  2
>>> dt_filled_df.columns = [col + '_notnull' for col in dt_filled_df]
>>> value_filled_df.columns = [col + '_notnull' for col in value_filled_df]
>>> df = df.join(value_filled_df)
>>> df = df.join(dt_filled_df)
>>> df
                           a    b  c  c_notnull                  a_notnull
0 2019-02-17 18:06:15.231557  5.0  1          1 2019-02-17 18:06:15.231557
1                        NaT  NaN  2          2 2019-02-17 18:06:36.040404
Yellowed Yak

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