check for missing/ nan values in pandas dataframe
In [27]: df
Out[27]:
A B C
1 NaN -2.027325 1.533582
2 NaN NaN 0.461821
3 -0.788073 NaN NaN
4 -0.916080 -0.612343 NaN
5 -0.887858 1.033826 NaN
In [28]: df.isnull().sum() # Returns the sum of NaN values in each column.
Out[28]:
A 2
B 2
C 3
In [29]: df.isnull().sum().sum # Returns the total NaN values in the dataframe
Out[29]:
7how to fill nan values with mean in pandas
df.fillna(df.mean())dataframe fill nan with mode
df['Column_Name'].fillna(df['Column_Name'].mode()[0], inplace=True)Copyright © 2021 Codeinu
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