pandas filter non nan
filtered_df = df[df['name'].notnull()]pandas replace nan
data["Gender"].fillna("No Gender", inplace = True)python dataframe replace nan with 0
In [7]: df
Out[7]:
0 1
0 NaN NaN
1 -0.494375 0.570994
2 NaN NaN
3 1.876360 -0.229738
4 NaN NaN
In [8]: df.fillna(0)
Out[8]:
0 1
0 0.000000 0.000000
1 -0.494375 0.570994
2 0.000000 0.000000
3 1.876360 -0.229738
4 0.000000 0.000000dataframe fill nan with mode
df['Column_Name'].fillna(df['Column_Name'].mode()[0], inplace=True)Copyright © 2021 Codeinu
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