drop if nan in column pandas
df = df[df['EPS'].notna()]
pandas dropna specific column
df.dropna(subset=['column1','column2'], inplace=True)
dropna for specific column pandas
df = df[df['EPS'].notna()] #instead of dropping, take another DF with non-na values
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
dropna in specific column pandas
df.dropna(subset = ['column1', 'column2'], inplace = True)
drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwoman
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