drop if nan in column pandas
df = df[df['EPS'].notna()]
drop null rows pandas
df.dropna()
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
clean nas from column pandas
>>> df.dropna()
name toy born
1 Batman Batmobile 1940-04-25
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