remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
drop na in pandas
df.dropna(inplace = True)
or
df_new = df.dropna()
drop na pandas
>>> df.dropna(subset=['name', 'born'])
name toy born
1 Batman Batmobile 1940-04-25
drop na for empty rows
org_dest.dropna(subset=['Vehicle'],inplace = True)
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