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')pandas dropna
df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],
... "toy": [np.nan, 'Batmobile', 'Bullwhip'],
... "born": [pd.NaT, pd.Timestamp("1940-04-25"),
... pd.NaT]})
>>> df
name toy born
0 Alfred NaN NaT
1 Batman Batmobile 1940-04-25
2 Catwoman Bullwhip NaT
##Drop the rows where at least one element is missing.
>>> df.dropna()
name toy born
1 Batman Batmobile 1940-04-25Copyright © 2021 Codeinu
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