drop if nan in column pandas
df = df[df['EPS'].notna()]remove all rows where one ccolumns egale to nan
#remove in dataframe but no in the file
df = df[df['column'].notna()]
#remove in dataframe and in the file
df.dropna(subset=['EPS'], how='all', inplace=True)drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwomanclean nas from column pandas
>>> df.dropna()
name toy born
1 Batman Batmobile 1940-04-25threshold meaning in 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.dropna(thresh=2)
name toy born
1 Batman Batmobile 1940-04-25
2 Catwoman Bullwhip NaTCopyright © 2021 Codeinu
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