drop if nan in column pandas
df = df[df['EPS'].notna()]
how to remove rows with nan in pandas
df.dropna(subset=[columns],inplace=True)
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwoman
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 1940-04-25
when converting from dataframe to list delete nan values
a = [[y for y in x if pd.notna(y)] for x in df.values.tolist()]
print (a)
[['str', 'aad', 'asd'], ['ddd'], ['xyz', 'abc'], ['btc', 'trz', 'abd']]
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