drop if nan in column pandas
df = df[df['EPS'].notna()]
remove nan from list python
cleanedList = [x for x in countries if str(x) != 'nan']
drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwoman
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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