drop if nan in column pandas
df = df[df['EPS'].notna()]
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
dropping nan in pandas dataframe
df.dropna(subset=['name', 'born'])
drop column with nan values
fish_frame = fish_frame.dropna(axis = 1, how = 'all')
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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