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)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)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']]Copyright © 2021 Codeinu
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