Pandas : How to drop #DIV/0! and NA values in new column in pandas dataframe?

2024/11/16 7:46:36

I did some calculation and have #DIV/0! in my dataframe. How to drop these values and count further ? I followed df.dropna but dataframe still counting #DIV/0!. Please suggest.

df.insert(loc=df.columns.get_loc('A')+1 , column = 'new', value=(abs(df['A'] - df['B'])/df['B'] * 100))
df = df.dropna()
df.reset_index(drop=True)
print(len(df.index))

Answer

You can tell your script to treat '#DIV/0!' as NaN values when you read your excel/csv file:

More here: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html

df = pd.read_csv('my_file.csv', na_values=['#DIV/0!'])

https://en.xdnf.cn/q/118955.html

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