Drop rows with specific values in all columns Pandas

Question

I got a dataframe and I want to drop all the rows that contain a value >= 100 in all the columns (in the whole dataframe), not in just one specific column. I tried : df = df[(df < 100).any()] df.drop(df[(df <= 100)].index, inplace=True)

But nothing work... Could you please help ?

Do you want any row where any value is >= 100 to be dropped, or do you want any where where every value is >= 100 to be dropped? It's not 100% clear in your question. — BeRT2me
– BeRT2me, Commented Apr 25, 2022 at 23:40
Please provide enough code so others can better understand or reproduce the problem. — Community
– Community Bot, Commented Apr 26, 2022 at 4:40

fsimonjetz · Accepted Answer · 2022-04-25 23:11:29Z

1

Once you have the Boolean mask (df >= 100 or df.ge(100)) you can select the rows where all values are True with all(axis=1), then reverse the resulting mask with ~ to select the desired rows from the original df.

df = df[~df.ge(100).all(axis=1)]

answered Apr 25, 2022 at 23:11

fsimonjetz

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