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question editted to avoid duplication

I have a pandas dataframe with A, B, C, D , E columns:

A B C D E

X 2 3 - 5

Y Â 3 4 Â

Z - - Â 5

I would like to remove all non-machine readable characters (Â) and non-numeric characters (-) from column B onwards and replace them with NaN.

Thanks

Analyst
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1 Answers1

2

Using where

df.where(df.applymap(
    lambda x: str(x).isdigit()
))
piRSquared
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  • Thanks. This works. A followup; if I only wanted to remove non-machine readable characters from the frame (i.e. keep standard text), how would I modify this? – Analyst Apr 23 '18 at 13:55