Replace list of values in a dataframe with NaN

Question

I have a list of values [1,-1,2,'X']. I want to replace these values that are in the dataframe with a NaN value.

Here is what I tried

non_values = [1,-1,2,'X'] for i in non_values: #azdias is the name of the dataframe that I am trying to change. azdias.replace(i, np.NaN, inplace=True)

However, the solution above doesn't make change on the output. Is there any other way to do this

jezrael · Accepted Answer · 2020-03-29 06:23:58Z

Use DataFrame.mask with default NaNs replace with selected values by DataFrame.isin:

azdias = pd.DataFrame({'a':[1,2,3,-1], 'b':list('XYZX')}) non_values = [1,-1,2,'X'] azdias = azdias.mask(azdias.isin(non_values)) print (azdias) a b 0 NaN NaN 1 NaN Y 2 3.0 Z 3 NaN NaN

Or use DataFrame.replace:

azdias = azdias.replace(non_values, np.nan) print (azdias) a b 0 NaN NaN 1 NaN Y 2 3.0 Z 3 NaN NaN

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