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I'm attempting to drop a range of columns in a pandas dataframe that have all NaN. I know the following code:

df.dropna(axis=1, how='all', inplace = True)

Will search all the columns in the dataframe and drop the ones that have all NaN.

However, when I extend this code to a specific range of columns:

df[df.columns[48:179]].dropna(axis=1, how='all', inplace = True)

The result is the original dataframe with no columns removed. I also no for a fact that the selected range has multiple columns with all NaN's

Any idea what I might be doing wrong here?

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2 Answers 2

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Don't use inplace=True. Instead do this:

cols = df.columns[48:179]
df[cols] = df[cols].dropna(axis=1, how='all')
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3 Comments

Thank you, however, that only returns a dataframe containing the variables in the range. How would I return the above columns into the original dataframe?
@r_user Please check my updated answer.
Hmm. I appreciate the help. However, I get a Columns must be same length as key valueerror
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inplace=True can only used when you apply changes to the whole dataframe. I won't work in range of columns. Try to use dropna without inplace=True to see the results(in a jupyter notebook)

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Hi @Anas. You can improve the readability of your answer using the text forma options.

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