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I have a dataframe like this:

article_id title NaN title_1 NaN title_2 NaN title_3 '202102011404103' title_4 '202102011404104' title_5 NaN title_6

Firstly I would like to add a condition 'if there is NaN value do the following' (else do nothing). If there is NaN value in the column: I would like to add directly an incremental value to NaN values in the column with something like this:

x = 1 df.insert(0, 'article_id', range(x, x + len(df)))

But I don't know how to add directly the code above to the column article_id, only to NaN values. How can I do it ?

Expected output:

article_id title 1 title_1 2 title_2 3 title_3 '202102011404103' title_4 '202102011404104' title_5 4 title_6
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  • Can you add expected output? Commented Feb 4, 2021 at 13:08
  • 1
    Hello, I updated my post Commented Feb 4, 2021 at 13:10

1 Answer 1

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You can create mask for compare missing values and pass range with first value with count of NaNs by sum:

m = df['article_id'].isna() x = 1 df.loc[m, 'article_id'] = range(x, x + m.sum()) print (df) article_id title 0 1 title_1 1 2 title_2 2 3 title_3 3 '202102011404103' title_4 4 '202102011404104' title_5 5 4 title_6
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