Convert pandas series to int with NaN values

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I have a series (month_addded) in my DataFrame like this:

9.0
12.0
12.0
nan
1.0

I want all the floats to be ints, and the NaN's to stay as they are. I did this:

for i in df['month_added']:
    if i > 0:
        i=int(i)

But it did nothing.

pandas dataframe python
1 Answers

NaN is float typed, so Pandas would always downcast your column to float as long as you have NaN. You can use Nullable Integer, available from Pandas 0.24.0:

df['month_added'] = df['month_added'].astype('Int64')

If that's not possible, you can force Object type (not recommended):

df['month_added'] = pd.Series([int(x) if x > 0 else x for x in df.month_added], dtype='O')

Or since your data is positive and NaN, you can mask NaN with 0:

df['month_added'] = df['month_added'].fillna(0).astype(int)
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