pandas sort_values returns unexpected result

Question

I'm trying to sort a datafarame using the pandas sort_values() function but the returned result is sorted in a strange way as shown in the image attached

it looks like your Citations column is of type string. Convert it to number then sorting should work — megges
– megges, Commented Nov 5, 2019 at 8:00
I checked the au_df_srtd.dtypes' and it returns dtype: object` for all columns — E. Aly
– E. Aly, Commented Nov 5, 2019 at 8:02

jezrael · Accepted Answer · 2019-11-05 08:02:30Z

3

Problem is column Citation is strings repr of numbers, so need convert to numeric by Series.astype:

au_df['Citation'] = au_df['Citation'].astype(int)
au_df_srtd = au_df.sort_values('Citations')

If not working because at least one string value in numbers use to_numeric with errors='coerce' for convert non numbers to NaNs:

au_df['Citation'] = pd.to_numeric(au_df['Citation'], errors='coerce')
au_df_srtd = au_df.sort_values('Citations')

edited Nov 5, 2019 at 8:02

answered Nov 5, 2019 at 8:00

jezrael

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2 Comments

U13-Forward Over a year ago

You're faster 7 sec

U13-Forward Over a year ago

nice one with to_numeric tho.

U13-Forward · Accepted Answer · 2019-11-05 08:00:31Z

2

Because they must be strings, so try using astype:

au_df['Citations'] = au_df['Citations'].astype(int)
au_df_srtd = au_df.sort_values('Citations')

answered Nov 5, 2019 at 8:00

U13-Forward

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