Sorting values in a pandas series in ascending order not working when re-assigned

问题

I am trying to sort a Pandas Series in ascending order.

Top15['HighRenew'].sort_values(ascending=True)

Gives me:

Country
China                       1
Russian Federation          1
Canada                      1
Germany                     1
Italy                       1
Spain                       1
Brazil                      1
South Korea           2.27935
Iran                  5.70772
Japan                 10.2328
United Kingdom        10.6005
United States          11.571
Australia             11.8108
India                 14.9691
France                17.0203
Name: HighRenew, dtype: object

The values are in ascending order.

However, when I then modify the series in the context of the dataframe:

Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True)
Top15['HighRenew']

Gives me:

Country
China                       1
United States          11.571
Japan                 10.2328
United Kingdom        10.6005
Russian Federation          1
Canada                      1
Germany                     1
India                 14.9691
France                17.0203
South Korea           2.27935
Italy                       1
Spain                       1
Iran                  5.70772
Australia             11.8108
Brazil                      1
Name: HighRenew, dtype: object

Why this is giving me a different output to that above?

Would be grateful for any advice?

回答1:

Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).to_numpy() 

or

Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).reset_index(drop=True)

When you sort_values , the indexes don't change so it is aligning per the index!

Thank you to anky for providing me with this fantastic solution!

来源：https://stackoverflow.com/questions/61802149/sorting-values-in-a-pandas-series-in-ascending-order-not-working-when-re-assigne