Pandas reindex subset of rows

January 23, 2022

I have the following dataframe:

import pandas as pd
#Create DF
d = { 
     'Country': ['USA','USA','AUS','AUS','AUS','UK','UK'],
    'poulation_k':[200,250,150,120,350,800,600,],
    }
           
df = pd.DataFrame(data=d)
df

I would like to sort the rows by poulation where Country = AUS but maintaining their order in the overall dataframe:

So my expected output will be:

I would also like to do it by the other countries however i would like to do it on a manual basis – i.e i would like the function to specify the Country name. Any help would be fantastic! Thanks

>Solution :

Use df.sort_values with df.loc:

# Create a function to sort df by population
In [99]: def sort_population(country):
    ...:     # Find index of rows for the country passed
    ...:     ix = df[df.Country.eq(country)].index 
    ...:     # Update the df for the above index with the new sorted population
    ...:     df.loc[ix, 'poulation_k'] = df[df.Country.eq(country)].sort_values('poulation_k', ascending=False)['poulation_k'].tolist()
    ...: 

In [101]: sort_population('AUS')

In [102]: df
Out[102]: 
  Country  poulation_k
0     USA          200
1     USA          250
2     AUS          350
3     AUS          150
4     AUS          120
5      UK          800
6      UK          600