Be the following python pandas DataFrame.
| date | days | country |
| ------------- | ---------- | --------- |
| 2022-02-01 | 10 | Spain |
| 2022-02-02 | 20 | Spain |
| 2022-02-01 | 10 | Italy |
| 2022-02-03 | 41 | France |
| 2022-02-03 | 13 | Germany |
| 2022-02-04 | 11 | Italy |
| 2022-02-04 | 1 | UK |
| 2022-02-05 | 20 | UK |
| 2022-02-04 | 50 | Spain |
| 2022-02-04 | 11 | Portugal |
I want to get a ranking by country according to the number of rows from that country that appear.
| country | count |
| ---------------- | ----------- |
| Spain | 3 |
| Italy | 2 |
| UK | 2 |
| France | 1 |
| Germany | 1 |
| Portugal | 1 |
Finally I want to return the countries from most to least number of rows in a string array.
return: countries = ['Spain', 'Italy', 'UK', 'France', 'Germany', 'Portugal']
The aim is that from this array you can make subsets of the top 3 and analyse the data for each one.
df1 = df[ (df['country'] == countries[0]) ].reset_index(drop=True)
df2 = df[ (df['country'] == countries[1]) ].reset_index(drop=True)
df3 = df[ (df['country'] == countries[2]) ].reset_index(drop=True)
The dataframe may vary by month in the country classification, which is why I want to do it this way.
