How to get top 5 dense ranked rows in Pandas?

January 15, 2022

So I tried to get this working. I know how to sort, use nlargest or use rank with method dense.. But somehow I’m still lost.

Here is what I want to achieve:

I always want to have top 3 rows based on some value (1, 2, 3)
But, if there are multiple rows with same values, then I want to have more than 3 rows (e.g. 1,2,2,3 should return 4 rows)

Let’s say I have this data

I want to select top3 rows based on the lowest score and I want to get this

As I said I want top3 rows, but if there is the same score, should get 4 or more.

I got lost a bit in all of the combinations that I tried. Is there a simple way do do this?

>Solution :

You can create an array that has the 3 smallest values of your Score column, and then use isin to filter your dataframe:

some_vals = pd.Series(df['Score'].unique()).nsmallest(3).values
df[df['Score'].isin(some_vals)]

   Name  Score
0   John      1
1   Mark      2
2  Perry      2
3   Dion      3

This way you ensure that all Name’s that have a value in Score equal to any of the 3 smallest values will be returned back.