Finding the indexes of the N maximum values across an axis in Pandas

Question

I know that there is a method .argmax() that returns the indexes of the maximum values across an axis.

But what if we want to get the indexes of the 10 highest values across an axis?

How could this be accomplished?

E.g.:

data = pd.DataFrame(np.random.random_sample((50, 40)))

you should provide a sample result that you want because the question can be interpenetrated differently. Is it the sum of 10 highest number in a row? or 10 highest in a column? — adhg, Apr 11 '19 at 22:37

score 1 · Answer 1 · answered Apr 11 '19 at 22:31

1

IIUC, say, if you want to get the index of the top 10 largest numbers of column col:

data[col].nlargest(10).index

answered Apr 11 '19 at 22:31

Juan C

score 0 · Accepted Answer · answered Apr 11 '19 at 22:40

You can use argsort:

s = pd.Series(np.random.permutation(30))
sorted_indices = s.argsort()
top_10 = sorted_indices[sorted_indices < 10]
print(top_10)

Output:

3     9
4     1
6     0
8     7
13    4
14    2
15    3
19    8
20    5
24    6
dtype: int64

score 0 · Answer 3 · answered Apr 11 '19 at 22:41

0

Give this a try. This will take the 10 largest values across a row and put them into a dataframe.

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.random_sample((50, 40)))
df2 = pd.DataFrame(np.sort(df.values)[:,-10:])

answered Apr 11 '19 at 22:41

Angel Roman

3 Answers3