如何对列求和然后在 Pandas python 中对它们进行排序

Question

Below is a sample DataFrame, The data is in .csv file.

  EPISODE_Number EPISODE_TITLE  object1  object2  object3  object4  object5
0         S01E01             A        1        1        0        0        0
1         S01E02             B        0        0        0        1        0
2         S01E03             C        1        1        0        0        1
3         S01E04             D        0        1        1        1        0
4         S01E05             E        1        0        0        1        0
5         S01E06             F        1        1        0        1        1
6         S01E07             G        0        0        0        1        1
7         S01E08             H        0        1        0        0        0
8         S01E09             I        1        1        0        1        1
9         S01E10             J        0        1        1        0        0

I would like to have the sum of each object and then sort the objects from bigger to smaller (top 10 only)

Below is my code so far:

import pandas as pd

data = pd.read_csv("TV_show.csv")
sume_s =  data[data.sum(0).sort_values(ascending=False)[2:6].index]

output should be like below:

object2: 7
object4: 6
object1: 5
object5: 4
object3: 2

But I'm getting the following error:

    indexer = non_nan_idx[non_nans.argsort(kind=kind)]
TypeError: '>' not supported between instances of 'numpy.ndarray' and 'str'

Answer 1

Use DataFrame.iloc with sum and for top 10 add Series.nlargest :

sume_a = data.iloc[:, 2:7].sum().nlargest(10)
print (sume_a)
object2    7
object4    6
object1    5
object5    4
object3    2
dtype: int64

Working like comment solution:

sume_a = data.iloc[:, 2:7].sum().sort_values(ascending=False).head(10)