在 Pandas value_counts() 中提取值

Question

Say we have used pandas dataframe[column].value_counts() which outputs:

 apple   5 
 sausage 2
 banana  2
 cheese  1

How do you extract the values in the order same as shown above from max to min ?

eg: [apple,sausage,banana,cheese]

Answer 1

Try this:

dataframe[column].value_counts().index.tolist()
['apple', 'sausage', 'banana', 'cheese']

Answer 2

#!/usr/bin/env python

import pandas as pd

# Make example dataframe
df = pd.DataFrame([(1, 'Germany'),
                   (2, 'France'),
                   (3, 'Indonesia'),
                   (4, 'France'),
                   (5, 'France'),
                   (6, 'Germany'),
                   (7, 'UK'),
                   ],
                  columns=['groupid', 'country'],
                  index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])

# What you're looking for
values = df['country'].value_counts().keys().tolist()
counts = df['country'].value_counts().tolist()

Now, print(df['country'].value_counts()) gives:

France       3
Germany      2
UK           1
Indonesia    1

and print(values) gives:

['France', 'Germany', 'UK', 'Indonesia']

and print(counts) gives:

[3, 2, 1, 1]

Answer 3

如果有人在评论中错过了它，请尝试以下操作：

dataframe[column].value_counts().to_frame()

Answer 4

The best way to extract the values is to just do the following

json.loads(dataframe[column].value_counts().to_json())

This returns a dictionary which you can use like any other dict. Using values or keys.

 {"apple": 5, "sausage": 2, "banana": 2, "cheese": 1}

Answer 5

First you have to sort the dataframe by the count column max to min if it's not sorted that way already. In your post, it is in the right order already but I will sort it anyways:

dataframe.sort_index(by='count', ascending=[False])
    col     count
0   apple   5
1   sausage 2
2   banana  2
3   cheese  1 

Then you can output the col column to a list:

dataframe['col'].tolist()
['apple', 'sausage', 'banana', 'cheese']