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]
Try this:
dataframe[column].value_counts().index.tolist()
['apple', 'sausage', 'banana', 'cheese']
#!/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]
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()
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}
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']
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