Python 在 Pandas value_counts() 中提取值
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Extract values in Pandas value_counts()
提问by JamesButterlips
Say we have used pandas dataframe[column].value_counts()which outputs:
假设我们使用了dataframe[column].value_counts()输出：
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 ?
您如何按照与上述相同的顺序从 max 到 min 提取值？
e.g: [apple,sausage,banana,cheese]
例如： [apple,sausage,banana,cheese]
采纳答案by Mike Müller
Try this:
尝试这个：
dataframe[column].value_counts().index.tolist()
['apple', 'sausage', 'banana', 'cheese']
回答by Joe T. Boka
First you have to sortthe dataframeby the countcolumn maxto minif it's not sorted that way already. In your post, it is in the right order already but I will sortit anyways:
首先，你必须sort在dataframe由count列max到min，如果没有排序已经如此。在您的帖子中，它的顺序已经正确，但sort无论如何我都会这样做：
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 colcolumn to a list:
然后您可以将col列输出到列表：
dataframe['col'].tolist()
['apple', 'sausage', 'banana', 'cheese']
回答by Martin Thoma
#!/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:
现在，print(df['country'].value_counts())给出：
France 3
Germany 2
UK 1
Indonesia 1
and print(values)gives:
并print(values)给出：
['France', 'Germany', 'UK', 'Indonesia']
and print(counts)gives:
并print(counts)给出：
[3, 2, 1, 1]
回答by Sawant
If anyone missed it out in the comments, try this:
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()
回答by Harish Kumawat
Code
代码
train["label_Name"].value_counts()
where : label_Name Mean column_name
其中： label_Name 均值 column_name
result (my case) :-
结果（我的情况）：-
0 29720
1 2242
Name: label, dtype: int64
