获取跨列的值 - Pandas DataFrame

时间:2022-12-16 22:51:58

I have a Pandas DataFrame like following:

我有一个像下面这样的Pandas DataFrame:

               A              B              C
0   192.168.2.85   192.168.2.85  124.43.113.22
1  192.248.8.183  192.248.8.183   192.168.2.85
2  192.168.2.161            NaN  192.248.8.183
3   66.249.74.52            NaN  192.168.2.161
4            NaN            NaN   66.249.74.52

I want to get the count of a certain values across columns. So my expected output is something like:

我想获得跨列的特定值的计数。所以我的预期输出是这样的:

IP          Count
192.168.2.85 3 #Since this value is there in all coulmns
192.248.8.183 3
192.168.2.161 2
66.249.74.52 2
124.43.113.22 1

I know how to this across rows, but doing this for columns is bit strange?Help me to solve this? Thanks.

我知道如何跨行,但对列进行此操作有点奇怪吗?帮帮我解决这个问题?谢谢。

2 个解决方案

#1


34  

stack it first and then use value_counts:

首先堆栈然后使用value_counts:

In [14]: df.stack().value_counts()
Out[14]: 
192.248.8.183    3   
192.168.2.85     3   
66.249.74.52     2   
192.168.2.161    2   
124.43.113.22    1   
dtype: int64

#2


2  

df['Counts'] = df[['col1','col2','col3']].groupby(['col1','col2','col3']).transform('count')

#1


34  

stack it first and then use value_counts:

首先堆栈然后使用value_counts:

In [14]: df.stack().value_counts()
Out[14]: 
192.248.8.183    3   
192.168.2.85     3   
66.249.74.52     2   
192.168.2.161    2   
124.43.113.22    1   
dtype: int64

#2


2  

df['Counts'] = df[['col1','col2','col3']].groupby(['col1','col2','col3']).transform('count')