python之按一列中出现的频率对整个 csv 进行排序，并仅显示实例的一个副本

我有一个看起来像这样的 csv:

CompanyName    High Priority     QualityIssue 
Customer1         Yes             User 
Customer1         Yes             User 
Customer2         No              User 
Customer3         No              Equipment 
Customer1         No              Neither 
Customer3         No              User 
Customer3         Yes             User 
Customer3         Yes             Equipment 
Customer4         No              User 

我想计算 CompanyName 中的每个实例在整个文件中出现了多少次，并按出现次数递减排序，但只打印一次 CompanyName:

例如，使用这段代码:

df['count'] = df.groupby('CompanyName'['CompanyName'].transform(pd.Series.value_counts) 
df.sort('count', ascending=False) 

我得到:

Out: 
 
CompanyName HighPriority QualityIssue count 
5   Customer3           No         User     4 
3   Customer3           No    Equipment     4 
7   Customer3          Yes    Equipment     4 
6   Customer3          Yes         User     4 
0   Customer1          Yes         User     3 
4   Customer1           No      Neither     3 
1   Customer1          Yes         User     3 
8   Customer4           No         User     1 
2   Customer2           No         User     1 

我想要的是:

   CompanyName   count 
   Customer3       4 
   Customer1       3 
   Customer4       1 
   Customer2       1 

有什么想法吗？

问题 2: 空行:

CompanyName    High Priority     QualityIssue 
Customer1         Yes             User 
Customer1         Yes             User 
                  No              User   
Customer3         No              Equipment   
Customer1         No              Neither 
                  No              User 
Customer3         Yes             User 
Customer3         Yes             Equipment 
Customer4         No              User 

预期输出:

   CompanyName   count 
   Customer3       3 
   Customer1       3 
                   2 
   Customer4       1 

请您参考如下方法:

我想你可以跳过两行，直接写

# single columns 
df.CompanyNames.value_counts() 
# or 
df['CompanyNames'].value_counts() 
# or via Sriram solution 
df.groupby(['CompanyNames']).size() 
 
# Multiple columns 
df.groupBy(['CompanyNames', 'HighPriority']).size() 

Python: get a frequency count based on two columns (variables) in pandas dataframe

这应该会给你你想要的，而不是将计数附加为一列。

编辑

替换 Nan 值然后找到计数

df.CompanyNames = df.CompanyNames.fillna('unknown') 
# or inline 
df.CompanyNames.fillna('unknown', inplace=True) 

然后用之前的代码总结一下