Python的pandas数据框连接和按function分组

我有在Excel中的数据如下

category size1 size2 size3 cat1 10 20 30 cat2 20 10 15 cat3 30 20 10 

我想要两个报告/ excel输出如下

 #1) Category-sizetype-value cat1 size1 10 cat1 size2 20 cat1 size3 30 cat2 size1 20 

…

 #2) Category-size-value-value counts(ie how many time specific size value appears) cat1 size1 10 3 times cat1 size2 20 2 times cat1 size3 30 1 time cat2 size1 20 4 times 

…到目前为止我写的代码，感谢一些指针为什么pd.concat不在这里工作？ 而且不能

 import pandas as pd path_to_file = 'C:\Users\Niru\Desktop\cat-sizes.xlsx' xl = pd.ExcelFile(path_to_file) print(xl.sheet_names) df = xl.parse('Sheet1') #print(df.head()) print(df.columns) frames = [] for i in df.columns: dfd = "df.loc[:,['Category','" +i+"']]" frames.append(dfd) print(pd.concat(frames)) 

Answer 1

你的示例数据和输出使我困惑了一下，但是我想这就是你想要的。

 #Q1: df1=pd.melt(df, id_vars=['category'], value_vars=['size1','size2','size3']) Out[66]: category variable value 0 cat1 size1 10 1 cat2 size1 20 2 cat3 size1 30 3 cat1 size2 20 4 cat2 size2 10 5 cat3 size2 20 6 cat1 size3 30 7 cat2 size3 15 8 cat3 size3 10 #Q2: df1['counts']=df1.groupby(['variable','value']).transform('count') Out[69]: category variable value counts 0 cat1 size1 10 1 1 cat2 size1 20 1 2 cat3 size1 30 1 3 cat1 size2 20 2 4 cat2 size2 10 1 5 cat3 size2 20 2 6 cat1 size3 30 1 7 cat2 size3 15 1 8 cat3 size3 10 1 

或Q2

  df1['counts']=df1.groupby(['variable']).transform('count') Out[71]: category variable value counts 0 cat1 size1 10 3 1 cat2 size1 20 3 2 cat3 size1 30 3 3 cat1 size2 20 3 4 cat2 size2 10 3 5 cat3 size2 20 3 6 cat1 size3 30 3 7 cat2 size3 15 3 8 cat3 size3 10 3