python pandas dataframe concat和group by function

时间:2017-07-01 12:33:51

标签: python excel pandas dataframe

我在excel中有数据如下

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(i.e 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

... 我到目前为止编写的代码,感谢一些指针为什么pd.concat不能在这里工作?并且不能

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))

1 个答案:

答案 0 :(得分:1)

您的示例数据和输出让我感到困惑,但我想这就是您想要的。

#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

或第二季

  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