python pandas dataframe 添加带有过滤条件的总列

Question

我有一个文件，可以在其中比较基础数据集不同 View 的不同信息。目标是列出信息片段并比较总数。

我有以下数据框:

df = pandas.DataFrame({"Measures": 
['Country','State','County','City'], 
"Green": ['Included','Excluded','Included','Included'], "Orange": 
['Excluded', 'Excluded', 'Excluded', 'Included']})

我有以下基础数据集:

Location    Green    Orange
Country     1        6
State       3        10
County      2        15
City        5        20

我希望最终的结果是这样的:

Measures    Green    Orange
Country     Included Excluded
State       Excluded Excluded
County      Included Excluded
City        Included Included
Total       8        20

Answer 1

您可以在计算总和之前使用 df 屏蔽底层数据帧的值。

m = df.eq('Included')   
# Assume df2 is your underlying DataFrame.
v = df2[m].sum()
# Assign the total back as a new row in df.    
df.loc['Total', :] = v[df2.dtypes != object]

df
      Measures     Green    Orange
0      Country  Included  Excluded
1        State  Excluded  Excluded
2       County  Included  Excluded
3         City  Included  Included
Total      NaN         8        20

<小时/>

如果您想要更相同的输出，另一个选项是分别将“Measures”和“Locations”设置为索引。

df = df.set_index('Measures')
df2 = df2.set_index('Location')

m = df.eq('Included') 
v = df2[m].sum()
df.loc['Total', :] = v

df
             Green    Orange
Measures                    
Country   Included  Excluded
State     Excluded  Excluded
County    Included  Excluded
City      Included  Included
Total            8        20