将计算列添加到 Pandas 数据透视表
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Add calculated column to a pandas pivot table
提问by Pynewbie
I have created a pandas data frame and then converted it into pivot table.
我创建了一个Pandas数据框，然后将其转换为数据透视表。
My pivot table looks like this:
我的数据透视表如下所示：
Operators TotalCB Qd(cb) Autopass(cb)
Aircel India 55 11 44
Airtel Ghana 20 17 3
Airtel India 41 9 9
Airtel Kenya 9 4 5
Airtel Nigeria 24 17 7
AT&T USA 18 10 8
I was wondering how to add calculated columns so that I get my pivot table with Autopass% (Autopass(cb)/TotalCB*100) just like we are able to create them in Excel using calculated field option.
我想知道如何添加计算列，以便使用 Autopass% ( Autopass(cb)/TotalCB*100)获取数据透视表，就像我们能够使用计算字段选项在 Excel 中创建它们一样。
I want my pivot table output to be something like below:
我希望我的数据透视表输出如下所示：
Operators TotalCB Qd(cb) Autopass(cb) Qd(cb)% Autopass(cb)%
Aircel India 55 11 44 20% 80%
Airtel Ghana 20 17 3 85% 15%
Airtel India 41 29 9 71% 22%
Airtel Kenya 9 4 5 44% 56%
AT&T USA 18 10 8 56% 44%
How do I define the function which calculates the percentage columns and how to apply that function to my two columns namely Qd(cb)and Autopass(cb)to give me additional calculated columns
我如何定义计算百分比列的函数以及如何将该函数应用于我的两列Qd(cb)并Autopass(cb)为我提供额外的计算列
采纳答案by Korem
This should do it, assuming datais your pivoted dataframe:
这应该可以做到，假设data是您的旋转数据框：
data['Autopass(cb)%'] = data['Autopass(cb)'] / data['TotalCB'] * 100
data['Qd(cb)%'] = data['Qd(cb)'] / data['TotalCB'] * 100
Adding a new column to a dataframe is as simple as df['colname'] = new_series. Here we assign it with your requested function, when we do it as a vector operation it creates a new series.
向数据框中添加新列就像df['colname'] = new_series. 在这里，我们将您请求的功能分配给它，当我们将其作为向量操作进行时，它会创建一个新系列。
