python中的两个Series如何相乘或相除？

Question

我有一个这样的数据集。不过实际数据集要大得多。

data1 = pd.DataFrame({'Name':["Tom","Andy","Joseph","Joe","Mary","Alexa","Chris","Jessica","Jimmy","Andrea","George","Bruce","Will","Eric","Leonard","Ryan","Megan","Michael","Sara"],\
                  "City":["NY","DC","LAX","NY","DC","DC","SF","SD","NY","SF","SD","DC","LAX","SF","LAX","NY","SF","PDX","FL"],\
                  'Car':["Ford","Ford","TOYOTA","GM","GM","Honda","GM","Porsche","Tesla","TOYOTA","Tesla","Tesla","Honda","GM","Nissan","Porsche","Nissan","Ford","Tesla"]})

首先，我想计算“City”和“Car”组合的实际频率并这样做了。

df_City_Car_actual=data1.groupby(["City","Car"]).size()
df_City_Car_actual

然后我想计算“城市”和“汽车”组合的预期频率。所以我先做了这个。

df_City=data1.groupby("City").size()
df_City
df_Car=data1.groupby("Car").size()
df_Car

然后我想乘以 df_City 和 df_Car 并显示 City x Car 的预期频率。例如，“DC”频率在 df_City 中为 4，“Ford”频率在 df_Car 中为 3。因此，DC x Ford 预期频率将为 4x3=12。

我试过了但是没用

df_City_Car_expected=df_City*df_Car
df_City_Car_expected

最后，我想将 df_City_Car_actual 除以 df_City_Car_expected，以便最终数据标准化。有没有好的方法来做到这一点？感谢您的帮助。

Answer 1

我能想到的最简单的方法是使用numpy“外积”函数，例如：

pd.DataFrame(np.outer(df_City.values, df_Car.values), index=df_City.index, columns=df_Car.index)

给出：

Car   Ford  GM  Honda  Nissan  Porsche  TOYOTA  Tesla
City                                                 
DC      12  16      8       8        8       8     16
FL       3   4      2       2        2       2      4
LAX      9  12      6       6        6       6     12
NY      12  16      8       8        8       8     16
PDX      3   4      2       2        2       2      4
SD       6   8      4       4        4       4      8
SF      12  16      8       8        8       8     16

python中的两个Series如何相乘或相除？

How to multiply or divide two Series in python?

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