用另一个数据帧的值替换一个数据帧中的列值 [英] replace column values in one dataframe by values of another dataframe

问题描述

我有两个数据框，第一个有 1000 行，看起来像:

I have two dataframes, the first one has 1000 rows and looks like:

Date            Group         Family       Bonus
2011-06-09      tri23_1       Laavin       456
2011-07-09      hsgç_T2       Grendy       679
2011-09-10      bbbj-1Y_jn    Fantol       431
2011-11-02      hsgç_T2       Gondow       569

Group 列有不同的值，有时会重复，但通常大约有 50 个唯一值.

The column Group has different values, sometimes repeated, but in general about 50 unique values.

第二个数据框包含所有这 50 个唯一值(50 行)以及与这些值关联的酒店:

The second dataframe contains all these 50 unique values (50 rows) and also the hotels, that are associated to these values:

Group             Hotel
tri23_1           Jamel
hsgç_T2           Frank
bbbj-1Y_jn        Luxy
mlkl_781          Grand Hotel
vchs_94           Vancouver

我的目标是将第一个数据帧的 Group 列中的值替换为第二个数据帧的 Hotel 列的相应值/或创建列 Hotel 具有相应的值.当我试图通过像

My goal is to replace the value in the column Group of the first dataframe by the corresponding values of the column Hotel of the second dataframe/or create the column Hotel with the corresponding values. When I try to make it just by assignment like

df1.loc[(df1.Group=df2.Group), 'Hotel']=df2.Hotel

我有一个错误，即数据帧的大小不同，因此无法进行比较.

I have an error that the dataframes are not of equal size, so the comparison is not possible.

推荐答案

如果您将索引设置为另一个 df 的 'Group' 列，那么您可以使用 map 在原始 df 'Group' 列上:

If you set the index to the 'Group' column on the other df then you can replace using map on your original df 'Group' column:

In [36]:
df['Group'] = df['Group'].map(df1.set_index('Group')['Hotel'])
df

Out[36]:
         Date  Group  Family  Bonus
0  2011-06-09  Jamel  Laavin    456
1  2011-07-09  Frank  Grendy    679
2  2011-09-10   Luxy  Fantol    431
3  2011-11-02  Frank  Gondow    569

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