通过从不同的数据框中查找来替换列中的pandas值

Question

我有一个参考DataFrame,如下所示:

    Variables   Key Values  
0   GRTYPE      40  Total exclusions 4-year schools
1   GRTYPE      2   4-year institutions, Adjusted cohort
2   GRTYPE      3   4-year institutions, Completers 
41  CHRTSTAT    2   Revised cohort
42  CHRTSTAT    3   Exclusions
43  CHRTSTAT    4   Adjusted cohort 
57  SECTION     12  Bachelors/ equiv .
58  SECTION     23  Bachelors or equiv 2009 .

我想使用参考数据框来替换下面主DataFrame中的值:

    GRTYPE      CHRTSTAT  SECTION
0   40             2    12      
1   2              3    12      
2   2              4    23      
3   3              2    12  
4   3              3    23  

最终结果将是:

    GRTYPE                                CHRTSTAT          SECTION
0   Total exclusions 4-year schools         Revised cohort       Bachelors/ equiv . 
1   4-year institutions, Adjusted cohort    Exclusions           Bachelors/ equiv .         
2   4-year institutions, Adjusted cohort    Adjusted cohort      Bachelors or equiv 2009 .      
3   4-year institutions, Completers         Revised cohort       Bachelors/ equiv . 
4   4-year institutions, Completers         Exclusions           Bachelors or equiv 2009 .  

在pandas或python中执行此操作的最佳方法是什么？我尝试从第一个数据帧加入和提取变量,并在第二个数据帧上循环,但没有得到任何结果.

Answer 1

运用 map

您需要设置Variables和Key作为映射数据框的索引,然后只需在列上使用map.

mapping_df = mapping_df.set_index(['Variables', 'Key'])
df = df.apply(lambda x: x.map(mapping_df.loc[x.name]['Values']))

与以下相同:

mapping_df = mapping_df.set_index(['Variables', 'Key'])
df['GRTYPE'] = df.GRTYPE.map(mapping_df.loc['GRTYPE']['Values'])
df['CHRTSTAT'] = df.CHRTSTAT.map(mapping_df.loc['CHRTSTAT']['Values'])
df['SECTION'] = df.SECTION.map(mapping_df.loc['SECTION']['Values'])

输出:

                                 GRTYPE         CHRTSTAT                    SECTION
0       Total exclusions 4-year schools   Revised cohort         Bachelors/ equiv .
1  4-year institutions, Adjusted cohort       Exclusions         Bachelors/ equiv .
2  4-year institutions, Adjusted cohort  Adjusted cohort  Bachelors or equiv 2009 .
3       4-year institutions, Completers   Revised cohort         Bachelors/ equiv .
4       4-year institutions, Completers       Exclusions  Bachelors or equiv 2009 .