小编典典

Pandas左外连接多个列上的多个数据框

python

我是使用DataFrame的新手,我想知道如何在一系列表的多个列上执行等效于左外部联接的SQL

例:

df1: 
Year    Week    Colour    Val1 
2014       A       Red      50
2014       B       Red      60
2014       B     Black      70
2014       C       Red      10
2014       D     Green      20

df2:
Year    Week    Colour    Val2
2014       A     Black      30
2014       B     Black     100
2014       C     Green      50
2014       C       Red      20
2014       D       Red      40

df3:
Year    Week    Colour    Val3
2013       B       Red      60
2013       C     Black      80
2013       B     Black      10
2013       D     Green      20
2013       D       Red      50

本质上,我想做类似以下SQL代码的操作(注意df3在Year上没有加入):

SELECT df1.*, df2.Val2, df3.Val3
FROM df1
  LEFT OUTER JOIN df2
    ON df1.Year = df2.Year
    AND df1.Week = df2.Week
    AND df1.Colour = df2.Colour
  LEFT OUTER JOIN df3
    ON df1.Week = df3.Week
    AND df1.Colour = df3.Colour

结果应如下所示:

Year    Week    Colour    Val1    Val2    Val3
2014       A       Red      50    Null    Null
2014       B       Red      60    Null      60
2014       B     Black      70     100    Null
2014       C       Red      10      20    Null
2014       D     Green      20    Null    Null

我曾尝试使用合并和联接,但无法弄清楚如何在多个表上以及涉及多个联接时执行此操作。有人可以帮我吗?

谢谢


阅读 195

收藏
2020-12-20

共1个答案

小编典典

合并他们在两个步骤,df1df2第一,然后那到结果df3

In [33]: s1 = pd.merge(df1, df2, how='left', on=['Year', 'Week', 'Colour'])

我从df3删除了year,因为您上次加入不需要它。

In [39]: df = pd.merge(s1, df3[['Week', 'Colour', 'Val3']],
                       how='left', on=['Week', 'Colour'])

In [40]: df
Out[40]: 
   Year Week Colour  Val1  Val2 Val3
0  2014    A    Red    50   NaN  NaN
1  2014    B    Red    60   NaN   60
2  2014    B  Black    70   100   10
3  2014    C    Red    10    20  NaN
4  2014    D  Green    20   NaN   20

[5 rows x 6 columns]
2020-12-20