pandas 左外联接的结果表大于左表 [英] Pandas Left Outer Join results in table larger than left table
问题描述
根据我对左外部联接的了解,结果表的行数永远不应超过左表的行数……如果这是错误的话,请告诉我...
From what I understand about a left outer join, the resulting table should never have more rows than the left table...Please let me know if this is wrong...
我的左表是192572行和8列.
My left table is 192572 rows and 8 columns.
我的右边表格是42160行和5列.
My right table is 42160 rows and 5 columns.
我的左"表中有一个名为"id"的字段,该字段与我的右表中的一列键"相匹配.
My Left table has a field called 'id' which matches with a column in my right table called 'key'.
因此,我将它们合并为这样:
Therefore I merge them as such:
combined = pd.merge(a,b,how='left',left_on='id',right_on='key')
但是合并后的形状是236569.
But then the combined shape is 236569.
我误会什么?
推荐答案
如果键与另一个DataFrame中的多个行匹配,则可以预期这种情况会增加:
You can expect this to increase if keys match more than one row in the other DataFrame:
In [11]: df = pd.DataFrame([[1, 3], [2, 4]], columns=['A', 'B'])
In [12]: df2 = pd.DataFrame([[1, 5], [1, 6]], columns=['A', 'C'])
In [13]: df.merge(df2, how='left') # merges on columns A
Out[13]:
A B C
0 1 3 5
1 1 3 6
2 2 4 NaN
为避免此行为,请将重复项放在df2中:
In [21]: df2.drop_duplicates(subset=['A']) # you can use take_last=True
Out[21]:
A C
0 1 5
In [22]: df.merge(df2.drop_duplicates(subset=['A']), how='left')
Out[22]:
A B C
0 1 3 5
1 2 4 NaN
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