Python 熊猫：合并（加入）多列上的两个数据框
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pandas: merge (join) two data frames on multiple columns
提问by Edamame
I am trying to join two pandas data frames using two columns:
我正在尝试使用两列连接两个熊猫数据框：
new_df = pd.merge(A_df, B_df, how='left', left_on='[A_c1,c2]', right_on = '[B_c1,c2]')
but got the following error:
但出现以下错误：
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4164)()
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4028)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13166)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13120)()
KeyError: '[B_1, c2]'
Any idea what should be the right way to do this? Thanks!
知道什么是正确的方法吗？谢谢！
回答by Shijo
Try this
尝试这个
new_df = pd.merge(A_df, B_df, how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html
left_on : label or list, or array-like Field names to join on in left DataFrame. Can be a vector or list of vectors of the length of the DataFrame to use a particular vector as the join key instead of columns
right_on : label or list, or array-like Field names to join on in right DataFrame or vector/list of vectors per left_on docs
left_on ：标签或列表，或类似数组的字段名称，以加入左侧数据帧。可以是 DataFrame 长度的向量或向量列表，以使用特定向量作为连接键而不是列
right_on ：标签或列表，或类似数组的字段名称，以加入右侧数据帧或每个 left_on 文档的向量/向量列表
回答by Celius Stingher
the problem here is that by using the apostrophes you are setting the value being passed to be a string, when in fact, as @Shijo stated from the documentation, the function is expecting a label or list, but not a string! If the list contains each of the name of the columns beings passed for both the left and right dataframe, then each column-name mustindividually be within apostrophes. With what has been stated, we can understand why this is inccorect:
这里的问题是，通过使用撇号，您将传递的值设置为字符串，而实际上，正如@Shijo 从文档中所述，该函数需要一个标签或列表，而不是一个字符串！如果列表包含为左右数据框传递的每个列的名称，则每个列名称必须单独位于撇号内。根据上述内容，我们可以理解为什么这是不正确的：
new_df = pd.merge(A_df, B_df, how='left', left_on='[A_c1,c2]', right_on = '[B_c1,c2]')
And this is the correct way of using the function:
这是使用该功能的正确方法：
new_df = pd.merge(A_df, B_df, how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])
回答by john ed
Another way of doing this:
new_df = A_df.merge(B_df, left_on=['A_c1','c2'], right_on = ['B_c1','c2'], how='left')
这样做的另一种方法：
new_df = A_df.merge(B_df, left_on=['A_c1','c2'], right_on = ['B_c1','c2'], how='left')
