Python Pandas：在具有不同名称的字段上加入 DataFrames？
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Pandas: join DataFrames on field with different names?
提问by woshitom
According to this documentationI can only make a join between fields having the same name.
根据此文档，我只能在具有相同名称的字段之间进行连接。
Do you know if it's possible to join two DataFrames on a field having different names?
您知道是否可以在具有不同名称的字段上连接两个 DataFrame 吗？
The equivalent in SQL would be:
SQL 中的等效项是：
SELECT *
FROM df1
LEFT OUTER JOIN df2
ON df1.id_key = df2.fk_key
采纳答案by Alex Riley
I think what you want is possible using merge. Pass in the keyword arguments for left_onand right_onto tell Pandas which column(s) from each DataFrame to use as keys:
我认为使用merge. 传入left_on和的关键字参数right_on以告诉 Pandas 将每个 DataFrame 中的哪些列用作键：
pandas.merge(df1, df2, how='left', left_on=['id_key'], right_on=['fk_key'])
The documentation describes this in more detail on this page.
回答by Vipul Saxena
df2['id_key'] = df2['fk_key'].str.lower()
df2['id_key'] = df2['fk_key'].str.lower()
df1['id_key'] = df1['id_key'].str.lower()
df1['id_key'] = df1['id_key'].str.lower()
Now try to merge the dataframes
现在尝试合并数据帧
df3 = pd.merge(df2,df1,how='inner', on='id_key')
df3 = pd.merge(df2,df1,how='inner', on='id_key')
