如何在熊猫中连接两个具有不同列名的数据框？- Python
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how to concat two data frames with different column names in pandas? - python
提问by HappyPy
df1 = pd.DataFrame({'a':[1,2,3],'x':[4,5,6],'y':[7,8,9]})
df2 = pd.DataFrame({'b':[10,11,12],'x':[13,14,15],'y':[16,17,18]})
I'm trying to merge the two data frames using the keys from the df1. I think I should use pd.mergefor this, but I how can I tell pandas to place the values in the bcolumn of df2in the acolumn of df1. This is the output I'm trying to achieve:
我正在尝试使用df1. 我想我应该用pd.merge这一点，但我我怎么能告诉大熊猫放置值的b列df2在a列df1。这是我试图实现的输出：
a x y
0 1 4 7
1 2 5 8
2 3 6 9
3 10 13 16
4 11 14 17
5 12 15 18
回答by EdChum
Just use concatand renamethe column for df2so it aligns:
In [92]:
pd.concat([df1,df2.rename(columns={'b':'a'})], ignore_index=True)
Out[92]:
a x y
0 1 4 7
1 2 5 8
2 3 6 9
3 10 13 16
4 11 14 17
5 12 15 18
similarly you can use mergebut you'd need to rename the column as above:
同样，您可以使用，merge但您需要重命名列如上：
In [103]:
df1.merge(df2.rename(columns={'b':'a'}),how='outer')
Out[103]:
a x y
0 1 4 7
1 2 5 8
2 3 6 9
3 10 13 16
4 11 14 17
5 12 15 18
回答by scottlittle
Use numpy to concatenate the dataframes, so you don't have to rename all of the columns (or explicitly ignore indexes). np.concatenatealso works on an arbitrary number of dataframes.
使用 numpy 连接数据帧，因此您不必重命名所有列（或显式忽略索引）。 np.concatenate也适用于任意数量的数据帧。
df = pd.DataFrame( np.concatenate( (df1.values, df2.values), axis=0 ) )
df.columns = [ 'a', 'x', 'y' ]
df
