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When I was trying to horizontally concatenate several DataFrames which contain some overlapping column names, and those overlapping columns would remain unchanged. However, it might be quite useful to have a suffixes
argument as e.g DataFrame.merge
has in practice, so that could easily add meaningful suffix to distinguish those overlapped columns. And this argument will be used only when axis=1
.
While a walkaround for this is: pd.merge(df1, df2, left_index=True, right_index=True)
, but this cannot be applied in more dfs.
Just found out that this might be similar to #21791 and if this is the arg we want to add, I would be happy to work on this.
Minimum reproducible code:
>>> df1 = pd.DataFrame({"a": [1, 2, 3], "b": [2, 3, 4]})
>>> df2 = pd.DataFrame({"a": [4, 5, 6], "b": [7, 8, 9]})
>>> pd.concat([df1, df2], axis=1)
a | b | a | b
-- | -- | -- | --
1 | 2 | 4 | 7
2 | 3 | 5 | 8
3 | 4 | 6 | 9
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