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Description
this is from a stackoverflow question here, you can download serialized object here and reproduce using python 2.7 and pandas 0.16.2.
I'm trying to concat two series with multiindex using pd.concat([a, b], axis=1)
like so:
>>>payed_orders.head()
dt product_id
2015-01-15 10001 1
10007 1
10016 14
10022 1
10023 1
Name: payed_orders, dtype: int64
>>>refund_orders.head()
dt product_id
2015-01-15 10007 1
10016 4
10030 1
2015-01-16 10007 3
10008 1
Name: refund_orders, dtype: int64
>>>pd.concat([payed_orders.head(), refund_orders.head()], axis=1, ignore_index=False)
payed_orders refund_orders
dt product_id
2015-01-15 10001 NaN NaN
10007 NaN NaN
10016 NaN NaN
10022 NaN NaN
10023 NaN NaN
10030 NaN NaN
2015-01-16 10007 NaN NaN
10008 NaN NaN
I've checked the index type and many other stuff to make sure no obvious were made, I've read the docs to learn that concatenating and merging series and dataframes may introduce NaN
, but I didn't find anything in the docs to explain this behavior.