How to merge rows in pandas dataframe

Question

I have a dataframe that looks like this:

productID	units sold	units in inventory
101	32	NaN
102	45	NaN
103	15	NaN
104	27	NaN
101	NaN	18
102	NaN	12
103	NaN	30
104	NaN	23

As you can see, the first column contains duplicates, where each instance has data in one 'data' column, but not the other 'data' column.

Is there a way to merge the rows, so the dataframe looks like this?

productID	units sold	units in inventory
101	32	18
102	45	12
103	15	30
104	27	23

[`Groupby.first`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.first.html) -> `df.groupby('productID', as_index=False).first()` — Henry Ecker, Aug 29 '21 at 02:03

score 1 · Accepted Answer · answered Aug 29 '21 at 02:02

Try groupby.first:

>>> df.groupby('productID', as_index=False).first()
   productID  units sold  units in inventory
0        101        32.0                18.0
1        102        45.0                12.0
2        103        15.0                30.0
3        104        27.0                23.0
>>>

productID	units sold	units in inventory
101	32	NaN
102	45	NaN
103	15	NaN
104	27	NaN
101	NaN	18
102	NaN	12
103	NaN	30
104	NaN	23

productID	units sold	units in inventory
101	32	NaN
102	45	NaN
103	15	NaN
104	27	NaN
101	NaN	18
102	NaN	12
103	NaN	30
104	NaN	23

How to merge rows in pandas dataframe

1 Answers1

productID	units sold	units in inventory
101	32	NaN
102	45	NaN
103	15	NaN
104	27	NaN
101	NaN	18
102	NaN	12
103	NaN	30
104	NaN	23