如何合并具有相同索引的多行，每一行在熊猫中只有一个真实值？

Question

I have a pandas dataframe which has the following shape:

                          OPEN_INT PX_HIGH PX_LAST VOL
timestamp  ticker source     
2018-01-01   AAPL   NYSE         1      NaN    NaN NaN
2018-01-01   AAPL   NYSE       NaN        2    NaN NaN
2018-01-01   AAPL   NYSE       NaN      NaN      3 NaN
2018-01-01   AAPL   NYSE       Nan      NaN    NaN   4
2018-01-01   MSFT   NYSE         5      NaN    NaN NaN
2018-01-01   MSFT   NYSE       NaN        6    NaN NaN
2018-01-01   MSFT   NYSE       NaN      NaN      7 NaN
2018-01-01   MSFT   NYSE       Nan      NaN    NaN   8

In each column for each (timestamp, ticker, source) group there is gurantted only one value, all other values are Nan, is there any way I can combine these into single rows so it looks like:

                          OPEN_INT PX_HIGH PX_LAST VOL
timestamp  ticker source     
2018-01-01   AAPL   NYSE         1      2        3   4
2018-01-01   MSFT   NYSE         5      6        7   8

I have tried to use df.groupby(['timestamp', 'ticker', 'source']).agg(lambda x: x.dropna() but I got an error saying Function does not reduce .

Answer 1

Use GroupBy.first :

df.groupby(['timestamp', 'ticker', 'source']).first()

If is always only one value per groups aggregate by max , min , sum , mean ...:

df.groupby(['timestamp', 'ticker', 'source']).max()