在同一个 df 中合并具有相同索引的 Pandas df 行

Question

If I have a df that looks something like this:

               v1     v2         ...   v10       v11
id                               ...                            
102717.0   101234650  2018-08-27  ...   NaN       NaN
102717.0   101234650  2018-08-27  ...  UDMS    27/08/2018
102717.0   101234650  2018-08-27  ...   NaN       NaN
102717.0   101234650  2018-08-27  ...  UDMS    27/08/2018

So when the id col matches how could I combine these to just 1 row?

Desired output would be something like:

               v1     v2         ...   v10       v11
id                               ...                            
102717.0   101234650  2018-08-27  ...  UDMS    27/08/2018

So the script would check for all values across each row that are repeated and then reduce it down filling any NaN values...

Answer 1

It really depends on what your results should look like. Eg does v2 always contain the same date for the corresponding id? From what I guess you're trying to do I'd do the following:

mean_dict = dict((el, np.nanmean) for el in df.columns)
newdf = df.groupby('id').agg(mean_dict)

I hope that helps. With more detailed information of your input and desired output we might be able to help you better.