Concatenate strings from several rows using Pandas groupby

You can groupby the 'name' and 'month' columns, then call transform which will return data aligned to the original df and apply a lambda where we join the text entries:

In [119]:df['text'] = df[['name','text','month']].groupby(['name','month'])['text'].transform(lambda x: ','.join(x))df[['name','text','month']].drop_duplicates()Out[119]:    name         text  month0  name1       hej,du     112  name1        aj,oj     124  name2     fin,katt     116  name2  mycket,lite     12

I sub the original df by passing a list of the columns of interest df[['name','text','month']] here and then call drop_duplicates

EDIT actually I can just call apply and then reset_index:

In [124]:df.groupby(['name','month'])['text'].apply(lambda x: ','.join(x)).reset_index()Out[124]:    name  month         text0  name1     11       hej,du1  name1     12        aj,oj2  name2     11     fin,katt3  name2     12  mycket,lite

update

the lambda is unnecessary here:

In[38]:df.groupby(['name','month'])['text'].apply(','.join).reset_index()Out[38]:     name  month         text0  name1     11           du1  name1     12        aj,oj2  name2     11     fin,katt3  name2     12  mycket,lite

we can groupby the 'name' and 'month' columns, then call agg() functions of Panda’s DataFrame objects.

The aggregation functionality provided by the agg() function allows multiple statistics to be calculated per group in one calculation.

df.groupby(['name', 'month'], as_index = False).agg({'text': ' '.join})

The answer by EdChum provides you with a lot of flexibility but if you just want to concateate strings into a column of list objects you can also:

output_series = df.groupby(['name','month'])['text'].apply(list)