[python-3.x] Concatenate strings from several rows using Pandas groupby

I want to merge several strings in a dataframe based on a groupedby in Pandas.

This is my code so far:

import pandas as pd
from io import StringIO

data = StringIO("""
"name1","hej","2014-11-01"
"name1","du","2014-11-02"
"name1","aj","2014-12-01"
"name1","oj","2014-12-02"
"name2","fin","2014-11-01"
"name2","katt","2014-11-02"
"name2","mycket","2014-12-01"
"name2","lite","2014-12-01"
""")

# load string as stream into dataframe
df = pd.read_csv(data,header=0, names=["name","text","date"],parse_dates=[2])

# add column with month
df["month"] = df["date"].apply(lambda x: x.month)

I want the end result to look like this:

I don't get how I can use groupby and apply some sort of concatenation of the strings in the column "text". Any help appreciated!

If you want to concatenate your "text" in a list:

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

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)

For me the above solutions were close but added some unwanted /n's and dtype:object, so here's a modified version:

df.groupby(['name', 'month'])['text'].apply(lambda text: ''.join(text.to_string(index=False))).str.replace('(\\n)', '').reset_index()