CODEWITHSUNDEEP
pythonpandasdataframejupyter-notebookfeature-engineering
Lynn
Lynn

Reputation: 131

Pandas: calculate mean of Dataframe column values per "year"

I have a data frame representing the customers checkins (visits) of restaurants. year is simply the year when a checkin in a restaurant happened .

data = {
        'restaurant_id':  ['--1UhMGODdWsrMastO9DZw', '--1UhMGODdWsrMastO9DZw','--1UhMGODdWsrMastO9DZw','--1UhMGODdWsrMastO9DZw','--1UhMGODdWsrMastO9DZw','--1UhMGODdWsrMastO9DZw','--6MefnULPED_I942VcFNA','--6MefnULPED_I942VcFNA','--6MefnULPED_I942VcFNA','--6MefnULPED_I942VcFNA'],
        'year': ['2016','2016','2016','2016','2017','2017','2011','2011','2012','2012'],
        }
df = pd.DataFrame (data, columns = ['restaurant_id','year'])


# here i count the total number of checkins a restaurant had
d = df.groupby('restaurant_id')['year'].count().to_dict()
df['nb_checkin'] = df['restaurant_id'].map(d)


mean_checkin= df.groupby(['restaurant_id','year']).agg({'nb_checkin':[np.mean]})
mean_checkin.columns = ['mean_checkin']
mean_checkin.reset_index()

# the values in mean_checkin makes no sens

#I need to merge it with df to add that new column

I am still new with the pandas lib, I tried something like this but my results makes no sens. Is there something wrong with my syntax? If any clarifications needed, please ask.

Upvotes: 0

Views: 1375

Answers (1)

Cameron Riddell
Cameron Riddell

Reputation: 13417

The average number of visits per year can be calculated as the total number of visits a restaurant has, divided by the number of unique years you have data for.

grouped = df.groupby(["restaurant_id"])
avg_annual_visits = grouped["year"].count() / grouped["year"].nunique()
avg_annual_visits = avg_annual_visits.rename("avg_annual_visits")

print(avg_annual_visits)
restaurant_id
--1UhMGODdWsrMastO9DZw    3.0
--6MefnULPED_I942VcFNA    2.0
Name: avg_annual_visits, dtype: float64

Then if you wanted to merge it back to your original data:

df = df.merge(avg_annual_visits, left_on="restaurant_id", right_index=True)

print(df)
            restaurant_id  year  avg_annual_visits
0  --1UhMGODdWsrMastO9DZw  2016                3.0
1  --1UhMGODdWsrMastO9DZw  2016                3.0
2  --1UhMGODdWsrMastO9DZw  2016                3.0
3  --1UhMGODdWsrMastO9DZw  2016                3.0
4  --1UhMGODdWsrMastO9DZw  2017                3.0
5  --1UhMGODdWsrMastO9DZw  2017                3.0
6  --6MefnULPED_I942VcFNA  2011                2.0
7  --6MefnULPED_I942VcFNA  2011                2.0
8  --6MefnULPED_I942VcFNA  2012                2.0
9  --6MefnULPED_I942VcFNA  2012                2.0

Upvotes: 1

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