熊猫:计算每"year"的数据帧列值的平均值



我有一个数据框架,表示顾客在餐馆的登记(访问(。year只是一家餐厅办理入住手续的年份。

  • 我想做的是在我的初始数据框df中添加一列average_checkin,它表示每年餐厅的平均访问次数
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

我还是熊猫库的新手,我尝试过这样的东西,但我的结果毫无意义。我的语法有问题吗?如果需要任何澄清,请询问。

每年的平均访问次数可以计算为餐厅的总访问次数除以您拥有数据的唯一年份。

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

然后,如果你想将其合并回你的原始数据:

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

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