Pandas groupby周给出了一个日期时间列

Question

假设我有以下数据样本:

df = pd.DataFrame({'date':['2011-01-01','2011-01-02',
                       '2011-01-03','2011-01-04','2011-01-05',
                       '2011-01-06','2011-01-07','2011-01-08',
                       '2011-01-09','2011-12-30','2011-12-31'],
                   'revenue':[5,3,2,
                              10,12,2,
                              1,0,6,10,12]})

# Let's format the date and add the week number and year
df['date'] = pd.to_datetime(df['date'],format='%Y-%m-%d')
df['week_number'] = df['date'].dt.week
df['year'] = df['date'].dt.year

df

        date        revenue     week_of_year    year
0       2011-01-01  5           52              2011
1       2011-01-02  3           52              2011
2       2011-01-03  2           1               2011
3       2011-01-04  10          1               2011
4       2011-01-05  12          1               2011
5       2011-01-06  2           1               2011
6       2011-01-07  1           1               2011
7       2011-01-08  0           1               2011
8       2011-01-09  6           1               2011
9       2011-12-30  10          52              2011
10      2011-12-31  12          52              2011

我想计算每周的收入,以便稍后绘制结果,并分析时间序列.预期的输出将是这样的:

    week    revenue
0   1       8
1   2       33
2   52      22

我首先考虑使用给出的周数timestamp.week.
但是,我无法弄清楚如何处理第1周之前一周的ISO周数定义.我有点困惑,因为week_number在这种情况下分组将在年初的收入总和,以及那些年底的人.

Answer 1

使用dt.week转换时,它是ISO周日期.

你可以用 strftime

df.groupby(df.date.dt.strftime('%W')).revenue.sum()
Out[588]: 
date
00     8
01    33
52    22
Name: revenue, dtype: int64