我正在尝试按连续日期对ID进行分组.
ID Date
abc 2017-01-07
abc 2017-01-08
abc 2017-01-09
abc 2017-12-09
xyz 2017-01-05
xyz 2017-01-06
xyz 2017-04-15
xyz 2017-04-16
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需要退货:
ID Count
abc 3
abc 1
xyz 2
xyz 2
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我试过了:
d = {'ID': ['abc', 'abc', 'abc', 'abc', 'xyz', 'xyz', 'xyz', 'xyz'], 'Date': ['2017-01-07','2017-01-08', '2017-01-09', '2017-12-09', '2017-01-05', '2017-01-06', '2017-04-15', '2017-04-16']}
df = pd.DataFrame(data=d)
df['Date'] = pd.to_datetime(df['Date'])
today = pd.to_datetime('2018-10-23')
x = df.sort_values('Date', ascending=0)
g = x.groupby(['ID'])
x[(today - x['Date']).dt.days == g.cumcount()].groupby(['ID']).size()
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是否有一种简单的方法可以通过ID获取所有日期范围的计数?