Python pandas groupby 中的最大和最小日期
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Max and Min date in pandas groupby
提问by DataSwede
I have a dataframe that looks like:
我有一个看起来像的数据框：
data = {'index': ['2014-06-22 10:46:00', '2014-06-24 19:52:00', '2014-06-25 17:02:00', '2014-06-25 17:55:00', '2014-07-02 11:36:00', '2014-07-06 12:40:00', '2014-07-05 12:46:00', '2014-07-27 15:12:00'],
'type': ['A', 'B', 'C', 'A', 'B', 'C', 'A', 'C'],
'sum_col': [1, 2, 3, 1, 1, 3, 2, 1]}
df = pd.DataFrame(data, columns=['index', 'type', 'sum_col'])
df['index'] = pd.to_datetime(df['index'])
df = df.set_index('index')
df['weekofyear'] = df.index.weekofyear
df['date'] = df.index.date
df['date'] = pd.to_datetime(df['date'])
type sum_col weekofyear date
index
2014-06-22 10:46:00 A 1 25 2014-06-22
2014-06-24 19:52:00 B 2 26 2014-06-24
2014-06-25 17:02:00 C 3 26 2014-06-25
2014-06-25 17:55:00 A 1 26 2014-06-25
2014-07-02 11:36:00 B 1 27 2014-07-02
2014-07-06 12:40:00 C 3 27 2014-07-06
2014-07-05 12:46:00 A 2 27 2014-07-05
2014-07-27 15:12:00 C 1 30 2014-07-27
I'm looking to groupby the weekofyear, then sum up the sum_col. In addition, I need to find the earliest, and the latest date for the week. The first part is pretty easy:
我希望按周分组，然后总结 sum_col。另外，我需要找到一周中最早和最晚的日期。第一部分非常简单：
gb = df.groupby(['type', 'weekofyear'])
gb['sum_col'].agg({'sum_col' : np.sum})
I've tried to find the min/max date with this, but haven't been successful:
我试图用这个找到最小/最大日期，但没有成功：
gb = df.groupby(['type', 'weekofyear'])
gb.agg({'sum_col' : np.sum,
'date' : np.min,
'date' : np.max})
How would one find the earliest/latest date that appears?
如何找到最早/最晚出现的日期？
采纳答案by chrisb
You need to combine the functions that apply to the same column, like this:
您需要组合适用于同一列的函数，如下所示：
In [116]: gb.agg({'sum_col' : np.sum,
...: 'date' : [np.min, np.max]})
Out[116]:
date sum_col
amin amax sum
type weekofyear
A 25 2014-06-22 2014-06-22 1
26 2014-06-25 2014-06-25 1
27 2014-07-05 2014-07-05 2
B 26 2014-06-24 2014-06-24 2
27 2014-07-02 2014-07-02 1
C 26 2014-06-25 2014-06-25 3
27 2014-07-06 2014-07-06 3
30 2014-07-27 2014-07-27 1
回答by Shantanu Deshmukh
Simple code can be
简单的代码就可以
df.groupby([key_field]).agg({'time_field': [np.min,np.max]})
where key_field here can be event_id and time_field can be timestamp field.
其中 key_field 可以是 event_id，time_field 可以是时间戳字段。
