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[英]Pandas DateTimeIndex multiple groupby or resample aggregation
[英]pandas groupby with datetimeindex
grouped = data.groupby('LA_DECH')
start = date(2016, 1, 1)
end = date(2016, 12, 31)
rng = pd.date_range(start, end, freq='BM')
有沒有一種簡單的方法可以通過以下比較提取數據(df列表): '2016/1/1' < grouped['LA_DECH] < '2016/2/29'
並且每個周期的rng
?
至少對我來說,您沒有給出很好的例證,說明您遇到了什么問題以及您想得到什么。 你是這個意思嗎
import pandas as pd
import numpy as np
from datetime import datetime
start = datetime(2016,1,1)
end = datetime(2016,12,31)
idx = pd.date_range('2015-01-01','2017-09-01')
df = pd.DataFrame(np.random.randint(10,size= (len(idx),2)), index= idx, columns=['VALUE',"LA_DECH"])
rng = pd.date_range(start, end, freq='BM')
# filted by start and end date
df = df[(df.index>start)&(df.index <end)] # this line is not necessary needed
print(df.groupby([pd.cut(df.index,rng), 'LA_DECH'])['LA_DECH'].count())
LA_DECH
(2016-01-29, 2016-02-29] 0 2
2 1
3 5
4 2
5 3
6 4
7 4
8 5
9 5
(2016-02-29, 2016-03-31] 0 4
2 1
3 4
4 5
5 2
6 3
7 3
8 6
9 3
..
(2016-08-31, 2016-09-30] 8 2
9 1
(2016-11-30, 2016-12-30] 0 2
1 1
2 1
3 1
4 1
5 5
6 3
7 5
8 5
9 6
Name: LA_DECH, Length: 104, dtype: int64
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