pandas 如何使用pandas在时间序列中查找连续的相同数据
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/26911851/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to use pandas to find consecutive same data in time series
提问by figo
Here is a time series data like this,call it df:
这是一个像这样的时间序列数据，称之为 df：
'No' 'Date' 'Value'
0 600000 1999-11-10 1
1 600000 1999-11-11 1
2 600000 1999-11-12 1
3 600000 1999-11-15 1
4 600000 1999-11-16 1
5 600000 1999-11-17 1
6 600000 1999-11-18 0
7 600000 1999-11-19 1
8 600000 1999-11-22 1
9 600000 1999-11-23 1
10 600000 1999-11-24 1
11 600000 1999-11-25 0
12 600001 1999-11-26 1
13 600001 1999-11-29 1
14 600001 1999-11-30 0
I want to get the date range of the consecutive 'Value' of 1, so how can I get the final result as follows:
我想获取连续“值”为 1 的日期范围，那么如何获得最终结果如下：
'No' 'BeginDate' 'EndDate' 'Consecutive'
0 600000 1999-11-10 1999-11-17 6
1 600000 1999-11-19 1999-11-24 4
2 600001 1999-11-26 1999-11-29 2
回答by user1827356
This should do it
这应该做
df['value_grp'] = (df.Values.diff(1) != 0).astype('int').cumsum()
value_grp will increment by one whenever Value changes. Below, you can extract the group results
每当 Value 更改时，value_grp 将增加 1。下面，您可以提取分组结果
pd.DataFrame({'BeginDate' : df.groupby('value_grp').Date.first(),
'EndDate' : df.groupby('value_grp').Date.last(),
'Consecutive' : df.groupby('value_grp').size(),
'No' : df.groupby('value_grp').No.first()}).reset_index(drop=True)
回答by MaxU
Here is an alternative solution:
这是一个替代解决方案：
rslt = (df.assign(Consecutive=df.Value
.groupby((df.Value != df.Value.shift())
.cumsum())
.transform('size'))
.query('Consecutive > 1')
.groupby('Consecutive')
.agg({'No':{'No':'first'}, 'Date': {'BeginDate':'first', 'EndDate':'last'}})
.reset_index()
)
rslt.columns = [t[1] if t[1] else t[0] for t in rslt.columns]
Demo:
演示：
In [225]: %paste
rslt = (df.assign(Consecutive=df.Value
.groupby((df.Value != df.Value.shift())
.cumsum())
.transform('size'))
.query('Consecutive > 1')
.groupby('Consecutive')
.agg({'No':{'No':'first'}, 'Date': {'BeginDate':'first', 'EndDate':'last'}})
.reset_index()
)
rslt.columns = [t[1] if t[1] else t[0] for t in rslt.columns]
## -- End pasted text --
In [226]: rslt
Out[226]:
Consecutive BeginDate EndDate No
0 2 1999-11-26 1999-11-29 600001
1 4 1999-11-19 1999-11-24 600000
2 6 1999-11-10 1999-11-17 600000
