[英]Pandas Rolling mean based on groupby multiple columns
I have a Long format dataframe with repeated values in two columns and data in another column. 我有一个长格式的数据框,在两列中有重复的值,在另一列中有数据。 I want to find SMAs for each group.
我想为每个组查找SMA。 My problem is :
rolling()
simply ignores the fact that the data is grouped by two columns. 我的问题是:
rolling()
只是忽略了数据按两列分组的事实。
Here is some dummy data and code. 这是一些伪数据和代码。
import numpy as np
import pandas as pd
dtix=pd.Series(pd.date_range(start='1/1/2019', periods=4) )
df=pd.DataFrame({'ix1':np.repeat([0,1],4), 'ix2':pd.concat([dtix,dtix]), 'data':np.arange(0,8) })
df
ix1 ix2 data 0 0 2019-01-01 0 1 0 2019-01-02 1 2 0 2019-01-03 2 3 0 2019-01-04 3 0 1 2019-01-01 4 1 1 2019-01-02 5 2 1 2019-01-03 6 3 1 2019-01-04 7
Now when I perform a grouped rolling mean on this data, I am getting an output like this: 现在,当我对这些数据执行分组的滚动均值时,得到的输出如下:
df.groupby(['ix1','ix2']).agg({'data':'mean'}).rolling(2).mean()
data ix1 ix2 0 2019-01-01 NaN 2019-01-02 0.5 2019-01-03 1.5 2019-01-04 2.5 1 2019-01-01 3.5 2019-01-02 4.5 2019-01-03 5.5 2019-01-04 6.5
Desired Output: Whereas, what I would actually like to have is this: 所需的输出:而我实际上想要的是:
sma ix1 ix2 0 2019-01-01 NaN 2019-01-02 0.5 2019-01-03 1.5 2019-01-04 2.5 1 2019-01-01 NaN 2019-01-02 4.5 2019-01-03 5.5 2019-01-04 6.5
Will appreciate your help with this. 感谢您的帮助。
Use another groupby
by firast level ( ix1
) with rolling
: 使用另一个
groupby
由firast水平( ix1
)与rolling
:
df1 = (df.groupby(['ix1','ix2'])
.agg({'data':'mean'})
.groupby(level=0, group_keys=False)
.rolling(2)
.mean())
print (df1)
data
ix1 ix2
0 2019-01-01 NaN
2019-01-02 0.5
2019-01-03 1.5
2019-01-04 2.5
1 2019-01-01 NaN
2019-01-02 4.5
2019-01-03 5.5
2019-01-04 6.5
In your solution affter aggregation is returned one column DataFrame
, so chained rolling
working with all rows, not per groups like need: 在您的解决方案中,聚合返回的是一列
DataFrame
,因此链式rolling
用于所有行,而不是按需要按组进行:
print(df.groupby(['ix1','ix2']).agg({'data':'mean'}))
data
ix1 ix2
0 2019-01-01 0
2019-01-02 1
2019-01-03 2
2019-01-04 3
1 2019-01-01 4
2019-01-02 5
2019-01-03 6
2019-01-04 7
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.