我使用groupby
' categorical_variable
+缩减器对空间栅格执行空间叠加/聚合。我想知道是否有办法为某些数据变量使用不同的reducer。例如,在下面的代码中,我希望first()
缩小mode
(或continuous_variable
,但似乎没有实现),mean()
用import xarray as xr
import numpy as np
categorical_variable = np.array([[1,1,1,1,1],
[1,1,1,1,2],
[1,1,1,2,2],
[1,1,2,2,2],
[1,2,2,2,2]], dtype='int16')
grouping_variable = np.array([[1,1,1,2,2],
[1,1,3,2,2],
[1,3,3,3,3],
[3,3,3,3,3],
[4,4,4,4,4]], dtype='int16')
continuous_variable = np.random.rand(5,5)
xr_dataset = xr.Dataset({'grouping_variable': xr.DataArray(grouping_variable,
dims=['x', 'y']),
'categorical_variable': xr.DataArray(categorical_variable,
dims=['x', 'y']),
'continuous_variable': xr.DataArray(continuous_variable,
dims=['x', 'y'])})
xr_grouped = xr_dataset.groupby('grouping_variable')
xr_reduced = xr_grouped.mean()
::ApplicationCable::Connection
答案 0 :(得分:1)
目前在xarray目前的AFAIK中,目前还不能实现这一目标,但是既然你失去了空间结构,你可以很简单地通过熊猫去使用agg
:
>>> df = xr_dataset.to_dataframe()
>>> df.groupby('grouping_variable').agg({"categorical_variable": "first",
"continuous_variable": "mean"})
categorical_variable continuous_variable
grouping_variable
1 1 0.458534
2 1 0.822294
3 1 0.539483
4 1 0.515586