我正在尝试计算每组中的成员数量，类似于pandas.DataFrame.groupby.count。但是，它似乎并没有起作用。这是一个例子：
In [1]: xr_test = xr.DataArray(np.random.rand(6), coords=[[10,10,11,12,12,12]], dims=['dim0'])
xr_test
Out[1]: <xarray.DataArray (dim0: 6)>
array([ 0.92908804, 0.15495709, 0.85304435, 0.24039265, 0.3755476 ,
0.29261274])
Coordinates:
* dim0 (dim0) int32 10 10 11 12 12 12
In [2]: xr_test.groupby('dim0').count()
Out[2]: <xarray.DataArray (dim0: 6)>
array([1, 1, 1, 1, 1, 1])
Coordinates:
* dim0 (dim0) int32 10 10 11 12 12 12
但是，我希望这个输出：
Out[2]: <xarray.DataArray (dim0: 3)>
array([2, 1, 3])
Coordinates:
* dim0 (dim0) int32 10 11 12
发生了什么？
换句话说：
In [3]: xr_test.to_series().groupby(level=0).count()
Out[3]: dim0
10 2
11 1
12 3
dtype: int64
答案 0 :(得分：2)
这是一个错误！ Xarray目前假设（在这种情况下是错误的）假设对应于维度的坐标具有所有唯一值。这通常是一个好主意，但不应该被要求。如果你做另一个坐标，这应该可以正常工作，例如，
=== Begin generated DRL ===
package com.sample;
//generated from Decision Table
import com.sample.Screens;
// rule values at C11, header at C6
rule "Screens_11"
when
var:Screens(deliveryChannel == "Y")
usePointsAppl == "Y"
contactDetails == "Y"
riskScore == "Y"
reasonCode == 100
currentScreen == 303
then
var.setNextScreen(306);
System.out.println(var.getNextScreen());
end
// rule values at C12, header at C6
rule "Screens_12"
when
var:Screens(deliveryChannel == "Y")
usePointsAppl == "Y"
contactDetails == "Y"
riskScore == "Y"
reasonCode == 100
currentScreen == 303
then
var.setNextScreen(306);
System.out.println(var.getNextScreen());
end
=== End generated DRL ===