在xarray中过滤数据的简便方法 [英] Concise way to filter data in xarray

问题描述

我需要对xarray数组中的值应用一个非常简单的"match语句":

I need to apply a very simple 'match statement' to the values in an xarray array:

1. 如果值> 0，则设为2
2. 如果值== 0，则设为0
3. 值是NaN时，将NaN

1. Where the value > 0, make 2
2. Where the value == 0, make 0
3. Where the value is NaN, make NaN

这是我当前的解决方案.我正在使用NaN s，.fillna和&类型强制代替2d索引.

Here's my current solution. I'm using NaNs, .fillna, & type coercion in lieu of 2d indexing.

valid = date_by_items.notnull()
positive = date_by_items > 0
positive = positive * 2
result = positive.fillna(0.).where(valid)
result

这会改变这一点:

In [20]: date_by_items = xr.DataArray(np.asarray((list(range(3)) * 10)).reshape(6,5), dims=('date','item'))
    ...: date_by_items
    ...: 
Out[20]: 
<xarray.DataArray (date: 6, item: 5)>
array([[0, 1, 2, 0, 1],
       [2, 0, 1, 2, 0],
       [1, 2, 0, 1, 2],
       [0, 1, 2, 0, 1],
       [2, 0, 1, 2, 0],
       [1, 2, 0, 1, 2]])
Coordinates:
  * date     (date) int64 0 1 2 3 4 5
  * item     (item) int64 0 1 2 3 4

...对此:

Out[22]: 
<xarray.DataArray (date: 6, item: 5)>
array([[ 0.,  2.,  2.,  0.,  2.],
       [ 2.,  0.,  2.,  2.,  0.],
       [ 2.,  2.,  0.,  2.,  2.],
       [ 0.,  2.,  2.,  0.,  2.],
       [ 2.,  0.,  2.,  2.,  0.],
       [ 2.,  2.,  0.,  2.,  2.]])
Coordinates:
  * date     (date) int64 0 1 2 3 4 5
  * item     (item) int64 0 1 2 3 4

在大熊猫中df[df>0] = 2就足够了.当然，我正在做一些行人活动，并且有一种更简洁的方式?

While in pandas df[df>0] = 2 would be enough. Surely I'm doing something pedestrian and there's an terser way?

推荐答案

xarray现在支持.where(condition, other)，因此现在有效:

xarray now supports .where(condition, other), so this is now valid:

result = date_by_items.where(date_by_items > 0, 2)

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