问题
I need to apply a very simple 'match statement' to the values in an xarray array:
- Where the value > 0, make 2
- Where the value == 0, make 0
- Where the value is
NaN
, makeNaN
Here's my current solution. I'm using NaN
s, .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
This changes this:
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
... to this:
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
While in pandas df[df>0] = 2
would be enough. Surely I'm doing something pedestrian and there's an terser way?
回答1:
xarray now supports .where(condition, other)
, so this is now valid:
result = date_by_items.where(date_by_items > 0, 2)
回答2:
If you are happy to load your data in-memory as a NumPy array, you can modify the DataArray values in place with NumPy:
date_by_items.values[date_by_items.values > 0] = 2
The cleanest way to handle this would be if xarray supported the other
argument to where
, but we haven't implemented that yet (hopefully soon -- the groundwork has been laid!). When that works, you'll be able to write date_by_items.where(date_by_items > 0, 2)
.
Either way, you'll need to do this twice to apply both your criteria.
来源:https://stackoverflow.com/questions/38884283/concise-way-to-filter-data-in-xarray