issue_comments: 773214721

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https://github.com/pydata/xarray/issues/4858#issuecomment-773214721 https://api.github.com/repos/pydata/xarray/issues/4858 773214721 MDEyOklzc3VlQ29tbWVudDc3MzIxNDcyMQ== 10194086 2021-02-04T10:48:27Z 2021-02-04T10:48:27Z MEMBER

@mark-boer @dcherian @max-sixty

  1. Should we be more clever about incompatible dtypes? (numpy is not) a. By raising an error? b. By casting arr? c. Add an argument for the behavior on incompatible dtypes?
  2. If not - is the numpy error explicit enough?
  3. Should we just remove the example or should we replace it with something like arr.pad(x=1, constant_values=1.5) and mention that 1.5 is cast to 1

Currently there are 3 different behaviors, depending on constant_values

```python import xarray as xr import numpy as np arr = xr.DataArray([5, 6, 7], coords=[("x", [0, 1, 2])])

arr.pad(x=1, constant_values=np.nan)

ValueError: cannot convert float NaN to integer

arr.pad(x=1, constant_values=None)

casts arr to float

arr.pad(x=1, constant_values=1.5)

casts constant_values to int

```

https://github.com/pydata/xarray/blob/5735e163bea43ec9bc3c2e640fbf25a1d4a9d0c0/xarray/core/dataarray.py#L3883-L3892

 
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