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  • hottwaj · 2 ✖

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  • timedelta64[D] is always coerced to timedelta64[ns] · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
264133419 https://github.com/pydata/xarray/issues/1143#issuecomment-264133419 https://api.github.com/repos/pydata/xarray/issues/1143 MDEyOklzc3VlQ29tbWVudDI2NDEzMzQxOQ== hottwaj 5629061 2016-12-01T10:15:21Z 2016-12-01T10:15:21Z NONE

The pandas docs do seem to say that conversion to timedelta64[D] (or other frequencies) is possible - see: http://pandas.pydata.org/pandas-docs/stable/timedeltas.html#frequency-conversion

Also here's a more realistic example of why this is problematic for me - I have a sequence of dates and I want to calculate the difference between them in days: possible in pandas, but not possible in xarray without first reverting to pandas/numpy types

``` dates = pandas.Series([datetime.date(2016, 01, 10), datetime.date(2016, 01, 20), datetime.date(2016, 01, 25)]).astype('datetime64[ns]')

dates.diff().astype('timedelta64[D]').astype(float)

returns

0 NaN

1 10.0

2 5.0

dtype: float6

xarray.DataArray(dates).diff(dim = 'dim_0').astype('timedelta64[D]').astype(float)

returns

<xarray.DataArray (dim_0: 2)>

array([ 8.64000000e+14, 4.32000000e+14])

Coordinates:

* dim_0 (dim_0) int64 1 2

```

Again the xarray result is in ns rather than days.

Thanks

 
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   timedelta64[D] is always coerced to timedelta64[ns] 192325490
263626446 https://github.com/pydata/xarray/issues/1143#issuecomment-263626446 https://api.github.com/repos/pydata/xarray/issues/1143 MDEyOklzc3VlQ29tbWVudDI2MzYyNjQ0Ng== hottwaj 5629061 2016-11-29T16:47:25Z 2016-11-29T16:47:25Z NONE

The conversion to timedelta64[ns] is done on this line of code: https://github.com/pydata/xarray/blob/d66f673ab25fe0fc0483bd5d67479fc94a14e46d/xarray/core/variable.py#L169

Is there a reason behind the conversion, or could it be removed?

 
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   timedelta64[D] is always coerced to timedelta64[ns] 192325490

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