Changing dtype on v0.13.0 causes Dataset attributes to be lost

MCVE Code Sample

import numpy as np
import pandas as pd
import xarray as xr

np.random.seed(123)

times = pd.date_range("2000-01-01", "2001-12-31", name="time")
annual_cycle = np.sin(2 * np.pi * (times.dayofyear.values / 365.25 - 0.28))

base = 10 + 15 * annual_cycle.reshape(-1, 1)
tmin_values = base + 3 * np.random.randn(annual_cycle.size, 3)
tmax_values = base + 10 + 3 * np.random.randn(annual_cycle.size, 3)

ds = xr.Dataset({"tmin": (("time", "location"), tmin_values),
                 "tmax": (("time", "location"), tmax_values),},
                {"time": times, "location": ["IA", "IN", "IL"]})

# Assign an attribute
ds = ds.assign_attrs(CRS = 'EPSG:4326')

# Change dtype
ds.astype(np.float32)

Expected Output

ds to be returned with variables of dtype np.float32, with attributes (e.g. CRS = 'EPSG:4326') still included in the dataset.

Problem Description

On xarray version 0.12.1, changing the dtype of a dataset preserves any attached attributes, e.g:

<xarray.Dataset>
Dimensions:   (location: 3, time: 731)
Coordinates:
  * location  (location) <U2 'IA' 'IN' 'IL'
  * time      (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2001-12-31
Data variables:
    tmin      (time, location) float32 -8.03737 -1.7884412 ... -4.543927
    tmax      (time, location) float32 12.980549 3.3104093 ... 3.8052793
Attributes:
    CRS:      EPSG:4326

However, on xarray version 0.13.0, changing the dtype of a dataset silently drops any attached attributes, e.g:

<xarray.Dataset>
Dimensions:   (location: 3, time: 731)
Coordinates:
  * time      (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2001-12-31
  * location  (location) <U2 'IA' 'IN' 'IL'
Data variables:
    tmin      (time, location) float32 -8.03737 -1.7884412 ... -4.543927
    tmax      (time, location) float32 12.980549 3.3104093 ... 3.8052793

This causes issues with large geospatial analyses (e.g. OpenDataCube workflows), as we need to change dtype to reduce memory, but also preserve CRS information that is used for downstream tools.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.8 (default, Jan 14 2019, 11:02:34) [GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] python-bits: 64 OS: Linux OS-release: 4.14.133-113.112.amzn2.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: C.UTF-8 LANG: None LOCALE: en_US.UTF-8 libhdf5: 1.10.0 libnetcdf: 4.6.0

xarray: 0.13.0 pandas: 0.24.2 numpy: 1.16.2 scipy: 1.3.1 netCDF4: 1.3.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: 1.0.24 cfgrib: None iris: None bottleneck: None dask: 2.3.0 distributed: 2.3.2 matplotlib: 3.1.1 cartopy: 0.17.0 seaborn: None numbagg: None setuptools: 40.6.3 pip: 19.2.3 conda: None pytest: 3.5.0 IPython: 7.8.0 sphinx: None

[shoyer]

It’s also not clear to me how this managed to change/break but I think we should consider it a bug.

I agree that the right fix is to write an explicit astype method, but I don’t think there’s a good reason for keep_attrs=False in this case. astype isn’t really changing the data, just changing how the data is represented so I think it makes sense to always preserve attributes.

[mathause]

Yes, this is fixed so I am closing. Thanks for noting @rhkleijn