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- Shorter repr for DataArrays with many coordinates & dims · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 165985090 | https://github.com/pydata/xarray/issues/680#issuecomment-165985090 | https://api.github.com/repos/pydata/xarray/issues/680 | MDEyOklzc3VlQ29tbWVudDE2NTk4NTA5MA== | fmaussion 10050469 | 2015-12-19T13:44:28Z | 2015-12-19T13:44:28Z | MEMBER | I wonder if there should be a repr of values at all. I actually like the way xray displays netcdf variables when they are not yet read out of the file. See:
to be compared to: ``` python netcdf = xray.open_dataset('./data/ERA-Int-MonthlyAvg-4D-UVWZ.nc') netcdf.z.copy() <xray.DataArray 'z' (month: 12, level: 15, latitude: 241, longitude: 480)> array([[[[ 1.88768500e+05, 1.88769000e+05, 1.88768500e+05, ..., 1.88769000e+05, 1.88768500e+05, 1.88769000e+05], [ 1.88901000e+05, 1.88902500e+05, 1.88903000e+05, ..., 1.88898000e+05, 1.88899000e+05, 1.88900500e+05], [ 1.89048500e+05, 1.89051000e+05, 1.89052500e+05, ..., 1.89042000e+05, 1.89044000e+05, 1.89046500e+05], ..., [ 2.01986500e+05, 2.01987500e+05, 2.01987000e+05, ..., 2.01986500e+05, 2.01986000e+05, 2.01987000e+05], [ 2.01974500e+05, 2.01975000e+05, 2.01975000e+05, ..., 2.01974500e+05, 2.01974500e+05, 2.01975000e+05], [ 2.01957500e+05, 2.01958000e+05, 2.01957500e+05, ..., 2.01958000e+05, 2.01957500e+05, 2.01958000e+05]], Coordinates: * latitude (latitude) float32 90.0 89.25 88.5 87.75 87.0 86.25 85.5 ... * level (level) int32 50 100 150 200 300 400 500 600 700 750 800 850 ... * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12 * longitude (longitude) float32 -180.0 -179.25 -178.5 -177.75 -177.0 ... Attributes: units: m2 s-2 long_name: Geopotential standard_name: geopotential number_of_significant_digits: 5 ``` |
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Shorter repr for DataArrays with many coordinates & dims 122384593 |
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