issue_comments: 552714604
This data as json
| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/2799#issuecomment-552714604 | https://api.github.com/repos/pydata/xarray/issues/2799 | 552714604 | MDEyOklzc3VlQ29tbWVudDU1MjcxNDYwNA== | 5635139 | 2019-11-12T03:10:39Z | 2019-11-12T03:10:39Z | MEMBER | One note: if you're indexing into a dataarray and don't care about the coords, index into the variable. 2x numpy time, rather than 30x: ```python In [26]: da = xr.tutorial.open_dataset('air_temperature')['air'] In [27]: da Out[27]: <xarray.DataArray 'air' (time: 2920, lat: 25, lon: 53)> [3869000 values with dtype=float32] Coordinates: * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0 * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0 * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00 Attributes: long_name: 4xDaily Air temperature at sigma level 995 units: degK precision: 2 GRIB_id: 11 GRIB_name: TMP var_desc: Air temperature dataset: NMC Reanalysis level_desc: Surface statistic: Individual Obs parent_stat: Other actual_range: [185.16 322.1 ] In [20]: %timeit da.variable[0] 28.2 µs ± 2.29 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) In [21]: %timeit da[0] 459 µs ± 37.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) In [22]: %timeit da.variable.values[0] 14.1 µs ± 183 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) ``` |
{
"total_count": 2,
"+1": 2,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
416962458 |