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/4203#issuecomment-654988562,https://api.github.com/repos/pydata/xarray/issues/4203,654988562,MDEyOklzc3VlQ29tbWVudDY1NDk4ODU2Mg==,15280721,2020-07-07T16:46:38Z,2020-07-08T04:39:21Z,NONE,"> that's only the short repr, the values are not modified:
> 
> ```python
> In [5]: da.lat
> Out[5]: 
> <xarray.DataArray 'lat' (lat: 16100)>
> array([37.49944, 37.5004 , 37.50135, ..., 43.1014 , 43.10143, 43.10144])
> Coordinates:
>   * lat      (lat) float64 37.5 37.5 37.5 37.5 37.5 ... 43.1 43.1 43.1 43.1 43.1
> ```

Thanks for help！I found `sparse` grids are not easy to plot, so I changed my code like [Colab code](https://colab.research.google.com/drive/1ehp-2t8faXzCyXJ1raTV8YHGIwYSDvek?usp=sharing), which is similar with the 'rasm' example in xr. Maybe you can show how to create this example datasets (more than the `toy weather`) in tutorial, which would be helpful.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,651101286
https://github.com/pydata/xarray/issues/4203#issuecomment-654568514,https://api.github.com/repos/pydata/xarray/issues/4203,654568514,MDEyOklzc3VlQ29tbWVudDY1NDU2ODUxNA==,15280721,2020-07-07T02:56:22Z,2020-07-07T02:56:22Z,NONE,"> thanks, that helps. First of all (unless I did something wrong with the `read_csv` call), there's a `Unnamed: 0` column that has to be removed.
> 
> Other than that, your data seems to be quite sparse so that's an ideal fit for [`sparse`](https://sparse.pydata.org):
> 
> ```python
> In [38]: %%time 
>     ...: df = pd.read_csv(""/tmp/data.csv"") 
>     ...: a = df.drop(""Unnamed: 0"", axis=1).set_index([""lat"", ""lon""]) 
>     ...: a = a.stack() 
>     ...: a.index.names = [""lat"", ""lon"", ""time""] 
>     ...: a = a.sort_index() 
>     ...: a.name = ""T"" 
>     ...: xr.DataArray.from_series(a, sparse=True) 
>     ...:  
>     ...:
> CPU times: user 606 ms, sys: 63.9 ms, total: 670 ms
> Wall time: 670 ms
> Out[38]: 
> <xarray.DataArray 'T' (lat: 16100, lon: 29959, time: 31)>
> <COO: shape=(16100, 29959, 31), dtype=float64, nnz=1003191, fill_value=nan>
> Coordinates:
>   * lat      (lat) float64 37.5 37.5 37.5 37.5 37.5 ... 43.1 43.1 43.1 43.1 43.1
>   * lon      (lon) float64 96.46 96.46 96.46 96.47 ... 102.6 102.6 102.6 102.6
>   * time     (time) object '2011-01-01 00:00:00' ... '2011-01-31 00:00:00'
> ```

Thanks for your codes!  I noticed that only two decimal numbers are kept for lat and lon. Does it mean a resample process happened? The data is a grid with 0.005 degree resolution, can I keep the resolution in the results?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,651101286
https://github.com/pydata/xarray/issues/4203#issuecomment-654182532,https://api.github.com/repos/pydata/xarray/issues/4203,654182532,MDEyOklzc3VlQ29tbWVudDY1NDE4MjUzMg==,15280721,2020-07-06T11:41:43Z,2020-07-06T11:41:43Z,NONE,"> Please could you fill out the issue template, including a reproducible example? A CSV could be OK if you include the reproduction steps.

Thank you, updated.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,651101286