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  1. docs.xarray.dev › en › stableIndexing and selecting data - xarray

    Learn how to use Xarray's flexible indexing routines to access elements of DataArray and Dataset objects. Compare different kinds of indexing, such as positional, label, name, and vectorized, and see examples of slicing, selecting, and reindexing data.

  2. tutorial.xarray.dev › fundamentals › 02Indexing and Selecting Data - tutorial.xarray.dev

    Select data by label using .sel with values or slices. Use nearest-neighbor lookups with .sel. Select timeseries data by date/time with values or slices. Introduction # Xarray offers extremely flexible indexing routines that combine the best features of NumPy and Pandas for data selection.

  3. stackoverflow.com › questions › 70626511Xarray: slicing latitude longitude using dimension name

    7. Jan. 2022 · Is there a way I can slice the data using Xarray using a string for the coordinate indexer? For example: For example: LatIndexer, LonIndexer = 'lat', 'lon' SlicedData = data.sel(LatIndexer=slice(max_lat,min_lat), LonIndexer=slice(min_lon,max_lon))

  4. xarray-test.readthedocs.io › en › latestIndexing and selecting data — xarray 0.9.6+dev240.g5a28b89...

    Learn how to use xarray objects to access and manipulate data with different indexing methods. See examples of positional, label, name, and vectorized indexing for DataArray and Dataset objects.

  5. tutorial.xarray.dev › workshops › online-tutorial-seriesIndexing and Selecting Data - tutorial.xarray.dev

    xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. da = ds["sst"] # Extract data array da. Show code cell output. NumPy style indexing still works (but preserves the labels/metadata) da[:, 20, 40] Show code cell output.

  6. github.com › pydata › xarrayxarray/doc/user-guide/indexing.rst at main · pydata/xarray

    Quick overview. In total, xarray supports four different kinds of indexing, as described below and summarized in this table: More advanced indexing is also possible for all the methods by supplying :py ~xarray.DataArray objects as indexer. See vectorized_indexing for the details. Positional indexing.