python-data/exercises/ex01b_xr_label_based_indexing.ipynb

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    "# Exercise 1b: Label-based indexing"
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    "## Aim: Learn how to index data arrays"
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    "Find the teaching resources here: https://tutorial.xarray.dev/fundamentals/02.1_indexing_Basic.html."
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    "### Issues Covered: \n",
    "- Indexing, using `.loc()`, `.isel()` and `.sel()`"
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    "Q1. Open the `'../data/xbhubo.pgc0apr.nc'` dataset and load it into an xarray `Dataset` called `ds`.\n",
    "(Hint: Don't forget to import any packages you need).\n",
    "This file is a model run for HadCM3 run as part of the RAPID study: https://catalogue.ceda.ac.uk/uuid/6bbab8394124b252f8b1b036f9eb6b6b/"
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    "Q2. Select a subset of the `temperature` array using label-based indexing to get data at the position [0,0,0]."
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    "Q3. Use `.loc` to find the temperature 5 meters below the sea surface in south atlantic where latitiude is -50.625 and longitude is 0."
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    "Q4. It's not ideal to have to keep track of which dimension is in which position. Instead, use `.isel` to use the dimension names to get the data in the same place: this is depth position 0, latitude position 31 and longitude position 0."
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    "Q5. The previous method is still referring to a selection by integer position. Use `.sel` to give a labelled index with the named dimension to find the data at `time=2065-12-30`, `lat=-78.5`, `lon=11.0`."
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