python-data/exercises/ex01a_xr_intro.ipynb

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    "# Exercise 1a: Introduction to xarray\n"
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   "source": [
    "## Aim: Learn about what xarray is and how to create and look at a `DataArray`."
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    "Find the teaching resources here: https://tutorial.xarray.dev/fundamentals/01_data_structures.html and https://tutorial.xarray.dev/fundamentals/01_datastructures.html."
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    "### Issues Covered:\n",
    "- Importing `xarray`\n",
    "- Loading a dataset using `xr.open_dataset()`\n",
    "- Creating a `DataArray`"
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    "## 1. Introduction to multidimensional arrays"
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    "- Unlabelled N dimensional arrays of numbers are the most widely used data structure in scientific computing\n",
    "- These arrays lack meaningful metadata so users must track indices in an arbitrary fashion"
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    "<img src=\"../images/multidimensional_array.png\" width=\"800\"/>"
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    "Q1. Can you think of any reasons why xarray might be preferred to pandas when working with multi-dimensional data like climate models?\n",
    "(Hint: how many dimensions does a pandas dataframe have?)"
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    "## 2. Opening and Exploring Datasets"
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    "Q2. 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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    "Q3. Look at the parameters of the dataset."
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    "Q4. What are the dimensions and variables in this dataset? What does each represent? "
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    "Q5. Find the name of the temperature data variable, and use it to extract a `DataArray` called `temperature`."
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    "Q6. Take a look at the `temperature` data array and inspect its dimensions, coordinates and attributes. What are the specific dimensions and coordinates associated with it? What metadata (attributes) is provided?"
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    "Q7. Find out what dimensions and coordinates exist in your dataset. Which latitude and longitude variables are associated with the ocean temperature variable?"
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