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# <h1>xarray: Calculations</h1>
# <h3>Unidata AMS 2021 Student Conference</h3>
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# ---
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# Using [xarray](http://xarray.pydata.org/en/stable/), you can perform many of the same calculations as you would with a basic NumPy array, but with the added benefit of name-based rather than position-based dimensions/axes as well as label-based lookups. In this notebook, we'll be demonstrating several of these types of calculations (except for a specific subset of calculations, called aggregations, which combine data together using some summary statistic...these get [their own training notebook](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/analysis/xarray_aggregations.ipynb)).
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# For a full overview of xarray calculations, see [the relevant page in xarray's documentation](http://xarray.pydata.org/en/stable/computation.html).
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# <div style="float:right; width:250 px"><img src="../../instructors/images/xarray_data_access_screenshot.png" alt="HTML repr for a basic NetCDF dataset opened with xarray" style="height: 300px;"></div>
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# ### Focuses
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# - Show how ufuncs work smoothly on xarray data
# - Demonstrate pandas-like missing data calculations
# - Learn artithmetic operations take care of dimension broadcasting automatically
# - Learn how to wrap custom computations
# - Demonstrate using calculations from an external library (xskillscore, for verification statistics)
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# ### Objectives
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# 1. [...](#1.-Access-local-NetCDF-data)
# 1. [...](#2.-Access-remote-OPENDAP-data)
# 1. [...](#3.-Access-local-GRIB-data)
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# ---

# ### Imports

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import numpy as np
import xarray as xr


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# ## 1. Section 1
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# ## 2. Section 2
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# ## 3. Section 3
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# ## See also
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# There's a lot more to xarray than just calculations! Be sure to take a look at the other xarray training notebooks linked below:
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# - [Xarray data access](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/dataAccess/xarray_data_access.ipynb)
# - [Indexing with xarray](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/analysis/xarray_indexing.ipynb)
# - [Interpolation and regridding with xarray](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/analysis/xarray_interpolation.ipynb)
# - [Xarray aggregation operations](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/analysis/xarray_aggregations.ipynb)
# - [MetPy with xarray](https://nbviewer.jupyter.org/github/Unidata/pyaos-ams-2021/blob/master/notebooks/analysis/metpy_and_xarray.ipynb)
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