Loading and storing data from NetCDF files

Many scientific applications require that we start with large quantities of multi-dimensional data in a robust format. NetCDF is one example of a format used for data that’s developed by the weather and climate industry. Unfortunately, the complexity of the data means that we can’t simply use the utilities from the Pandas package, for example, to load this data for analysis. We need the netcdf4 package to be able to read and import the data into Python, but we also need to use xarray. Unlike the Pandas library, xarray can handle higher-dimensional data while still providing a Pandas-like interface.

In this recipe, we will learn how to load data from and store data in NetCDF files.

Getting ready

For this recipe, we will need to import the NumPy package as np, the Pandas package as pd, the Matplotlib pyplot module as plt, and an instance of the default random number generator from NumPy:

import numpy as np
import pandas...