Exploratory data analysis with xarray

Xarray makes working with multi-dimensional data easier, just like pandas makes working with tabular data easier. Best of all, Xarray can use Dask in the background to help you process the data quickly and efficiently.

You have been tasked with analyzing the European weather dataset further. Now that you know how to use Xarray, you will start by doing some exploratory data analysis.

xarray has been imported for you as xr.

Bu egzersiz

Parallel Programming with Dask in Python

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Using Xarray's open_zarr() function, open the "data/era_eu.zarr" dataset.
Using the DataSet's .isel() method select the zeroth index on the time coordinate.
Select the 'temp' variable from the zeroth index ds_sel and plot it on ax1.
Select the 'precip' variable from the zeroth index ds_sel and plot it on ax2.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Open the ERA5 dataset
ds = ____.____("____")

# Select the zeroth time in the DataSet
ds_sel = ds.____(____=____)

fig, (ax1, ax2) = plt.subplots(1,2, figsize=(8, 3))

# Plot the zeroth temperature field on ax1
____[____].____(ax=____)

# Plot the zeroth precipitation field on ax2
____[____].____(ax=____)
plt.show()

Kodu Düzenle ve Çalıştır