In [11]:
import xarray as xr
import numpy as np
%matplotlib inline
In [12]:
rand = np.random.rand(10,20)
da = xr.DataArray(rand, dims=['x', 'y'])
da
Out[12]:
<xarray.DataArray (x: 10, y: 20)>
array([[6.089512e-01, 5.921867e-01, 2.887199e-01, 9.124592e-02, 9.271311e-01,
1.852007e-01, 5.549645e-01, 6.716445e-01, 9.405254e-01, 4.138753e-01,
4.651151e-01, 9.805317e-01, 1.132029e-01, 8.954666e-01, 4.230709e-01,
7.235119e-01, 7.597193e-01, 6.979327e-01, 5.570699e-02, 9.337514e-02],
[9.139808e-02, 8.131817e-01, 3.089330e-02, 5.717526e-01, 1.066662e-01,
5.657157e-01, 2.625941e-01, 9.896213e-01, 6.721665e-01, 5.564167e-01,
2.982966e-01, 1.308679e-01, 7.642018e-01, 5.684872e-01, 8.352758e-01,
3.317794e-01, 2.541880e-01, 4.921978e-03, 7.704251e-01, 3.362494e-01],
[3.111530e-01, 5.371339e-01, 8.077625e-01, 3.862287e-01, 4.009356e-01,
7.556269e-01, 9.047113e-01, 2.531478e-01, 4.379836e-01, 7.610534e-01,
6.318273e-03, 8.214699e-01, 2.902651e-01, 7.712718e-01, 8.999661e-01,
4.464614e-01, 7.098822e-02, 1.800008e-01, 5.808595e-02, 6.221029e-01],
[1.137917e-01, 9.279731e-01, 7.208999e-01, 7.674465e-01, 8.406247e-01,
8.498908e-01, 4.015754e-01, 6.817999e-01, 1.533586e-01, 9.221862e-01,
4.611826e-01, 5.863989e-01, 7.464779e-01, 1.398929e-01, 6.754868e-01,
2.731296e-02, 7.797667e-01, 1.670179e-01, 9.328458e-01, 3.503391e-01],
[8.348758e-02, 7.487514e-01, 5.056826e-02, 9.780706e-01, 6.783454e-01,
6.472068e-01, 8.483019e-01, 3.792755e-01, 7.031391e-01, 4.176098e-01,
1.328022e-01, 7.313341e-01, 1.641179e-02, 9.542104e-01, 7.993335e-01,
8.518552e-01, 7.076589e-01, 7.445155e-01, 4.720021e-01, 5.093500e-01],
[2.778791e-01, 9.808745e-02, 8.998674e-01, 2.798906e-01, 2.503440e-01,
3.451778e-01, 3.797488e-01, 6.584744e-01, 6.882464e-01, 6.176427e-01,
2.928799e-01, 7.657277e-02, 8.867912e-01, 8.939456e-01, 6.136981e-01,
4.207783e-01, 4.616000e-01, 7.854896e-01, 4.293707e-02, 9.572357e-01],
[8.406274e-02, 1.504745e-01, 6.030014e-02, 6.721167e-01, 1.835887e-01,
2.012850e-01, 7.604827e-01, 8.764416e-01, 1.732119e-01, 9.787593e-01,
4.089368e-01, 7.592372e-01, 1.652323e-01, 3.969846e-01, 4.787644e-01,
5.058492e-01, 6.943746e-01, 2.988215e-02, 8.585814e-01, 3.036220e-01],
[8.457635e-01, 2.561272e-01, 8.443130e-01, 4.350447e-01, 8.528330e-01,
1.783162e-01, 2.864370e-01, 3.807775e-01, 1.392894e-01, 4.269599e-01,
5.872172e-02, 7.361147e-02, 7.646812e-01, 5.440484e-01, 4.036109e-01,
7.461635e-01, 1.698425e-01, 1.519611e-01, 4.929727e-01, 6.600693e-01],
[3.109070e-01, 3.286642e-01, 7.161659e-01, 7.897546e-01, 4.583196e-01,
1.163877e-01, 4.411938e-01, 3.903958e-01, 3.126172e-02, 4.600458e-02,
3.738154e-01, 6.498342e-01, 8.994535e-01, 4.974055e-01, 8.896595e-01,
8.878730e-01, 3.126902e-01, 3.511536e-01, 4.980407e-01, 3.351488e-02],
[7.245638e-01, 3.379322e-01, 8.100103e-01, 3.593644e-02, 3.076934e-01,
4.975979e-01, 2.115820e-04, 8.443818e-01, 4.922226e-01, 3.827802e-01,
9.822423e-01, 4.598063e-01, 1.124241e-01, 2.174470e-01, 5.273616e-01,
7.051374e-01, 1.175613e-02, 8.015048e-01, 1.618827e-01, 3.250856e-01]])
Dimensions without coordinates: x, y
In [14]:
da.plot();
Some cool figure caption or other interpretational stuff. YEAH
In [ ]: