New answers tagged xarray
1
I think one of the most evident advantages is indexing. Consider the following example where you have data and both longitude and latitude stored in 2D arrays:
data = np.random.randint(100, 1000, size=(4, 4))
data
[[176, 479, 713, 973],
[992, 259, 969, 355],
[182, 139, 633, 938],
[761, 911, 124, 855]]
x = np.linspace(-76, -74.5, 4)
y = np.linspace(-5.0,...
0
I ended up writing a function to parse the structured metadata attribute and add coordinates to a dataset. Here is my code to read in the dataset, create the coordinates, and apply it to the dataset:
import xarray as xr
import pyproj
import numpy as np
from collections import OrderedDict
def parse_hdfeos_metadata(string):
out = OrderedDict()
lines = [i....
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