<jupyter_start><jupyter_text>Example - Merge<jupyter_code>import rioxarray # for the extension to load
import xarray
from rioxarray.merge import merge_arrays
# Note: You can merge datasets with the merge_datasets method

%matplotlib inline<jupyter_output><empty_output><jupyter_text>Load in xarray datasetAPI reference:- [rioxarray.open_rasterio](../rioxarray.rstrioxarray-open-rasterio)- [rioxarray.merge.merge_arrays](../rioxarray.rstrioxarray.merge.merge_arrays)- [rioxarray.merge.merge_datasets](../rioxarray.rstrioxarray.merge.merge_datasets)<jupyter_code>dem_test = "../../test/test_data/input/MODIS_ARRAY.nc"
rds = rioxarray.open_rasterio(dem_test)
arrays = [
    rds.isel(x=slice(100), y=slice(100)),
    rds.isel(x=slice(100, 200), y=slice(100, 200)),
    rds.isel(x=slice(100), y=slice(100, 200)),
    rds.isel(x=slice(100, 200), y=slice(100)),
]
merged = merge_arrays(arrays)
rds.where(rds!=rds.rio.nodata).plot();
merged.where(merged!=merged.rio.nodata).plot()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15469061876247506, 'fraction_numerical': 0.03592814371257485, 'mean_word_length': 6.775193798449612, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '551054', 'license': 'ECL-2.0', 'n_tokens_mistral': 419, 'n_tokens_neox': 376, 'n_words': 52, 'path': 'docs/examples/merge.ipynb', 'repo_name': 'mraspaud/rioxarray', 'size': '1002'}