{"library":"xarray","code":"import xarray as xr\nimport numpy as np\nimport pandas as pd\n\n# Create a DataArray\ndata_array = xr.DataArray(\n    np.random.rand(2, 3),\n    coords={\"x\": [10, 20], \"y\": [\"a\", \"b\", \"c\"]},\n    dims=(\"x\", \"y\"),\n    name=\"random_data\"\n)\n\n# Create a Dataset with two DataArrays sharing coordinates\ntemp = xr.DataArray(\n    25 + 10 * np.random.randn(2, 3, 4),\n    coords={\n        \"time\": pd.to_datetime([\"2026-01-01\", \"2026-01-02\"]),\n        \"lat\": [40, 50],\n        \"lon\": [100, 110, 120, 130]\n    },\n    dims=(\"time\", \"lat\", \"lon\"),\n    name=\"temperature\",\n    attrs={\"units\": \"Celsius\", \"long_name\": \"Air Temperature\"}\n)\n\nprecip = xr.DataArray(\n    5 * np.random.rand(2, 3, 4),\n    coords=temp.coords, # Share coordinates from temp\n    dims=temp.dims,\n    name=\"precipitation\",\n    attrs={\"units\": \"mm\", \"long_name\": \"Precipitation Rate\"}\n)\n\ndataset = xr.Dataset({\"temp\": temp, \"precip\": precip})\n\n# Perform a simple operation (e.g., mean over 'time' dimension)\nmean_temp = dataset[\"temp\"].mean(dim=\"time\")\n\nprint(\"DataArray:\\n\", data_array)\nprint(\"\\nDataset:\\n\", dataset)\nprint(\"\\nMean temperature over time:\\n\", mean_temp)","lang":"python","description":"This quickstart demonstrates the creation of a basic `DataArray` and a `Dataset`, including dimension names, coordinates, and attributes. It then shows how to perform a simple aggregation (mean) on a variable within the `Dataset` along a specified dimension.","tag":null,"tag_description":null,"last_tested":"2026-04-24","results":[{"runtime":"python:3.10-alpine","exit_code":1},{"runtime":"python:3.10-slim","exit_code":1},{"runtime":"python:3.11-alpine","exit_code":1},{"runtime":"python:3.11-slim","exit_code":1},{"runtime":"python:3.12-alpine","exit_code":1},{"runtime":"python:3.12-slim","exit_code":1},{"runtime":"python:3.13-alpine","exit_code":1},{"runtime":"python:3.13-slim","exit_code":1},{"runtime":"python:3.9-alpine","exit_code":1},{"runtime":"python:3.9-slim","exit_code":1}]}