Published
Edited
Jul 14, 2021
31 stars
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weights = weight_type==='Queen' ? geoda.getQueenWeights(data) : geoda.getRookWeights(data)
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conn = geoda.getConnectivity(weights, data)
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column_selected = geoda.getColumn(data, column)
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std_vals = standardize(column_selected)
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spatial_lags = geoda.spatialLag(weights, std_vals)
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bestFit = linearRegression(spatial_lags,std_vals)
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gmi = bestFit.slope
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lm = geoda.localMoran(weights, column_selected, permutations, 'lookup', significance_cutoff)
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Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
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