9)ĭef HighlightFeaturesABS( demo_city, feature_name, sorted_partition, LEGEND, title = 'Socio-economic features',ĪBS stands for absolute value, while the other function HighlightFeatures is calculating ratioĬ = temp. axhline( y = 1, linewidth = 4, c = 'r', alpha =. legend( LEGEND, fontsize = 18 - feature_len / 2, loc = 2) set_xticklabels( LABEL, fontsize = 18, fontweight = "bold") title( title + ' data on each community (Partition based on ' + Title + 'days)', fontweight = "bold",Īx. legend( LABEL, fontsize = 16, loc = 2)īar_step = np. set_xticklabels( Legend, fontsize = 18 - feature_len / 2, fontweight = "bold") title( title + ' data on each community (Partition based on ' + Title + 'days)', arange( 0.0, level) - 0.5 * level + 2Ĭolor = matplotlib. Weighted_mean, weighted_std = range( level), range( level) dot( data, data) / total_popĭata = for i in data. loc + feature_name]ĭata = dataīaseline = np. Partition = sorted_partitionĭata = demo_city. True-set features as x ticks, for better features demonstrationįalse-set community as x ticks, just regularly showing numbers from demo_city Advantages of the Install Manager: Malware protection informs you if your download has installed additional unwanted software. In addition to virus scans, our editors manually check each download for you. '''date_index has the similar function here: controlling the sample base The Install Manager downloads the app quickly and securely via FilePlanet´s high-speed server, so that a trustworthy origin is ensured. set_xticklabels(,ĭef HighlightFeatures( demo_city, feature_name, sorted_partition, LEGEND, title = 'Socio-economic features', itemgetter( 1), reverse = 1)ĬlusterRanking = for i in ClusterList] subplots_adjust( hspace = 0.2, wspace = 0.1)ĬlusterList = ĬlusterList. set_xticklabels( x, fontsize = 13 - top / 4, fontweight = "bold", rotation = 30) title( LABEL + 'days', fontweight = "bold", size = 15)Īx. add_edge( e, e, weight = G]])ĭef TopZipCode( fig, rank, date_index, Color, top = 10): #produce symmetrized undirected version of a directed network Zipcode_all = list( sorted( set( dataset. read_csv( RootPath + '/USzipcode_XY.csv') ZipPath = RootPath + '/nyc-zip-code-tabulation-areas-polygons.geojson' RootPath = '/Users/CQ/Documents/Project1' From datetime import datetime, timedelta, date
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