import matplotlib.pyplot as plt if __name__ == '__main__': result_files = dict() # collection result_files['tourspot_visitor'] = collection.crawling_tourspot_visitor( CONFIG['district'], **CONFIG['common']) result_files['foreign_visitor'] = [] for country in CONFIG['countries']: rf = collection.crawling_foreign_visitor(country, **CONFIG['common']) result_files['foreign_visitor'].append(rf) # 1. analysis & visualization result_analysis = analyze.analysis_correlation(result_files) print(result_analysis) visualize.graph_scatter(result_analysis) # 2. analysis & visualization # result_analysis = analyze.analysis_correlation_by_tourspot(result_files) # graph_table = pd.DataFrame(result_analysis, columns=['tourspot', 'r_중국', 'r_일본', 'r_미국']) # graph_table = graph_table.set_index('tourspot') # graph_table = graph_table.drop('서울시립미술관 본관') # graph_table = graph_table.drop('서대문자연사박물관') # # graph_table.plot(kind='bar', rot=60) # plt.show() # print(graph_table)
from config import CONFIG if __name__ == '__main__': resultfiles = {} resultfiles['tourspot_visitor'] = [] resultfiles['foreign_visitor'] = [] # collection returnedFilename = collect.crawling_tourspot_visitor( district=CONFIG['district'], **CONFIG['common']) resultfiles['tourspot_visitor'].append(returnedFilename) for country in CONFIG['countries']: returnedFilename = collect.crawling_foreign_visitor(country=country, **CONFIG['common']) resultfiles['foreign_visitor'].append(returnedFilename) # analysis results = analyze.analysis_correlation(resultfiles=resultfiles) # visualize for result in results: print(result) visualize.graph_scatter(results, showgraph=False) # 2. analysis & vsualization result_analysis = analyze.analysis_correlation_by_tourspot( resultfiles=resultfiles) print(result_analysis) visualize.graph_bar(result_analysis, showgraph=True)