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)