#collect
resultfiles['tourspot_visitor'] = collect.crawling_tourspot_visitor( #딕션에저장
district=CONFIG['district'], #config에 있는 지역
**CONFIG['common']) #커먼에 이쓴 속성을 불러옴,common= 공통적인 속성을 커먼이라는 딕셔너리로 묶음
#start_year= CONFIG ['common']['start_year'],
#end_year= CONFIG['common']['end_year'])
resultfiles['foreign_visitor'] = []
for country in CONFIG['countries']:
rf = collect.crawling_foreign_visitor(country,
**CONFIG['common']) #rf로 받음
resultfiles['foreign_visitor'].append(rf) #rf를 resultfile에 추가
# 1.analysis and visulize
#result_analysis=analyze.analysis_correlation(resultfiles)
# print(result_analysis)
#print(result_analysis)
#visualize
#visualize.graph_scatter(result_analysis)
#2.analysis and visualize, 장소별로 상관계수 구하끠
result_analysis = analyze.analysis_correlation_by_tourspot(resultfiles)
#graph_table = pd.DataFrame(result_analysis, columns=['tourspot','r_중국','r_일본','r_미국'])
#graph_table = graph_table.set_index('tourspot')
#graph_table.plot(kind='bar')
#plt.show()
#tourspot r_중국 r_일본 r_미국 중국_입국자수
#경복궁 0.2 0.3 0.5
#이런 값들을 넘겨줌니다.
resultfiles = dict()
#collect
resultfiles['tourspot_visitor'] = collection.crawling_tourspot_visitor(
district=CONFIG['district'], **CONFIG['common'])
resultfiles['foreign_visitor'] = []
for country in CONFIG['countries']:
rf = collection.crawling_foreign_visitor(country, **CONFIG['common'])
resultfiles['foreign_visitor'].append(rf)
# 1. analysis and visualize
# result_analysis = analyze.analysis_correlation(resultfiles)
# visualize.graph_scatter(result_analysis)
# 2. analysis and visualize
font_filename = 'c:/Windows/fonts/malgun.ttf'
font_name = font_manager.FontProperties(fname=font_filename).get_name()
font_options = {'family': 'Malgun Gothic'}
plt.rc('font', **font_options)
plt.rc('axes', unicode_minus=False)
result_analysis = analyze.analysis_correlation_by_tourspot(
resultfiles) # 각 관광명소와 각 나라 관광객들의 상관계수 ex)창덕궁 방문자 수와 일본 관광객의 상관계수
print(result_analysis)
graph_table = pd.DataFrame(result_analysis,
columns=['tourspot', 'r_중국', 'r_일본', 'r_미국'])
graph_table = graph_table.set_index('tourspot')
graph_table.plot(kind='bar')
plt.show()
