def 특정사건들에_대한_상관관계_계산(news_df, tw_df, intc_li):
import Report
print('\n' + '=' * 60 + inspect.stack()[0][3])
intc_li = sorted(intc_li)
intc_li_len = len(intc_li)
i = 1
corr_dicli = []
for event_num in intc_li:
print('\n' + '-' * 60 +
'{}/{}, event_num:{}'.format(i, intc_li_len, event_num))
news_g = news_df[news_df['predicted'] == event_num].groupby(
'입력일시').count().loc[:, ['news_id']]
tw_g = tw_df[tw_df['predicted'] == event_num].groupby(
'created_at').count().loc[:, ['tw_id']]
print({'news_g_len': len(news_g)})
print({'tw_g_len': len(tw_g)})
#print(news_g)
#print(tw_g)
"""= = = = = = = = = = = = = = = 합치기 = = = = = = = = = = = = = = =
-> 시간인덱스를 변경해가며 합치기
"""
print('\n' + '= ' * 30 + '합치기')
news_data = Report.TimeResampled_data(df=news_g,
rsp_period='24H',
agg='sum')
tw_data = Report.TimeResampled_data(df=tw_g,
rsp_period='24H',
agg='sum')
corr_dic = pd_corr(news_data, tw_data)
corr_dic['event_num'] = event_num
corr_dicli.append(corr_dic)
i += 1
#break
return corr_dicli
