baseline2.py

import pandas as pd
test_0322_path = '/mnt/5/Alert_BTS_HW_0316-0322' 
test_0330_path = '/mnt/5/Alert_BTS_HW_0324-0330' 
all_test_data = pd.DataFrame()
all_test_data2 = pd.DataFrame()
for now_csv in tqdm(os.listdir(test_0322_path)):
    data = pd.read_csv(os.path.join(test_0322_path,now_csv))
    all_test_data = all_test_data.append(data)
    tmp1 = all_test_data[(all_test_data['告警名称']=='小区不可用告警')|(all_test_data['告警名称']=='网元连接中断')]
    tmp1_label1_IDs = tmp1['基站名称'].unique()
for now_csv in tqdm(os.listdir(test_0330_path)):
    data = pd.read_csv(os.path.join(test_0330_path,now_csv))
    all_test_data2 = all_test_data2.append(data)
    tmp2 = all_test_data2[(all_test_data2['告警名称']=='小区不可用告警')|(all_test_data2['告警名称']=='网元连接中断')]
    tmp2_label1_IDs = tmp2['基站名称'].unique()
sub1 = pd.read_csv('/mnt/5/提交文件样例/Sample23日.csv', encoding='gbk')
sub2 = pd.read_csv('/mnt/5/提交文件样例/Sample31日.csv', encoding='gbk')
sub1['未来24小时发生退服类告警的概率'] = sub1['基站名称'].apply(lambda x: 1 if x in tmp1_label1_IDs else 0)
sub2['未来24小时发生退服类告警的概率'] = sub2['基站名称'].apply(lambda x: 1 if x in tmp2_label1_IDs else 0)
sub1.to_csv('/root/models/results/Sample23日.csv', index=False)
sub2.to_csv('/root/models/results/Sample31日.csv', index=False)