人工智能-项目实践-智慧交通-城市交通道路流量预测.zip

# -*- coding: utf-8 -*- __Author__ = 'zhangbaojun' __Time__ = '2018/6/6 14:00' __File__ = 'data_volumn.py' import pandas as pd # time='DTCOLLECTTIME' # volumn = 'SUM(D.NVOLUME)' data = 'D:/Hisense/TrafficFlowPrediction/data/100211gaizao.csv' df1 = pd.read_csv(data, encoding='utf-8', header=None, ).fillna(0) df1.columns = ['time', 'volumn'] a = [] b=[] # print(df1['time'].values[0][0:9]) for i in range(0, len(df1)): if df1['time'].values[i][0:9] == '2018/1/20' or df1['time'].values[i][0:9] == '2018/1/21'\ or df1['time'].values[i][0:9] == '2018/1/27'or df1['time'].values[i][0:9] == '2018/1/28'\ or df1['time'].values[i][0:8] == '2018/2/3'or df1['time'].values[i][0:8] == '2018/2/4'\ or df1['time'].values[i][0:9] == '2018/2/10'or df1['time'].values[i][0:9] == '2018/2/15'\ or df1['time'].values[i][0:9] == '2018/2/16'or df1['time'].values[i][0:9] == '2018/2/17'\ or df1['time'].values[i][0:9] == '2018/2/18'or df1['time'].values[i][0:9] == '2018/2/19'\ or df1['time'].values[i][0:9] == '2018/2/20'or df1['time'].values[i][0:9] == '2018/2/21'\ or df1['time'].values[i][0:9] == '2018/2/25'\ or df1['time'].values[i][0:8] == '2018/3/3'or df1['time'].values[i][0:8] == '2018/3/4'\ or df1['time'].values[i][0:9] == '2018/3/10'or df1['time'].values[i][0:9] == '2018/3/11'\ or df1['time'].values[i][0:9] == '2018/3/17'or df1['time'].values[i][0:9] == '2018/3/18'\ or df1['time'].values[i][0:9] == '2018/3/24'or df1['time'].values[i][0:9] == '2018/3/25'\ or df1['time'].values[i][0:9] == '2018/3/31'or df1['time'].values[i][0:8] == '2018/4/1'\ or df1['time'].values[i][0:8] == '2018/4/5'or df1['time'].values[i][0:8] == '2018/4/6'\ or df1['time'].values[i][0:8] == '2018/4/7'or df1['time'].values[i][0:9] == '2018/4/14'\ or df1['time'].values[i][0:9] == '2018/4/15'or df1['time'].values[i][0:9] == '2018/4/21'\ or df1['time'].values[i][0:9] == '2018/4/22'or df1['time'].values[i][0:9] == '2018/4/29'\ or df1['time'].values[i][0:9] == '2018/4/28'or df1['time'].values[i][0:9] == '2018/4/30'\ or df1['time'].values[i][0:8] == '2018/5/1'or df1['time'].values[i][0:8] == '2018/5/5'\ or df1['time'].values[i][0:9] == '2018/5/6': a.append([df1['time'].values[i],df1['volumn'].values[i]]) zhoumo=pd.DataFrame(a) zhoumo.to_csv('100211_jiejiari.csv',index=None) for i in range(0, len(df1)): if df1['time'].values[i][0:9] != '2018/1/20' and df1['time'].values[i][0:9] != '2018/1/21'\ and df1['time'].values[i][0:9] != '2018/1/27'or df1['time'].values[i][0:9] != '2018/1/28'\ and df1['time'].values[i][0:8] != '2018/2/3'or df1['time'].values[i][0:8] != '2018/2/4'\ and df1['time'].values[i][0:9] != '2018/2/10'or df1['time'].values[i][0:9] != '2018/2/15'\ and df1['time'].values[i][0:9] != '2018/2/16'or df1['time'].values[i][0:9] != '2018/2/17'\ and df1['time'].values[i][0:9] != '2018/2/18'or df1['time'].values[i][0:9] != '2018/2/19'\ and df1['time'].values[i][0:9] != '2018/2/20'or df1['time'].values[i][0:9] != '2018/2/21'\ and df1['time'].values[i][0:9] != '2018/2/25'\ and df1['time'].values[i][0:8] != '2018/3/3'and df1['time'].values[i][0:8] != '2018/3/4'\ and df1['time'].values[i][0:9] != '2018/3/10'and df1['time'].values[i][0:9] != '2018/3/11'\ and df1['time'].values[i][0:9] != '2018/3/17'and df1['time'].values[i][0:9] != '2018/3/18'\ and df1['time'].values[i][0:9] != '2018/3/24'and df1['time'].values[i][0:9] != '2018/3/25'\ and df1['time'].values[i][0:9] != '2018/3/31'and df1['time'].values[i][0:8] != '2018/4/1'\ and df1['time'].values[i][0:8] != '2018/4/5'and df1['time'].values[i][0:8] != '2018/4/6'\ and df1['time'].values[i][0:8] != '2018/4/7'and df1['time'].values[i][0:9] != '2018/4/14'\ and df1['time'].values[i][0:9] != '2018/4/15'and df1['time'].values[i][0:9] != '2018/4/21'\ and df1['time'].values[i][0:9] != '2018/4/22'and df1['time'].values[i][0:9] != '2018/4/29'\ and df1['time'].values[i][0:9] != '2018/4/28'and df1['time'].values[i][0:9] != '2018/4/30'\ and df1['time'].values[i][0:8] != '2018/5/1'and df1['time'].values[i][0:8] != '2018/5/5'\ and df1['time'].values[i][0:9] != '2018/5/6': b.append([df1['time'].values[i],df1['volumn'].values[i]]) zhoumo=pd.DataFrame(b) zhoumo.to_csv('100211_gongzuori.csv',index=None) # print(a) # print(df1['time'].values[0])