Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/process.py @ 1061:671426ce0f3e

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author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 11 Jul 2018 17:31:26 -0400
parents a87b3072bd26
children a2e20aba0740
comparison
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1060:c04550f957ab 1061:671426ce0f3e
278 278
279 if args.analyze == 'event': # aggregate event data by 15 min interval (arg.intervalDuration), count events with thresholds 279 if args.analyze == 'event': # aggregate event data by 15 min interval (arg.intervalDuration), count events with thresholds
280 data = pd.read_csv(args.eventFilename, parse_dates = [2]) 280 data = pd.read_csv(args.eventFilename, parse_dates = [2])
281 #data = pd.read_csv('./speeds.csv', converters = {'time': lambda s: datetime.datetime.strptime(s, "%H:%M:%S").time()}, nrows = 5000) 281 #data = pd.read_csv('./speeds.csv', converters = {'time': lambda s: datetime.datetime.strptime(s, "%H:%M:%S").time()}, nrows = 5000)
282 # create time for end of each 15 min, then group by, using the agg method for each data column 282 # create time for end of each 15 min, then group by, using the agg method for each data column
283 headers = ['sites', 'date', 'intervalend15', 'duration', 'count'] 283 headers = ['site', 'date', 'intervalend15', 'duration', 'count']
284 aggFunctions, tmpheaders = utils.aggregationMethods(args.aggMethods, args.aggCentiles) 284 aggFunctions, tmpheaders = utils.aggregationMethods(args.aggMethods, args.aggCentiles)
285 dataColumns = list(data.columns[4:]) 285 dataColumns = list(data.columns[4:])
286 for h in dataColumns: 286 for h in dataColumns:
287 for h2 in tmpheaders: 287 for h2 in tmpheaders:
288 headers.append(h+'-'+h2) 288 headers.append(h+'-'+h2)