In [1]:
#%matplotlib inline
from pandas import Series, DataFrame
import pandas as pd
import numpy as np
import csv
import matplotlib as plt
In [2]:
c_names = ['vID', 'frID', 'tFr','Timestamp', 'localX', 'localY', 'globalX','globalY', 'vLenght', 'vWidth', 'vType',
'veloc','accel', 'line', 'pred', 'foll', 'spac', 'headway', 'dateTime']
In [3]:
data = pd.read_table('D:\\zzzLola\\PhD\\DataSet\\US101\\test\\dataset1DT.txt', sep='\t', header=None, names=c_names)
In [4]:
data[:50]
Out[4]:
vID
frID
tFr
Timestamp
localX
localY
globalX
globalY
vLenght
vWidth
vType
veloc
accel
line
pred
foll
spac
headway
dateTime
0
2
13
437
1118846980200
16.467
35.381
6451137.641
1873344.962
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
1
2
14
437
1118846980300
16.447
39.381
6451140.329
1873342.000
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
2
2
15
437
1118846980400
16.426
43.381
6451143.018
1873339.038
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
3
2
16
437
1118846980500
16.405
47.380
6451145.706
1873336.077
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
4
2
17
437
1118846980600
16.385
51.381
6451148.395
1873333.115
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
5
2
18
437
1118846980700
16.364
55.381
6451151.084
1873330.153
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
6
2
19
437
1118846980800
16.344
59.381
6451153.772
1873327.192
14.5
4.9
2
40.00
0.00
2
0
0
0
0
2005-06-15 14:49:40
7
2
20
437
1118846980900
16.323
63.379
6451156.461
1873324.230
14.5
4.9
2
40.02
0.25
2
0
0
0
0
2005-06-15 14:49:40
8
2
21
437
1118846981000
16.303
67.383
6451159.149
1873321.268
14.5
4.9
2
40.03
0.13
2
0
0
0
0
2005-06-15 14:49:41
9
2
22
437
1118846981100
16.282
71.398
6451161.838
1873318.307
14.5
4.9
2
39.93
-1.63
2
0
13
0
0
2005-06-15 14:49:41
10
2
23
437
1118846981200
16.262
75.401
6451164.546
1873315.323
14.5
4.9
2
39.61
-4.54
2
0
13
0
0
2005-06-15 14:49:41
11
2
24
437
1118846981300
16.254
79.349
6451167.199
1873312.382
14.5
4.9
2
39.14
-5.73
2
0
13
0
0
2005-06-15 14:49:41
12
2
25
437
1118846981400
16.221
83.233
6451169.802
1873309.533
14.5
4.9
2
38.61
-5.15
2
0
13
0
0
2005-06-15 14:49:41
13
2
26
437
1118846981500
16.201
87.043
6451172.358
1873306.719
14.5
4.9
2
38.28
-1.61
2
0
13
0
0
2005-06-15 14:49:41
14
2
27
437
1118846981600
16.169
90.829
6451174.961
1873303.870
14.5
4.9
2
38.42
3.73
2
0
13
0
0
2005-06-15 14:49:41
15
2
28
437
1118846981700
16.204
94.683
6451177.613
1873300.929
14.5
4.9
2
38.78
4.86
2
0
13
0
0
2005-06-15 14:49:41
16
2
29
437
1118846981800
16.252
98.611
6451180.342
1873297.924
14.5
4.9
2
38.92
0.00
2
0
13
0
0
2005-06-15 14:49:41
17
2
30
437
1118846981900
16.339
102.560
6451182.980
1873294.961
14.5
4.9
2
38.54
-8.59
2
0
13
0
0
2005-06-15 14:49:41
18
2
31
437
1118846982000
16.400
106.385
6451185.537
1873292.122
14.5
4.9
2
37.51
-11.20
2
0
13
0
0
2005-06-15 14:49:42
19
2
32
437
1118846982100
16.430
110.079
6451188.021
1873289.408
14.5
4.9
2
36.34
-10.86
2
0
13
0
0
2005-06-15 14:49:42
20
2
33
437
1118846982200
16.435
113.628
6451190.424
1873286.817
14.5
4.9
2
35.50
-6.20
2
0
13
0
0
2005-06-15 14:49:42
21
2
34
437
1118846982300
16.478
117.118
6451192.757
1873284.247
14.5
4.9
2
35.08
-1.89
2
0
13
0
0
2005-06-15 14:49:42
22
2
35
437
1118846982400
16.520
120.600
6451195.109
1873281.656
14.5
4.9
2
34.96
0.18
2
0
13
0
0
2005-06-15 14:49:42
23
2
36
437
1118846982500
16.562
124.096
6451197.462
1873279.065
14.5
4.9
2
34.98
0.25
2
0
13
0
0
2005-06-15 14:49:42
24
2
37
437
1118846982600
16.605
127.597
6451199.814
1873276.473
14.5
4.9
2
35.00
0.04
2
0
13
0
0
2005-06-15 14:49:42
25
2
38
437
1118846982700
16.647
131.099
6451202.167
1873273.882
14.5
4.9
2
34.99
-0.20
2
0
13
0
0
2005-06-15 14:49:42
26
2
39
437
1118846982800
16.691
134.595
6451204.519
1873271.290
14.5
4.9
2
34.98
-0.02
2
0
13
0
0
2005-06-15 14:49:42
27
2
40
437
1118846982900
16.727
138.081
6451206.879
1873268.700
14.5
4.9
2
35.10
1.95
2
0
13
0
0
2005-06-15 14:49:42
28
2
41
437
1118846983000
16.796
141.578
6451209.191
1873266.113
14.5
4.9
2
35.49
5.55
2
0
13
0
0
2005-06-15 14:49:43
29
2
42
437
1118846983100
16.795
145.131
6451211.610
1873263.514
14.5
4.9
2
36.20
8.99
2
0
13
0
0
2005-06-15 14:49:43
30
2
43
437
1118846983200
16.724
148.784
6451214.156
1873260.882
14.5
4.9
2
37.15
10.44
2
0
13
0
0
2005-06-15 14:49:43
31
2
44
437
1118846983300
16.588
152.559
6451216.824
1873258.213
14.5
4.9
2
38.12
9.30
2
0
13
0
0
2005-06-15 14:49:43
32
2
45
437
1118846983400
16.376
156.449
6451219.616
1873255.522
14.5
4.9
2
38.76
4.36
2
0
13
0
0
2005-06-15 14:49:43
33
2
46
437
1118846983500
16.064
160.379
6451222.548
1873252.829
14.5
4.9
2
38.95
-0.73
2
0
13
0
0
2005-06-15 14:49:43
34
2
47
437
1118846983600
15.763
164.277
6451225.462
1873250.139
14.5
4.9
2
38.95
-1.15
2
0
13
0
0
2005-06-15 14:49:43
35
2
48
437
1118846983700
15.471
168.150
6451228.376
1873247.450
14.5
4.9
2
38.99
1.90
2
0
13
0
0
2005-06-15 14:49:43
36
2
49
437
1118846983800
15.226
172.044
6451231.290
1873244.760
14.5
4.9
2
39.18
3.47
2
0
13
0
0
2005-06-15 14:49:43
37
2
50
437
1118846983900
14.979
176.000
6451234.204
1873242.071
14.5
4.9
2
39.34
0.02
2
0
13
0
0
2005-06-15 14:49:43
38
2
51
437
1118846984000
14.720
179.959
6451237.144
1873239.374
14.5
4.9
2
39.20
-3.52
2
0
13
0
0
2005-06-15 14:49:44
39
2
52
437
1118846984100
14.508
183.862
6451239.988
1873236.708
14.5
4.9
2
38.89
-3.28
2
0
13
0
0
2005-06-15 14:49:44
40
2
53
437
1118846984200
14.331
187.716
6451242.770
1873234.057
14.5
4.9
2
38.73
-0.33
2
0
13
0
0
2005-06-15 14:49:44
41
2
54
437
1118846984300
14.240
191.561
6451245.501
1873231.336
14.5
4.9
2
38.88
3.49
2
0
13
0
0
2005-06-15 14:49:44
42
2
55
437
1118846984400
14.309
195.455
6451248.125
1873228.494
14.5
4.9
2
39.28
5.00
2
0
13
0
0
2005-06-15 14:49:44
43
2
56
437
1118846984500
14.428
199.414
6451250.788
1873225.539
14.5
4.9
2
39.68
3.76
2
0
13
0
0
2005-06-15 14:49:44
44
2
57
437
1118846984600
14.540
203.417
6451253.489
1873222.554
14.5
4.9
2
39.94
1.29
2
0
13
0
0
2005-06-15 14:49:44
45
2
58
437
1118846984700
14.646
207.430
6451256.177
1873219.592
14.5
4.9
2
40.02
-0.22
2
0
13
0
0
2005-06-15 14:49:44
46
2
59
437
1118846984800
14.751
211.431
6451258.866
1873216.630
14.5
4.9
2
40.00
-0.21
2
0
13
0
0
2005-06-15 14:49:44
47
2
60
437
1118846984900
14.856
215.428
6451261.554
1873213.669
14.5
4.9
2
39.99
0.00
2
0
13
0
0
2005-06-15 14:49:44
48
2
61
437
1118846985000
14.962
219.427
6451264.243
1873210.707
14.5
4.9
2
39.99
0.00
2
0
13
0
0
2005-06-15 14:49:45
49
2
62
437
1118846985100
15.067
223.462
6451266.932
1873207.745
14.5
4.9
2
39.65
-5.35
2
0
13
0
0
2005-06-15 14:49:45
In [5]:
v_ts = DataFrame(data, columns=['vID', 'Timestamp'])
In [6]:
v_dt = DataFrame(data, columns=['vID', 'dateTime'])
In [7]:
v_ts[:10]
Out[7]:
vID
Timestamp
0
2
1118846980200
1
2
1118846980300
2
2
1118846980400
3
2
1118846980500
4
2
1118846980600
5
2
1118846980700
6
2
1118846980800
7
2
1118846980900
8
2
1118846981000
9
2
1118846981100
In [8]:
v_dt[:10]
Out[8]:
vID
dateTime
0
2
2005-06-15 14:49:40
1
2
2005-06-15 14:49:40
2
2
2005-06-15 14:49:40
3
2
2005-06-15 14:49:40
4
2
2005-06-15 14:49:40
5
2
2005-06-15 14:49:40
6
2
2005-06-15 14:49:40
7
2
2005-06-15 14:49:40
8
2
2005-06-15 14:49:41
9
2
2005-06-15 14:49:41
In [9]:
v_ts_gr = v_ts.groupby(['Timestamp']).size()
v_ts_gr
Out[9]:
Timestamp
1118846979700 1
1118846979800 1
1118846979900 1
1118846980000 1
1118846980100 1
1118846980200 2
1118846980300 2
1118846980400 2
1118846980500 2
1118846980600 2
1118846980700 2
1118846980800 2
1118846980900 2
1118846981000 2
1118846981100 3
1118846981200 3
1118846981300 3
1118846981400 3
1118846981500 3
1118846981600 3
1118846981700 3
1118846981800 4
1118846981900 4
1118846982000 4
1118846982100 5
1118846982200 5
1118846982300 5
1118846982400 5
1118846982500 5
1118846982600 6
..
1118847929600 1
1118847929700 1
1118847929800 1
1118847929900 1
1118847930000 1
1118847930100 1
1118847930200 1
1118847930300 1
1118847930400 1
1118847930500 1
1118847930600 1
1118847930700 1
1118847930800 1
1118847930900 1
1118847931000 1
1118847931100 1
1118847931200 1
1118847931300 1
1118847931400 1
1118847931500 1
1118847931600 1
1118847931700 1
1118847931800 1
1118847931900 1
1118847932000 1
1118847932100 1
1118847932200 1
1118847932300 1
1118847932400 1
1118847932500 1
dtype: int64
In [10]:
v_ts_gr.max()
Out[10]:
194
In [11]:
v_ts_gr.min()
Out[11]:
1
In [12]:
v_dt_gr = v_dt.groupby(['dateTime']).size()
v_dt_gr
Out[12]:
dateTime
2005-06-15 14:49:39 3
2005-06-15 14:49:40 18
2005-06-15 14:49:41 31
2005-06-15 14:49:42 55
2005-06-15 14:49:43 81
2005-06-15 14:49:44 118
2005-06-15 14:49:45 142
2005-06-15 14:49:46 167
2005-06-15 14:49:47 184
2005-06-15 14:49:48 210
2005-06-15 14:49:49 231
2005-06-15 14:49:50 257
2005-06-15 14:49:51 291
2005-06-15 14:49:52 326
2005-06-15 14:49:53 371
2005-06-15 14:49:54 407
2005-06-15 14:49:55 428
2005-06-15 14:49:56 466
2005-06-15 14:49:57 489
2005-06-15 14:49:58 528
2005-06-15 14:49:59 558
2005-06-15 14:50:00 580
2005-06-15 14:50:01 610
2005-06-15 14:50:02 631
2005-06-15 14:50:03 660
2005-06-15 14:50:04 687
2005-06-15 14:50:05 727
2005-06-15 14:50:06 754
2005-06-15 14:50:07 780
2005-06-15 14:50:08 820
...
2005-06-15 15:05:03 607
2005-06-15 15:05:04 594
2005-06-15 15:05:05 551
2005-06-15 15:05:06 519
2005-06-15 15:05:07 495
2005-06-15 15:05:08 475
2005-06-15 15:05:09 453
2005-06-15 15:05:10 440
2005-06-15 15:05:11 419
2005-06-15 15:05:12 392
2005-06-15 15:05:13 378
2005-06-15 15:05:14 348
2005-06-15 15:05:15 322
2005-06-15 15:05:16 290
2005-06-15 15:05:17 270
2005-06-15 15:05:18 256
2005-06-15 15:05:19 230
2005-06-15 15:05:20 214
2005-06-15 15:05:21 179
2005-06-15 15:05:22 159
2005-06-15 15:05:23 134
2005-06-15 15:05:24 117
2005-06-15 15:05:25 87
2005-06-15 15:05:26 48
2005-06-15 15:05:27 35
2005-06-15 15:05:28 19
2005-06-15 15:05:29 10
2005-06-15 15:05:30 10
2005-06-15 15:05:31 10
2005-06-15 15:05:32 6
dtype: int64
In [13]:
v_dt_gr.max()
Out[13]:
1926
In [14]:
v_dt_gr.min()
Out[14]:
3
In [15]:
data_mean = data.groupby(['vID', 'dateTime']).mean()
In [16]:
data_mean #Mean values for the data grouped by vID and dateTime
Out[16]:
frID
tFr
Timestamp
localX
localY
globalX
globalY
vLenght
vWidth
vType
veloc
accel
line
pred
foll
spac
headway
vID
dateTime
2
2005-06-15 14:49:40
16.5
437
1.118847e+12
16.395125
49.380625
6451147.05075
1873334.595875
14.5
4.9
2
40.0025
0.03125
2.0
0.0
0.0
0.000
0.000
2005-06-15 14:49:41
25.5
437
1.118847e+12
16.248700
85.049000
6451171.07880
1873308.121600
14.5
4.9
2
39.0260
-1.85300
2.0
0.0
11.7
0.000
0.000
2005-06-15 14:49:42
35.5
437
1.118847e+12
16.549500
122.327800
6451196.26890
1873280.366000
14.5
4.9
2
35.4440
-2.79500
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:43
45.5
437
1.118847e+12
16.078200
158.535100
6451221.32770
1873254.149300
14.5
4.9
2
38.1130
4.21500
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:44
55.5
437
1.118847e+12
14.532900
197.567300
6451249.44020
1873226.795300
14.5
4.9
2
39.4610
0.59800
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:45
65.5
437
1.118847e+12
15.562200
237.208600
6451276.55360
1873197.369400
14.5
4.9
2
39.8820
0.20500
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:46
75.5
437
1.118847e+12
16.657900
278.598900
6451305.62580
1873167.561400
14.5
4.9
2
43.2380
3.94300
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:47
85.5
437
1.118847e+12
16.130900
322.998400
6451337.91880
1873137.082800
14.5
4.9
2
44.8580
-0.37600
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:48
95.5
437
1.118847e+12
16.430600
367.761600
6451370.43160
1873105.807000
14.5
4.9
2
45.4040
2.91600
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:49
105.5
437
1.118847e+12
17.410300
413.588400
6451403.48850
1873073.998600
14.5
4.9
2
45.2830
-1.97200
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:50
115.5
437
1.118847e+12
18.355500
458.081900
6451435.56690
1873043.150300
14.5
4.9
2
42.8700
-4.14000
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:51
125.5
437
1.118847e+12
17.591300
499.134600
6451466.48710
1873015.865700
14.5
4.9
2
39.4340
-4.55300
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:52
135.5
437
1.118847e+12
17.668100
535.880900
6451493.86300
1872991.230200
14.5
4.9
2
35.0050
0.26700
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:53
145.5
437
1.118847e+12
18.431600
571.199700
6451519.68280
1872967.114800
14.5
4.9
2
35.5100
-0.44600
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:54
155.5
437
1.118847e+12
18.072300
607.279700
6451546.81490
1872943.332100
14.5
4.9
2
37.7340
4.91800
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:55
165.5
437
1.118847e+12
17.601300
646.529900
6451576.56980
1872917.526900
14.5
4.9
2
39.8910
0.67000
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:56
175.5
437
1.118847e+12
17.327600
687.665400
6451607.68290
1872890.569600
14.5
4.9
2
43.2090
4.44000
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:57
185.5
437
1.118847e+12
17.056600
732.249800
6451641.36670
1872861.358500
14.5
4.9
2
45.0000
0.00000
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:58
195.5
437
1.118847e+12
16.456900
777.691900
6451675.89490
1872831.836900
14.5
4.9
2
47.3600
6.27500
2.0
0.0
13.0
0.000
0.000
2005-06-15 14:49:59
205.5
437
1.118847e+12
12.999600
827.392800
6451715.50400
1872801.608200
14.5
4.9
2
49.5740
-4.00800
1.6
0.0
11.8
0.000
0.000
2005-06-15 14:50:00
215.5
437
1.118847e+12
11.227900
876.678400
6451753.67560
1872770.389600
14.5
4.9
2
50.1240
1.66300
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:01
225.5
437
1.118847e+12
11.653000
926.757400
6451791.11830
1872737.034000
14.5
4.9
2
50.0240
1.10400
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:02
235.5
437
1.118847e+12
11.286600
978.255700
6451830.21380
1872703.530700
14.5
4.9
2
53.9120
6.47400
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:03
245.5
437
1.118847e+12
10.747200
1034.549600
6451873.03330
1872666.971500
14.5
4.9
2
57.4660
0.42600
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:04
255.5
437
1.118847e+12
10.852600
1092.173700
6451916.41590
1872629.039300
14.5
4.9
2
57.2380
-3.70400
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:05
265.5
437
1.118847e+12
10.917100
1147.714700
6451958.25300
1872592.503000
14.5
4.9
2
53.3980
-5.01800
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:06
275.5
437
1.118847e+12
9.421900
1198.508000
6451997.43920
1872560.216400
14.5
4.9
2
49.1990
-1.01400
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:07
285.5
437
1.118847e+12
7.389700
1246.675700
6452035.00780
1872529.999700
14.5
4.9
2
47.2420
-0.03500
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:08
295.5
437
1.118847e+12
6.532700
1292.783100
6452070.27370
1872500.239700
14.5
4.9
2
43.4340
-4.88900
1.0
0.0
10.0
0.000
0.000
2005-06-15 14:50:09
305.5
437
1.118847e+12
7.086300
1334.235300
6452101.14070
1872472.575300
14.5
4.9
2
40.6790
-1.01400
1.0
0.0
10.0
0.000
0.000
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
3109
2005-06-15 15:01:09
6905.5
510
1.118848e+12
49.965000
888.403500
6451736.90280
1872733.552300
14.0
5.9
2
34.1310
-4.18700
5.0
2311.0
2325.0
79.454
2.330
2005-06-15 15:01:10
6915.5
510
1.118848e+12
50.097200
919.969800
6451760.75510
1872712.487300
14.0
5.9
2
29.8300
-0.09200
5.0
2311.0
2325.0
80.560
2.700
2005-06-15 15:01:11
6925.5
510
1.118848e+12
50.344900
950.634800
6451783.75870
1872692.161600
14.0
5.9
2
32.1000
2.04000
5.0
2311.0
2325.0
84.541
2.637
2005-06-15 15:01:12
6935.5
510
1.118848e+12
50.598900
983.280300
6451808.22210
1872670.559400
14.0
5.9
2
32.8670
2.62200
5.0
2311.0
2325.0
89.826
2.733
2005-06-15 15:01:13
6945.5
510
1.118848e+12
50.866000
1017.322700
6451833.69170
1872648.036800
14.0
5.9
2
35.2980
1.57400
5.0
2311.0
2325.0
95.715
2.711
2005-06-15 15:01:14
6955.5
510
1.118848e+12
52.012800
1053.410300
6451860.14870
1872623.468100
14.0
5.9
2
36.2320
-0.85000
5.0
2311.0
2325.0
103.587
2.860
2005-06-15 15:01:15
6965.5
510
1.118848e+12
52.337400
1089.725600
6451887.31780
1872599.369300
14.0
5.9
2
36.9980
2.58300
5.0
2311.0
2325.0
108.337
2.929
2005-06-15 15:01:16
6975.5
510
1.118848e+12
52.399100
1127.495900
6451915.75410
1872574.515800
14.0
5.9
2
38.2040
0.78900
5.0
2311.0
2325.0
113.285
2.966
2005-06-15 15:01:17
6985.5
510
1.118848e+12
52.437200
1166.052400
6451944.72620
1872549.200600
14.0
5.9
2
38.4870
-1.95800
5.0
2311.0
2325.0
121.125
3.149
2005-06-15 15:01:18
6995.5
510
1.118848e+12
52.392700
1203.944000
6451973.20810
1872524.315700
14.0
5.9
2
38.1670
2.93400
5.0
2311.0
2325.0
129.573
3.393
2005-06-15 15:01:19
7005.5
510
1.118848e+12
52.860400
1245.317800
6452003.99960
1872496.713200
14.0
5.9
2
45.7870
5.21900
5.0
2311.0
2325.0
136.368
2.993
2005-06-15 15:01:20
7015.5
510
1.118848e+12
53.701300
1294.186700
6452040.24830
1872463.838800
14.0
5.9
2
50.5310
1.83700
5.0
2311.0
2325.0
132.987
2.633
2005-06-15 15:01:21
7025.5
510
1.118848e+12
53.600400
1343.669900
6452077.72920
1872431.288800
14.0
5.9
2
47.7830
-2.71600
5.0
2311.0
2325.0
126.986
2.658
2005-06-15 15:01:22
7035.5
510
1.118848e+12
53.584900
1390.746500
6452113.25010
1872400.401600
14.0
5.9
2
46.1320
-1.90600
5.0
2311.0
2325.0
122.004
2.647
2005-06-15 15:01:23
7045.5
510
1.118848e+12
53.590400
1436.208900
6452147.32030
1872370.650800
14.0
5.9
2
45.6390
2.64700
5.0
2311.0
2325.0
120.312
2.637
2005-06-15 15:01:24
7055.5
510
1.118848e+12
52.816100
1483.174400
6452183.06460
1872340.252700
14.0
5.9
2
47.6030
-2.62900
5.0
2311.0
2325.0
119.083
2.502
2005-06-15 15:01:25
7065.5
510
1.118848e+12
52.487700
1528.895100
6452217.63870
1872310.283900
14.0
5.9
2
44.2770
-0.75700
5.0
2311.0
2325.0
118.737
2.680
2005-06-15 15:01:26
7075.5
510
1.118848e+12
52.267000
1573.851200
6452251.92580
1872280.674500
14.0
5.9
2
45.1190
-1.93700
5.0
2311.0
2325.0
119.006
2.640
2005-06-15 15:01:27
7085.5
510
1.118848e+12
52.124300
1617.437700
6452284.94910
1872252.238300
14.0
5.9
2
42.3440
-1.95700
5.0
2311.0
2325.0
119.345
2.820
2005-06-15 15:01:28
7095.5
510
1.118848e+12
51.994000
1659.106200
6452315.98350
1872225.315800
14.0
5.9
2
40.8850
0.53700
5.0
2311.0
2325.0
123.311
3.019
2005-06-15 15:01:29
7105.5
510
1.118848e+12
52.304800
1701.418600
6452347.14940
1872197.036700
14.0
5.9
2
44.2220
0.80600
5.0
2311.0
2325.0
131.022
2.966
2005-06-15 15:01:30
7115.5
510
1.118848e+12
53.673400
1745.842200
6452380.39550
1872166.033800
14.0
5.9
2
44.9500
2.93900
5.0
2311.0
2325.0
135.906
3.027
2005-06-15 15:01:31
7125.5
510
1.118848e+12
54.282500
1792.645900
6452415.38420
1872135.121500
14.0
5.9
2
49.1280
4.05300
5.0
2311.0
2325.0
127.182
2.594
2005-06-15 15:01:32
7135.5
510
1.118848e+12
54.286800
1842.750100
6452453.03710
1872102.392900
14.0
5.9
2
50.7730
3.94100
5.0
2311.0
2325.0
125.474
2.473
2005-06-15 15:01:33
7145.5
510
1.118848e+12
55.083200
1894.847100
6452492.21000
1872067.357800
14.0
5.9
2
51.6420
-5.40400
5.0
2311.0
2325.0
122.174
2.368
2005-06-15 15:01:34
7155.5
510
1.118848e+12
56.154300
1944.137100
6452529.27700
1872034.430900
14.0
5.9
2
48.2410
-0.58000
5.0
2311.0
2325.0
122.702
2.545
2005-06-15 15:01:35
7165.5
510
1.118848e+12
57.547400
1991.812800
6452565.62420
1872002.176900
14.0
5.9
2
47.5150
0.81000
5.0
1617.7
2325.0
87.145
1.852
2005-06-15 15:01:36
7175.5
510
1.118848e+12
57.577900
2040.323800
6452603.40940
1871971.312000
14.0
5.9
2
48.8950
-0.17300
5.0
0.0
2325.0
0.000
0.000
2005-06-15 15:01:37
7185.5
510
1.118848e+12
57.414500
2089.593400
6452642.39610
1871940.193300
14.0
5.9
2
50.0930
3.07100
5.0
0.0
2325.0
0.000
0.000
2005-06-15 15:01:38
7191.5
510
1.118848e+12
57.405000
2120.135500
6452666.26100
1871921.199500
14.0
5.9
2
51.0300
0.00000
5.0
0.0
2325.0
0.000
0.000
120032 rows × 17 columns
In [17]:
num_v = data.groupby(['vID']).size()
In [18]:
num_v #foe vID how many times it appears
Out[18]:
vID
2 437
4 351
5 452
6 357
8 448
9 409
10 436
12 443
13 432
14 515
18 291
20 414
21 439
22 441
23 438
25 436
26 438
27 432
31 465
32 438
33 383
34 451
35 280
37 408
39 450
40 391
42 389
43 458
44 379
47 428
...
3004 725
3005 726
3006 741
3007 853
3008 724
3009 732
3011 842
3014 676
3015 578
3018 714
3019 704
3021 678
3022 641
3023 403
3024 834
3025 644
3026 326
3030 667
3032 820
3033 633
3034 567
3101 255
3102 443
3103 461
3104 474
3105 534
3106 515
3107 282
3108 359
3109 510
dtype: int64
In [19]:
num_v.count() #num of different vehicles
Out[19]:
2169
In [20]:
data.describe()
Out[20]:
vID
frID
tFr
Timestamp
localX
localY
globalX
globalY
vLenght
vWidth
vType
veloc
accel
line
pred
foll
spac
headway
count
1180598.000000
1180598.000000
1180598.00000
1.180598e+06
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
1180598.000000
mean
1687.341261
4972.144159
585.54170
1.118847e+12
29.518502
983.008826
6451824.104109
1872689.857423
14.751878
6.145379
2.009898
37.496414
0.329052
2.965503
1603.584081
1610.456129
76.861747
166.340722
std
862.738747
2631.668242
160.25284
2.631668e+05
16.661830
594.629100
444.974278
395.885228
5.116659
1.027755
0.187414
14.875941
5.045285
1.468343
916.397282
916.845336
48.542040
1269.461537
min
2.000000
8.000000
177.00000
1.118847e+12
0.510000
0.000000
6451106.650000
1871874.940000
4.000000
2.000000
1.000000
0.000000
-11.200000
1.000000
0.000000
0.000000
0.000000
0.000000
25%
1023.000000
2705.000000
470.00000
1.118847e+12
17.338000
471.095500
6451438.148000
1872368.351500
12.500000
5.400000
2.000000
29.900000
-1.480000
2.000000
890.000000
898.000000
48.480000
1.490000
50%
1720.000000
5074.000000
541.00000
1.118847e+12
29.645000
932.115000
6451783.694000
1872720.025000
14.500000
6.000000
2.000000
39.250000
0.000000
3.000000
1657.000000
1662.000000
67.730000
2.020000
75%
2490.000000
7387.000000
687.00000
1.118848e+12
41.906000
1466.302250
6452185.333750
1873026.788750
16.500000
6.900000
2.000000
47.370000
2.380000
4.000000
2458.000000
2467.000000
95.780000
2.830000
max
3109.000000
9536.000000
1010.00000
1.118848e+12
73.475000
2195.462000
6452734.058000
1873372.900000
76.100000
8.500000
3.000000
95.300000
11.200000
8.000000
3109.000000
3109.000000
777.730000
9999.990000
In [21]:
v_dt.groupby(['dateTime'])
Out[21]:
<pandas.core.groupby.DataFrameGroupBy object at 0x00000000087962E8>
In [22]:
v_ts_gr.mean()
Out[22]:
123.89526707944171
In [ ]:
Content source: lalonica/PhD
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