In [1]:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import boris
In [2]:
task_dm = boris.DataManager(root=boris.nds_root_dpath, scene_data_root=boris.nds_task_root)
In [3]:
store = pd.HDFStore(task_dm.get_gaze_data_fpath('kre', 'ordering_coffee'), mode='r')
In [4]:
task_df = store['task']
store.close()
In [5]:
task_df#.loc[:,(['left', 'right'])]
Out[5]:
both
...
left
right
quality
frame_time_diff
frame_time
frame_count
frame_num
fixation x
fixation y
fixation z
horizontal version
vertical version
...
bref x
bref y
bref z
flag
href x
href y
pupil area
bref x
bref y
bref z
rep
time
1
2343656
GOOD
-2
2343658
24071
20700
49.183333
-17.569465
144.444444
-18.675704
6.935091
...
-2.934994
-0.112528
0.925128
FIX
6326
-475
1175
3.609658
-0.113481
0.932965
2343692
GOOD
1
2343691
24072
20701
19.398982
-16.934858
104.501608
-10.383841
9.204963
...
-3.073483
-0.154095
0.950889
SACC
4261
-1144
1219
3.490141
-0.157024
0.968961
2343724
GOOD
-1
2343725
24073
20702
-10.685435
-15.527017
84.782609
7.066986
10.378095
...
-3.371336
-0.176314
0.962732
SACC
-197
-2022
1151
3.201039
-0.181635
0.991787
2343756
GOOD
-2
2343758
24074
20703
-60.341002
-34.118817
199.386503
16.609711
9.710346
...
-3.533382
-0.160233
0.936386
SACC
-3507
-2086
1052
2.991135
-0.164042
0.958642
2343792
GOOD
1
2343791
24075
20704
-25.570836
-12.420308
64.698076
21.213510
10.867054
...
-3.611441
-0.175559
0.914499
SACC
-6892
-3005
766
2.811828
-0.169694
0.883946
2343824
GOOD
0
2343824
24076
20705
-19.273144
-8.551053
48.267327
21.463640
10.046298
...
-3.615475
-0.162153
0.915290
FIX
-7466
-2763
750
2.784097
-0.154578
0.872531
2343856
GOOD
-2
2343858
24077
20706
-19.514992
-8.551488
49.974372
21.051986
9.710262
...
-3.609197
-0.157400
0.919838
FIX
-7265
-2796
737
2.793457
-0.150072
0.877011
2343892
GOOD
1
2343891
24078
20707
-18.669906
-7.796118
47.982283
21.009960
9.228720
...
-3.609113
-0.149957
0.922932
FIX
-7325
-2876
704
2.791012
-0.142167
0.874984
2343924
GOOD
0
2343924
24079
20708
-18.310899
-7.850519
47.124215
20.971051
9.458162
...
-3.608766
-0.153816
0.923307
FIX
-7354
-3038
685
2.790367
-0.145434
0.872997
2343956
GOOD
-1
2343957
24080
20709
-19.515085
-8.696046
50.283651
20.928021
9.811674
...
-3.608188
-0.159611
0.922928
FIX
-7217
-3164
649
2.797248
-0.151341
0.875109
2343992
GOOD
1
2343991
24081
20710
-17.527005
-8.508934
45.990566
20.542994
10.482037
...
-3.601854
-0.170817
0.923259
SACC
-7293
-3312
633
2.794419
-0.161340
0.872036
2344024
GOOD
0
2344024
24082
20711
-13.914720
-5.975403
35.046729
21.374648
9.675785
...
-3.615558
-0.156982
0.920723
FIX
-8194
-3182
559
2.753766
-0.145248
0.851903
2344056
GOOD
-2
2344058
24083
20712
-16.737146
-6.925280
42.483660
21.247794
9.258377
...
-3.613271
-0.150309
0.922085
FIX
-7661
-2992
565
2.776246
-0.141191
0.866148
2344092
GOOD
1
2344091
24084
20713
-21.190217
-8.503671
54.347826
21.067338
8.892826
...
-3.610213
-0.144554
0.923860
FIX
-7099
-2854
584
2.801423
-0.137758
0.880425
2344124
GOOD
0
2344124
24085
20714
-25.997757
-10.100955
67.287785
20.911134
8.537251
...
-3.607494
-0.138898
0.925272
FIX
-6701
-2699
592
2.819780
-0.133721
0.890786
2344156
GOOD
-1
2344157
24086
20715
-32.243939
-12.414707
84.415584
20.701669
8.366319
...
-3.604127
-0.136348
0.927115
FIX
-6341
-2676
592
2.837358
-0.132223
0.899067
2344192
GOOD
1
2344191
24087
20716
-36.875499
-13.610598
97.305389
20.571763
7.962590
...
-3.601872
-0.129875
0.928504
FIX
-6143
-2525
618
2.846755
-0.126532
0.904611
2344224
GOOD
0
2344224
24088
20717
-36.983098
-12.644711
98.385469
20.447135
7.323628
...
-3.599825
-0.119607
0.930632
FIX
-6086
-2369
643
2.849134
-0.116570
0.907004
2344256
GOOD
-1
2344257
24089
20718
-35.641984
-10.617315
95.307918
20.388468
6.356549
...
-3.598516
-0.103819
0.931943
FIX
-6089
-1969
697
2.847843
-0.101320
0.909514
2344292
GOOD
1
2344291
24090
20719
-36.009222
-10.041327
97.208375
20.227465
5.897561
...
-3.595837
-0.096438
0.933601
FIX
-6016
-1830
738
2.851223
-0.094197
0.911907
2344324
GOOD
-1
2344325
24091
20720
-38.770879
-11.056349
105.748373
20.034167
5.968781
...
-3.592600
-0.097700
0.934448
FIX
-5878
-1813
760
2.858274
-0.095670
0.915033
2344356
GOOD
-2
2344358
24092
20721
-46.620542
-13.875124
128.797886
19.793013
6.148641
...
-3.588502
-0.100744
0.935174
FIX
-5643
-1793
777
2.870467
-0.099134
0.920228
2344392
GOOD
1
2344391
24093
20722
-60.520578
-18.874214
170.753065
19.406736
6.307591
...
-3.582071
-0.103561
0.936907
FIX
-5344
-1800
797
2.886347
-0.102411
0.926505
2344424
GOOD
0
2344424
24094
20723
-64.968870
-19.626364
186.781609
19.081980
5.998430
...
-3.576674
-0.098684
0.939167
FIX
-5196
-1691
830
2.894094
-0.097737
0.930150
2344456
GOOD
-1
2344457
24095
20724
-70.554671
-20.784832
207.006369
18.733245
5.733665
...
-3.570900
-0.094535
0.941516
FIX
-5040
-1607
862
2.902425
-0.093755
0.933755
2344492
GOOD
1
2344491
24096
20725
-71.952987
-20.733884
215.707965
18.368042
5.490412
...
-3.564779
-0.090706
0.943677
FIX
-4912
-1496
900
2.909266
-0.090051
0.936855
2344524
GOOD
-1
2344525
24097
20726
-90.391760
-24.694061
272.346369
18.290995
5.180929
...
-3.563451
-0.085631
0.944413
FIX
-4793
-1378
926
2.915674
-0.085207
0.939733
2344556
GOOD
-2
2344558
24098
20727
-93.738338
-23.098869
284.256560
18.194828
4.645684
...
-3.561972
-0.076876
0.946038
FIX
-4746
-1281
939
2.918155
-0.076470
0.941049
2344592
GOOD
1
2344591
24099
20728
-104.476384
-25.560671
317.589577
18.154646
4.601438
...
-3.561326
-0.076167
0.946376
FIX
-4698
-1280
952
2.920837
-0.075815
0.941990
2344624
GOOD
0
2344624
24100
20729
-114.536477
-28.443486
346.975089
18.211021
4.686376
...
-3.562274
-0.077549
0.945997
FIX
-4689
-1313
954
2.921387
-0.077224
0.942035
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
2499692
GOOD
-1
2499693
28752
25381
-21.012393
-8.287486
51.972281
21.764644
9.060092
...
-3.621208
-0.146408
0.918150
SACC
-7397
-2768
368
2.787268
-0.139387
0.874123
2499724
GOOD
-2
2499726
28753
25382
-20.021667
-7.031800
50.000000
21.629868
8.005346
...
-3.618852
-0.129544
0.921132
FIX
-7413
-2438
398
2.785302
-0.123207
0.876072
2499760
GOOD
0
2499760
28754
25383
-19.243116
-6.832881
49.719531
20.978294
7.825057
...
-3.608018
-0.127126
0.925032
FIX
-7223
-2298
444
2.793600
-0.121140
0.881477
2499792
GOOD
-1
2499793
28755
25384
-16.095886
-6.351816
45.327755
19.374939
7.976962
...
-3.581455
-0.130800
0.933413
FIX
-6934
-2220
454
2.806957
-0.124542
0.888752
2499824
GOOD
-2
2499826
28756
25385
-17.238053
-6.509256
49.567870
19.024516
7.481277
...
-3.575762
-0.123011
0.936727
FIX
-6640
-2115
487
2.820809
-0.117689
0.896202
2499860
GOOD
1
2499859
28757
25386
-18.366956
-6.393783
54.560716
18.487123
6.683812
...
-3.567049
-0.110369
0.941823
FIX
-6293
-1972
518
2.837560
-0.106047
0.904937
2499892
GOOD
-1
2499893
28758
25387
-21.351943
-7.325343
64.229249
18.277984
6.506468
...
-3.563612
-0.107593
0.943384
FIX
-5961
-1938
537
2.854302
-0.104073
0.912518
2499924
GOOD
-2
2499926
28759
25388
-25.938930
-8.781466
79.656863
17.935339
6.290951
...
-3.557896
-0.104236
0.945529
SACC
-5565
-1864
567
2.874735
-0.101587
0.921499
2499960
GOOD
0
2499960
28760
25389
-12.111414
-7.469712
36.667920
17.934313
11.514312
...
-3.558213
-0.190090
0.933130
SACC
-7070
-3381
376
2.805110
-0.178557
0.876515
2499992
BAD
-1
2499993
28761
25390
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
SACC
-9404
-5860
147
2.722482
NaN
0.795453
2500028
BAD
1
2500027
28762
25391
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
BLINK
NaN
NaN
0
NaN
NaN
NaN
2500060
BAD
0
2500060
28763
25392
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
BLINK
NaN
NaN
0
NaN
NaN
NaN
2500092
BAD
-1
2500093
28764
25393
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
BLINK
NaN
NaN
0
NaN
NaN
NaN
2500124
BAD
-2
2500126
28765
25394
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
BLINK
NaN
NaN
0
NaN
NaN
NaN
2500160
BAD
1
2500159
28766
25395
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
NONE
-8509
-7488
134
2.772595
NaN
0.791060
2500192
BAD
-1
2500193
28767
25396
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
FIX
-7625
-7199
193
2.807145
NaN
0.813224
2500240
GOOD
14
2500226
28768
25397
-20.216220
-22.150505
52.278820
19.598702
22.962345
...
-3.587790
-0.370110
0.873520
SACC
-7122
-6966
230
2.827430
-0.350354
0.826894
2500260
GOOD
1
2500259
28769
25398
-20.534335
-22.266426
53.778268
19.432306
22.491577
...
-3.584993
-0.363250
0.877328
SACC
-6997
-6819
280
2.831862
-0.344393
0.831784
2500292
BAD
-1
2500293
28770
25399
-18.566935
-17.724929
44.930876
21.026915
21.528902
...
-3.613261
-0.346787
0.879070
SACC
-7825
-6911
204
2.795888
-0.321105
0.813967
2500328
GOOD
2
2500326
28771
25400
-17.521054
-18.140645
42.989418
20.581322
22.878739
...
-3.602999
-0.365482
0.866113
FIX
-7838
-6791
212
2.794262
-0.344172
0.815614
2500360
GOOD
0
2500360
28772
25401
-15.027267
-16.469601
39.828431
19.221925
22.465764
...
-3.581181
-0.362968
0.877765
SACC
-7564
-6765
249
2.805960
-0.339716
0.821536
2500396
GOOD
3
2500393
28773
25402
-33.041184
-34.549782
86.821015
19.473471
21.699717
...
-3.583331
-0.348550
0.875880
SACC
-6288
-6198
388
2.860250
-0.340551
0.855779
2500424
BAD
-2
2500426
28774
25403
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
SACC
-4874
-5750
431
2.928962
NaN
0.888891
2500460
BAD
0
2500460
28775
25404
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
SACC
-4540
-5988
465
2.948317
NaN
0.890182
2500492
BAD
-1
2500493
28776
25405
-19.208930
-28.160638
49.897646
18.534221
29.438995
...
-3.569459
-0.468332
0.829835
SACC
-7185
-8916
231
2.842723
-0.446117
0.790471
2500524
BAD
-2
2500526
28777
25406
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
FIX
-7495
-8841
240
2.828483
NaN
0.786559
2500560
BAD
1
2500559
28778
25407
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
SACC
-6100
-7991
335
2.883894
NaN
0.826610
2500592
BAD
-1
2500593
28779
25408
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
SACC
-4828
-7301
410
2.941813
NaN
0.860619
2500628
BAD
1
2500627
28780
25409
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
FIX
-4076
-6984
449
2.979613
NaN
0.877976
2500660
GOOD
0
2500660
28781
25410
-174.736446
-250.251064
587.349398
15.306611
23.077325
...
-3.515966
-0.380907
0.894004
SACC
-3753
-6976
449
2.997221
-0.376007
0.882504
4711 rows × 25 columns
In [6]:
task_df['both', 'frame_count'].plot()
Out[6]:
<matplotlib.axes._subplots.AxesSubplot at 0x114362ed0>
In [38]:
tmp = task_df.loc[(1, 1788316):(1,1878552), 'both']
In [39]:
tmp
Out[39]:
quality
frame_time_diff
frame_time
frame_count
fixation x
fixation y
fixation z
horizontal version
vertical version
vergence
rep
time
1
1788316
GOOD
-2
1788318
7411
40.221405
-37.450822
318.627451
-7.145905
6.703671
1.142843
1788320
GOOD
2
NaN
NaN
36.069196
-32.533692
290.178571
-7.041850
6.397065
1.256217
1788324
BAD
6
NaN
NaN
33.978107
-31.483281
275.423729
-6.987804
6.521092
1.323492
1788328
GOOD
10
NaN
NaN
32.089382
-30.534475
262.096774
-6.933740
6.645047
1.390755
1788332
GOOD
14
NaN
NaN
22.186753
-21.635108
194.223108
-6.477121
6.356149
1.881299
1788336
BAD
NaN
NaN
NaN
20.165590
-20.647600
179.889299
-6.354776
6.547726
2.031381
1788340
GOOD
-11
NaN
NaN
18.379503
-19.761865
167.238422
-6.228646
6.739152
2.185221
1788344
GOOD
-7
NaN
NaN
15.746549
-16.921648
149.539877
-5.973251
6.456019
2.447504
1788348
BAD
-3
NaN
NaN
15.393449
-17.032546
146.837349
-5.945074
6.616512
2.491993
1788352
GOOD
1
1788351
7412
15.107196
-17.194706
144.658754
-5.920598
6.778596
2.528895
1788356
GOOD
5
NaN
NaN
15.441199
-16.995405
147.951442
-5.919550
6.552930
2.473779
1788360
BAD
9
NaN
NaN
15.675000
-16.940798
150.000000
-5.928338
6.443604
2.440457
1788364
GOOD
13
NaN
NaN
15.940234
-16.910911
152.343750
-5.937109
6.334183
2.403360
1788368
GOOD
NaN
NaN
NaN
17.298564
-17.292910
164.695946
-5.963437
5.994036
2.224366
1788372
BAD
-12
NaN
NaN
18.005682
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170.454545
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2.149240
1788376
GOOD
-8
NaN
NaN
18.775815
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176.630435
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2.074087
1788380
GOOD
-4
1788384
7413
20.326699
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189.320388
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5.648469
1.935330
1788384
BAD
0
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NaN
20.562133
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1788388
BAD
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NaN
20.706778
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1788392
BAD
8
NaN
NaN
20.407996
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187.861272
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1788396
BAD
12
NaN
NaN
20.997549
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1788400
BAD
NaN
NaN
NaN
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1788404
BAD
-14
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NaN
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1788408
BAD
-10
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NaN
19.204018
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1788412
BAD
-6
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NaN
17.965126
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1788416
BAD
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NaN
NaN
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1788420
BAD
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NaN
NaN
18.036179
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1788424
BAD
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NaN
NaN
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1788428
BAD
10
NaN
NaN
38.673132
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280.172414
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1788432
BAD
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NaN
60.262048
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...
...
...
...
...
...
...
...
...
...
...
1878436
GOOD
NaN
NaN
NaN
19.484172
8.378753
158.279221
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1878440
GOOD
-12
NaN
NaN
19.097669
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1878444
GOOD
-8
NaN
NaN
18.727671
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2.355703
1878448
GOOD
-4
NaN
NaN
17.889863
9.954614
148.628049
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1878452
GOOD
0
1878452
10115
17.499627
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145.305514
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1878456
GOOD
4
NaN
NaN
17.373696
11.094441
145.305514
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1878460
GOOD
8
NaN
NaN
16.327598
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136.938202
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2.672038
1878464
GOOD
12
NaN
NaN
16.025862
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1878468
GOOD
NaN
NaN
NaN
15.833220
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1878472
GOOD
-14
NaN
NaN
15.699526
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132.113821
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1878476
GOOD
-10
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NaN
15.472259
13.786334
130.347594
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2.801721
1878480
GOOD
-6
NaN
NaN
15.426609
13.997144
130.697051
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2.794281
1878484
GOOD
-2
1878486
10116
14.472398
13.961188
123.730964
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2.950466
1878488
GOOD
2
NaN
NaN
14.440294
14.652393
124.521073
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2.930848
1878492
GOOD
6
NaN
NaN
14.582349
15.407071
127.952756
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2.852656
1878496
GOOD
10
NaN
NaN
14.250644
16.454018
125.482625
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2.905287
1878500
GOOD
14
NaN
NaN
14.180680
16.750029
125.160462
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2.911934
1878504
GOOD
NaN
NaN
NaN
14.091635
17.430806
124.521073
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2.924607
1878508
GOOD
-11
NaN
NaN
13.985723
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123.730964
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2.938749
1878512
GOOD
-7
NaN
NaN
14.160714
19.474296
126.623377
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2.871337
1878516
GOOD
-3
NaN
NaN
14.264842
20.716530
128.627968
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2.824097
1878520
GOOD
1
1878519
10117
14.152273
21.313943
126.623377
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2.864996
1878524
GOOD
5
NaN
NaN
14.079167
21.630329
125.000000
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2.899434
1878528
GOOD
9
NaN
NaN
14.095644
22.357394
123.106061
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2.938605
1878532
GOOD
13
NaN
NaN
14.020964
22.889293
122.027534
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2.961234
1878536
GOOD
NaN
NaN
NaN
13.845238
22.825825
119.047619
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3.032138
1878540
GOOD
-12
NaN
NaN
13.729513
23.003040
115.795724
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3.111734
1878544
GOOD
-8
NaN
NaN
13.403015
22.402186
110.921502
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3.244721
1878548
GOOD
-4
NaN
NaN
13.226243
22.540007
107.734807
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3.334522
1878552
GOOD
0
1878552
10118
13.306944
22.835850
108.333333
-6.853622
-11.903259
3.315038
22560 rows × 10 columns
In [ ]:
Content source: Berkeley-BORIS/BORIS_Code
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