The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 20 new columns ({'relevant_positive_score', 'cautious_positive_score', 'Q_Timestamp', 'clear_negative_score', 'relevant_negative_score', 'specific_negative_score', 'assertive_neutral_score', 'cautious_negative_score', 'cautious_neutral_score', 'optimistic_negative_score', 'optimistic_positive_score', 'relevant_neutral_score', 'assertive_negative_score', 'assertive_positive_score', 'optimistic_neutral_score', 'specific_neutral_score', 'clear_positive_score', 'specific_positive_score', 'clear_neutral_score', 'A_Timestamp'}) and 10 missing columns ({'finberttone_cumulative_tone', 'timestamp_p', 'n_change_points', 'ev_expanding_min', 'section', 'finberttone_change_point', 'ev_expanding_max', 'ev_expanding_mean', 'finberttone_expected_value', 'ev_expanding_std'}).

This happened while the csv dataset builder was generating data using

hf://datasets/YYYYUN/MERIT/data/benchmark_split/train/benchmark_qa_120s.csv (at revision 670c3976d41050320c8082cd793c0633d6d02e69), [/tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_120s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_120s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_300s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_300s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_30s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_30s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_60s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_60s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_120s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_120s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_300s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_300s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_30s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_30s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_60s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_60s.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              tic: string
              year: int64
              quarter: string
              anchor_type: string
              anchor_id: int64
              post_window_sec: int64
              timestamp_anchor: double
              ec_session: string
              Q_Timestamp: double
              A_Timestamp: double
              bid_ask_spread_mean_pre: double
              bid_ask_spread_std_pre: double
              obi_mean_pre: double
              total_depth_mean_pre: double
              qrf_mean_pre: double
              quote_volatility_mean_pre: double
              n_ticks_pre: int64
              bid_ask_spread_mean_post: double
              bid_ask_spread_std_post: double
              obi_mean_post: double
              total_depth_mean_post: double
              qrf_mean_post: double
              quote_volatility_mean_post: double
              n_ticks_post: int64
              assertive_negative_score: double
              assertive_neutral_score: double
              assertive_positive_score: double
              cautious_negative_score: double
              cautious_neutral_score: double
              cautious_positive_score: double
              optimistic_negative_score: double
              optimistic_neutral_score: double
              optimistic_positive_score: double
              specific_negative_score: double
              specific_neutral_score: double
              specific_positive_score: double
              clear_negative_score: double
              clear_neutral_score: double
              clear_positive_score: double
              relevant_negative_score: double
              relevant_neutral_score: double
              relevant_positive_score: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 6005
              to
              {'tic': Value('string'), 'year': Value('int64'), 'quarter': Value('string'), 'anchor_type': Value('string'), 'anchor_id': Value('int64'), 'post_window_sec': Value('int64'), 'timestamp_anchor': Value('float64'), 'ec_session': Value('string'), 'timestamp_p': Value('float64'), 'section': Value('string'), 'bid_ask_spread_mean_pre': Value('float64'), 'bid_ask_spread_std_pre': Value('float64'), 'obi_mean_pre': Value('float64'), 'total_depth_mean_pre': Value('float64'), 'qrf_mean_pre': Value('float64'), 'quote_volatility_mean_pre': Value('float64'), 'n_ticks_pre': Value('int64'), 'bid_ask_spread_mean_post': Value('float64'), 'bid_ask_spread_std_post': Value('float64'), 'obi_mean_post': Value('float64'), 'total_depth_mean_post': Value('float64'), 'qrf_mean_post': Value('float64'), 'quote_volatility_mean_post': Value('float64'), 'n_ticks_post': Value('int64'), 'finberttone_expected_value': Value('float64'), 'finberttone_cumulative_tone': Value('float64'), 'finberttone_change_point': Value('float64'), 'ev_expanding_mean': Value('float64'), 'ev_expanding_std': Value('float64'), 'ev_expanding_max': Value('float64'), 'ev_expanding_min': Value('float64'), 'n_change_points': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 20 new columns ({'relevant_positive_score', 'cautious_positive_score', 'Q_Timestamp', 'clear_negative_score', 'relevant_negative_score', 'specific_negative_score', 'assertive_neutral_score', 'cautious_negative_score', 'cautious_neutral_score', 'optimistic_negative_score', 'optimistic_positive_score', 'relevant_neutral_score', 'assertive_negative_score', 'assertive_positive_score', 'optimistic_neutral_score', 'specific_neutral_score', 'clear_positive_score', 'specific_positive_score', 'clear_neutral_score', 'A_Timestamp'}) and 10 missing columns ({'finberttone_cumulative_tone', 'timestamp_p', 'n_change_points', 'ev_expanding_min', 'section', 'finberttone_change_point', 'ev_expanding_max', 'ev_expanding_mean', 'finberttone_expected_value', 'ev_expanding_std'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/YYYYUN/MERIT/data/benchmark_split/train/benchmark_qa_120s.csv (at revision 670c3976d41050320c8082cd793c0633d6d02e69), [/tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_120s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_120s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_300s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_300s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_30s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_30s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_60s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_pre_60s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_120s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_120s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_300s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_300s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_30s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_30s.csv), /tmp/hf-datasets-cache/medium/datasets/68663999050392-config-parquet-and-info-YYYYUN-MERIT-694f95f4/hub/datasets--YYYYUN--MERIT/snapshots/670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_60s.csv (origin=hf://datasets/YYYYUN/MERIT@670c3976d41050320c8082cd793c0633d6d02e69/data/benchmark_split/train/benchmark_qa_60s.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

tic
string
year
int64
quarter
string
anchor_type
string
anchor_id
int64
post_window_sec
int64
timestamp_anchor
float64
ec_session
string
timestamp_p
float64
section
string
bid_ask_spread_mean_pre
float64
bid_ask_spread_std_pre
float64
obi_mean_pre
float64
total_depth_mean_pre
float64
qrf_mean_pre
float64
quote_volatility_mean_pre
float64
n_ticks_pre
int64
bid_ask_spread_mean_post
float64
bid_ask_spread_std_post
float64
obi_mean_post
float64
total_depth_mean_post
float64
qrf_mean_post
float64
quote_volatility_mean_post
float64
n_ticks_post
int64
finberttone_expected_value
float64
finberttone_cumulative_tone
float64
finberttone_change_point
float64
ev_expanding_mean
float64
ev_expanding_std
float64
ev_expanding_max
float64
ev_expanding_min
float64
n_change_points
float64
AAPL
2,021
Q1
pre
1
120
21.87
after_hours
21.87
Pre
0.000669
0.000555
-0.216496
1,029.545455
120.954545
10.263113
44
0.000748
0.001032
-0.324268
2,317.307692
123.823077
0.067883
260
0.159266
0.159266
0
0.159266
0
0.159266
0.159266
0
AAPL
2,021
Q1
pre
2
120
24.373
after_hours
24.373
Pre
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0.000573
-0.21407
1,022.916667
120.4375
8.475715
48
0.000747
0.001037
-0.326043
2,330.859375
123.910156
0.068327
256
0.551028
0.710294
0
0.355147
0.277017
0.551028
0.159266
0
AAPL
2,021
Q1
pre
3
120
30.376
after_hours
30.376
Pre
0.000715
0.000613
-0.193544
1,128
118
0.049408
50
0.000734
0.001031
-0.315491
2,276.470588
123.894118
0.069966
255
-0.000003
0.710291
0
0.236764
0.283572
0.551028
-0.000003
0
AAPL
2,021
Q1
pre
4
120
33.881
after_hours
33.881
Pre
0.000672
0.000623
-0.188913
1,102.040816
118
0.049408
49
0.000714
0.001005
-0.291422
2,157.564576
123.476015
0.07155
271
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0.177557
0.260059
0.551028
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0
AAPL
2,021
Q1
pre
5
120
58.803
after_hours
58.803
Pre
0.000483
0.00052
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2,620.833333
118
0.049408
72
0.00092
0.001322
-0.182694
2,095.528455
123.869919
0.080288
246
-0.001054
0.709174
0
0.141835
0.238963
0.551028
-0.001054
0
AAPL
2,021
Q1
pre
6
120
66.166
after_hours
66.166
Pre
0.000538
0.000557
-0.582051
2,700
119.333333
0.051945
54
0.000965
0.00137
-0.193084
2,037.647059
128.921569
0.828822
255
-0.126273
0.582901
0
0.09715
0.240131
0.551028
-0.126273
0
AAPL
2,021
Q1
pre
7
120
80.132
after_hours
80.132
Pre
0.0007
0.000779
-0.27337
2,046.296296
125.111111
0.062938
54
0.001043
0.001504
-0.190184
2,444.912281
146.522807
3.428922
285
-0.004192
0.578709
0
0.082673
0.22253
0.551028
-0.126273
0
AAPL
2,021
Q1
pre
8
120
88.496
after_hours
88.496
Pre
0.000693
0.000723
-0.229088
4,724.137931
129.793103
0.071846
58
0.001126
0.001474
-0.096247
2,266.881029
159.736334
5.384751
311
-0.000161
0.578548
0
0.072319
0.208094
0.551028
-0.126273
0
AAPL
2,021
Q1
pre
9
120
92.131
after_hours
92.131
Pre
0.000693
0.000719
-0.169838
4,557.627119
130
0.072239
59
0.001188
0.001543
-0.086382
2,265.299685
161.981073
5.714418
317
-0.000788
0.577761
0
0.064196
0.196173
0.551028
-0.126273
0
AAPL
2,021
Q1
pre
10
120
93.752
after_hours
93.752
Pre
0.000726
0.000741
-0.166301
4,411.47541
130
0.072239
61
0.001226
0.001603
-0.087666
2,260.436137
163.523364
5.941512
321
0.060903
0.638664
0
0.063866
0.184957
0.551028
-0.126273
0
AAPL
2,021
Q1
pre
11
120
95.134
after_hours
95.134
Pre
0.000729
0.000747
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4,473.333333
130
0.072239
60
0.00123
0.001589
-0.087105
2,243.425076
164.541284
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327
0.238992
0.877656
0
0.079787
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0.551028
-0.126273
0
AAPL
2,021
Q1
pre
12
120
96.876
after_hours
96.876
Pre
0.000763
0.000759
-0.187223
4,377.419355
130
0.072239
62
0.001244
0.001587
-0.070045
2,246.341463
166.064024
6.315203
328
0.947094
1.824749
0
0.152062
0.305301
0.947094
-0.126273
0
AAPL
2,021
Q1
pre
13
120
105.404
after_hours
105.404
Pre
0.000698
0.000492
-0.298468
4,619.298246
130
0.072239
57
0.001243
0.001574
-0.038478
2,319.701493
170.889552
7.03967
335
1
2.824749
0
0.217288
0.375165
1
-0.126273
0
AAPL
2,021
Q1
pre
14
120
110.53
after_hours
110.53
Pre
0.000704
0.000468
-0.250584
4,321.875
130
0.072239
64
0.001351
0.001827
-0.046322
2,553.239437
176.859155
7.914894
355
-0.000001
2.824748
0
0.201768
0.365096
1
-0.126273
0
AAPL
2,021
Q1
pre
15
120
112.291
after_hours
112.291
Pre
0.000743
0.000489
-0.258897
3,965.277778
130
0.072239
72
0.001375
0.001853
-0.03456
2,591.117479
178.174785
8.127879
349
-0.000331
2.824417
0
0.188294
0.355664
1
-0.126273
0
AAPL
2,021
Q1
pre
16
120
116.127
after_hours
116.127
Pre
0.000799
0.0006
-0.131084
2,025
130
0.072239
60
0.001467
0.002109
-0.029672
2,642.857143
180.574344
8.507359
343
-0.000046
2.824371
0
0.176523
0.346815
1
-0.126273
0
AAPL
2,021
Q1
pre
17
120
120.771
after_hours
120.771
Pre
0.000895
0.001094
-0.182744
917.333333
129.653333
0.072694
75
0.001522
0.002205
-0.011541
2,729.94012
183.88024
9.020376
334
0.999775
3.824146
0
0.22495
0.390679
1
-0.126273
0
AAPL
2,021
Q1
pre
18
120
122.533
after_hours
122.533
Pre
0.00091
0.001123
-0.197364
942.647059
129.617647
0.072741
68
0.001522
0.002205
-0.011541
2,729.94012
183.88024
9.020376
334
-0.00001
3.824136
0
0.212452
0.382705
1
-0.126273
0
AAPL
2,021
Q1
pre
19
120
128.859
after_hours
128.859
Pre
0.001023
0.001454
-0.200223
889.855072
127.927536
0.07496
69
0.001524
0.002179
-0.005903
2,992.46988
184.198795
9.075331
332
-0.000006
3.82413
0
0.20127
0.375103
1
-0.126273
0
AAPL
2,021
Q1
pre
20
120
132.923
after_hours
132.923
Pre
0.000974
0.001421
-0.210093
925.352113
127.070423
0.076086
71
0.001532
0.00217
-0.019074
4,142.51497
183.712575
9.022669
334
-0.000009
3.824121
0
0.191206
0.367862
1
-0.126273
0
AAPL
2,021
Q1
pre
21
120
137.127
after_hours
137.127
Pre
0.000965
0.001425
-0.278798
1,056.338028
125.422535
0.078249
71
0.00156
0.002149
-0.020733
4,948.672566
182.563422
8.893168
339
-0.002103
3.822018
0
0.182001
0.361021
1
-0.126273
0
AAPL
2,021
Q1
pre
22
120
145.032
after_hours
145.032
Pre
0.000967
0.001748
-0.329771
1,012.5
120.453125
0.084774
64
0.00162
0.002141
-0.013035
5,089.602446
184.847095
9.217919
327
-0.000002
3.822016
0
0.173728
0.35445
1
-0.126273
0
AAPL
2,021
Q1
pre
23
120
152.157
after_hours
152.157
Pre
0.000815
0.001468
-0.28732
980
117
0.089308
60
0.001747
0.002364
-0.035232
6,467.477204
184.227964
9.165253
329
0.034132
3.856148
0
0.167659
0.347522
1
-0.126273
0
AAPL
2,021
Q1
pre
24
120
161.084
after_hours
161.084
Pre
0.000556
0.000976
-0.109096
891.044776
117
0.089308
67
0.001823
0.002354
-0.057459
6,504.587156
184.431193
9.223607
327
-0
3.856148
0
0.160673
0.341602
1
-0.126273
0
AAPL
2,021
Q1
pre
25
120
164.708
after_hours
164.708
Pre
0.000763
0.001374
-0.077194
839.130435
117
0.089308
69
0.001829
0.002388
-0.062874
6,450.909091
183.684848
9.142392
330
0.000255
3.856403
0
0.154256
0.335945
1
-0.126273
0
AAPL
2,021
Q1
pre
26
120
173.638
after_hours
173.638
Pre
0.000978
0.001491
-0.106361
1,975
117
0.089308
60
0.00185
0.002396
-0.040879
6,418.238994
186.125786
9.48505
318
0.000067
3.85647
0
0.148326
0.330544
1
-0.126273
0
AAPL
2,021
Q1
pre
27
120
177.302
after_hours
177.302
Pre
0.001039
0.001561
-0.081198
2,107.407407
117
0.089308
54
0.001906
0.002456
-0.032653
6,225.297619
182.208333
8.984638
336
0.997451
4.85392
0
0.179775
0.362989
1
-0.126273
0
AAPL
2,021
Q1
pre
28
120
179.044
after_hours
179.044
Pre
0.001238
0.001734
-0.0572
2,028.813559
117
0.089308
59
0.001903
0.002451
-0.0295
6,330.81571
183.145015
9.119669
331
-0.054131
4.799789
0
0.171421
0.358936
1
-0.126273
0
AAPL
2,021
Q1
pre
29
120
201.4
after_hours
201.4
Pre
0.001412
0.001833
-0.133283
3,014.285714
203.214286
11.60221
84
0.002062
0.002483
-0.019236
7,150.162866
163.351792
9.599231
307
0.003609
4.803398
0
0.165634
0.353843
1
-0.126273
0
AAPL
2,021
Q1
pre
30
120
203.681
after_hours
203.681
Pre
0.001352
0.001724
-0.08201
3,627.55102
208.591837
12.320319
98
0.002124
0.002527
-0.02166
7,115.410959
159.732877
9.428389
292
-0.000008
4.80339
0
0.160113
0.349002
1
-0.126273
0
AAPL
2,021
Q1
pre
31
120
209.306
after_hours
209.306
Pre
0.001343
0.001491
0.021907
3,766.393443
218.163934
13.59856
122
0.002208
0.002648
-0.064979
7,547.126437
151.842912
8.96495
261
0.000122
4.803512
0
0.154952
0.344337
1
-0.126273
0
AAPL
2,021
Q1
pre
32
120
211.227
after_hours
211.227
Pre
0.001477
0.001658
0.06523
3,770.16129
219
13.710206
124
0.002174
0.002646
-0.07962
7,713.385827
149.992126
8.834175
254
-0.000077
4.803435
0
0.150107
0.339844
1
-0.126273
0
AAPL
2,021
Q1
pre
33
120
222.376
after_hours
222.376
Pre
0.001538
0.001392
0.141589
3,231.632653
219
13.710206
98
0.002229
0.002748
-0.108358
8,509.333333
139.124444
8.310408
225
0.00013
4.803565
0
0.145563
0.335509
1
-0.126273
0
AAPL
2,021
Q1
pre
34
120
231.948
after_hours
231.948
Pre
0.001785
0.002042
0.174084
3,671.755725
219
13.710206
131
0.002376
0.002806
-0.223022
8,943.171806
116.845815
9.577363
227
0.000534
4.804099
0
0.141297
0.331322
1
-0.126273
0
AAPL
2,021
Q1
pre
35
120
242.635
after_hours
242.635
Pre
0.002268
0.003237
0.115728
2,971.264368
219
13.710206
87
0.002215
0.002458
-0.247618
9,005.829596
110.139013
9.566101
223
0.697773
5.501871
0
0.157196
0.339695
1
-0.126273
0
AAPL
2,021
Q1
pre
36
120
243.916
after_hours
243.916
Pre
0.002192
0.003219
0.123196
3,979.518072
215.168675
13.219862
83
0.002263
0.002534
-0.240315
8,643.946188
109.479821
9.56561
223
-0.000282
5.50159
0
0.152822
0.335835
1
-0.126273
0
AAPL
2,021
Q1
pre
37
120
245.376
after_hours
245.376
Pre
0.002245
0.003276
0.106588
4,086.25
212.375
12.86232
80
0.002256
0.00254
-0.240366
8,685.585586
109.243243
9.607885
222
-0.000033
5.501557
0
0.148691
0.332089
1
-0.126273
0
AAPL
2,021
Q1
pre
38
120
266.275
after_hours
266.275
Pre
0.001974
0.002002
-0.307733
18,618.181818
127.454545
1.993954
44
0.002293
0.00265
-0.197678
5,756.018519
103.013889
9.866204
216
1
6.501557
1
0.171094
0.355492
1
-0.126273
1
AAPL
2,021
Q1
pre
39
120
271.139
after_hours
271.139
Pre
0.002165
0.00267
-0.441572
22,876.923077
113
0.144019
52
0.002202
0.002395
-0.153736
4,190.821256
101.396135
10.288025
207
1
7.501557
0
0.192348
0.375055
1
-0.126273
1
AAPL
2,021
Q1
pre
40
120
281.287
after_hours
281.287
Pre
0.002001
0.002468
-0.390441
17,749.206349
113
0.144019
63
0.002272
0.002495
-0.141046
4,130.481283
100.15508
11.372946
187
1
8.501557
0
0.212539
0.391621
1
-0.126273
1
AAPL
2,021
Q1
pre
41
120
288.713
after_hours
288.713
Pre
0.002276
0.002968
-0.273973
9,056.363636
113
0.144019
55
0.00217
0.002395
-0.141817
4,145.744681
97.095745
11.310886
188
-0.948634
7.552923
0
0.184218
0.427105
1
-0.948634
1
AAPL
2,021
Q1
pre
42
120
304.674
after_hours
304.674
Pre
0.002306
0.002528
0.090997
1,779.245283
112.716981
1.245275
53
0.001998
0.002287
-0.248943
4,207.100592
91.337278
12.217943
169
0.258038
7.81096
0
0.185975
0.422018
1
-0.948634
1
AAPL
2,021
Q1
pre
43
120
328.626
after_hours
328.626
Pre
0.002072
0.00184
-0.108487
6,608
108.2
18.821329
50
0.001893
0.002311
-0.239705
2,478.362573
94.005848
6.970727
171
-0.977201
6.83376
0
0.158925
0.453126
1
-0.977201
1
AAPL
2,021
Q1
pre
44
120
341.271
after_hours
341.271
Pre
0.001738
0.001904
-0.515936
8,105.555556
108
19.59955
36
0.001985
0.002355
-0.191721
2,241.798942
96.386243
5.914684
189
0.999726
7.833486
0
0.178034
0.46542
1
-0.977201
1
AAPL
2,021
Q1
pre
45
120
344.693
after_hours
344.693
Pre
0.001476
0.001895
-0.481471
8,065.625
108
19.59955
32
0.00201
0.002293
-0.161538
2,032.085561
96.695187
4.834389
187
-0.000033
7.833453
0
0.174077
0.460866
1
-0.977201
1
AAPL
2,021
Q1
pre
46
120
358.027
after_hours
358.027
Pre
0.002537
0.002893
-0.388484
5,524.561404
108
19.59955
57
0.002023
0.00214
-0.02681
805
98.005556
0.486986
180
1
8.833453
0
0.192032
0.471706
1
-0.977201
1
AAPL
2,021
Q1
pre
47
120
371.238
after_hours
371.238
Pre
0.00255
0.00302
-0.396631
4,445.833333
98.222222
15.267982
72
0.002001
0.002016
0.036024
787.292818
100.027624
0.167544
181
1
9.833453
0
0.209222
0.481206
1
-0.977201
1
AAPL
2,021
Q1
pre
48
120
387.992
after_hours
387.992
Pre
0.001937
0.002353
-0.096908
1,200
67.473684
1.64634
38
0.002113
0.002143
0.025275
748.63388
101.928962
0.171828
183
1
10.833453
0
0.225697
0.489551
1
-0.977201
1
AAPL
2,021
Q1
pre
49
120
400.179
after_hours
400.179
Pre
0.001451
0.00081
0.204207
1,556.521739
64
0.107493
23
0.002023
0.002149
0.009677
938.423645
100.458128
0.170367
203
1
11.833452
0
0.241499
0.496893
1
-0.977201
1
AAPL
2,021
Q1
pre
50
120
411.873
after_hours
411.873
Pre
0.001173
0.000756
-0.01528
1,632
64
0.107493
25
0.002138
0.00223
0.029206
919.170984
103.072539
0.175186
193
0.00002
11.833472
0
0.236669
0.492981
1
-0.977201
1
AAPL
2,021
Q1
pre
51
120
415.917
after_hours
415.917
Pre
0.001085
0.000656
-0.173628
1,253.125
64
0.107493
32
0.002175
0.002265
0.060818
917.204301
104.758065
0.178197
186
1
12.833472
0
0.251637
0.499594
1
-0.977201
1
AAPL
2,021
Q1
pre
52
120
427.528
after_hours
427.528
Pre
0.000908
0.000322
-0.220285
990
71.066667
0.119095
30
0.002138
0.002279
0.089159
956.565657
102.818182
0.175575
198
0.996438
13.829909
0
0.26596
0.50534
1
-0.977201
1
AAPL
2,021
Q1
pre
53
120
439.706
after_hours
439.706
Pre
0.001435
0.001625
-0.283124
710.416667
101.541667
0.169127
48
0.002163
0.00232
0.143345
976.06383
98.234043
0.168687
188
0.000958
13.830868
0
0.26096
0.501779
1
-0.977201
1
AAPL
2,021
Q1
pre
54
120
456.281
after_hours
456.281
Pre
0.001986
0.002181
-0.090171
657.142857
117
0.194506
56
0.002
0.002188
0.079357
942.512077
92.652174
0.159838
207
1
14.830867
0
0.274646
0.507096
1
-0.977201
1
AAPL
2,021
Q1
pre
55
120
467.097
after_hours
467.097
Pre
0.00235
0.002369
0.054549
591.22807
117
0.194506
57
0.00191
0.002157
0.037504
1,004.040404
88.818182
0.154074
198
1
15.830867
0
0.287834
0.511811
1
-0.977201
1
AAPL
2,021
Q1
pre
56
120
470.127
after_hours
470.127
Pre
0.00237
0.002152
0.143021
602.083333
117
0.194506
48
0.00191
0.002162
0.033319
994.416244
88.675127
0.153869
197
-0.003514
15.827354
1
0.282631
0.508629
1
-0.977201
2
AAPL
2,021
Q1
pre
57
120
471.528
after_hours
471.528
Pre
0.002587
0.002125
0.222582
595.454545
117
0.194506
44
0.001917
0.002172
0.032635
1,000
88.384615
0.153452
195
-0.00107
15.826284
0
0.277654
0.505466
1
-0.977201
2
AAPL
2,021
Q1
pre
58
120
481.57
after_hours
481.57
Pre
0.002534
0.002178
0.208497
571.014493
115.565217
0.192595
69
0.001705
0.00205
-0.008301
1,085.802469
82.5
0.144879
162
0.292653
16.118937
0
0.277913
0.501016
1
-0.977201
2
AAPL
2,021
Q1
pre
59
120
482.631
after_hours
482.631
Pre
0.002526
0.002181
0.210913
563.768116
115.086957
0.191958
69
0.001706
0.002056
-0.006282
1,090.68323
82.490683
0.144844
161
-0.000302
16.118635
0
0.273197
0.497997
1
-0.977201
2
AAPL
2,021
Q1
pre
60
120
484.351
after_hours
484.351
Pre
0.002635
0.002323
0.216487
546.052632
111.789474
0.187564
76
0.001608
0.001926
-0.024005
1,110.897436
82.884615
0.146165
156
0.995969
17.114604
0
0.285243
0.502498
1
-0.977201
2
AAPL
2,021
Q1
pre
61
120
486.372
after_hours
486.372
Pre
0.002584
0.002304
0.210684
566.216216
110.756757
0.186189
74
0.001591
0.001911
-0.02882
1,087.421384
83.628931
0.148706
159
0.000455
17.115059
0
0.280575
0.499626
1
-0.977201
2
AAPL
2,021
Q1
pre
62
120
503.103
after_hours
503.103
Pre
0.002711
0.002509
0.164064
740.298507
99.268657
0.170884
67
0.001673
0.002133
-0.068895
984.180791
88.864407
0.166559
177
-0.000054
17.115005
0
0.276048
0.496793
1
-0.977201
2
AAPL
2,021
Q1
pre
63
120
507.445
after_hours
507.445
Pre
0.002609
0.002489
0.162115
809.259259
94.388889
0.164382
54
0.001712
0.002183
-0.078928
971.195652
89.679348
0.169349
184
-0.000025
17.11498
0
0.271666
0.493997
1
-0.977201
2
AAPL
2,021
Q1
pre
64
120
510.607
after_hours
510.607
Pre
0.002396
0.002603
0.139163
829.545455
84
0.150542
44
0.00168
0.002134
-0.102681
1,002.840909
90.198864
0.171092
176
0.000567
17.115547
0
0.26743
0.491231
1
-0.977201
2
AAPL
2,021
Q1
pre
65
120
518.97
after_hours
518.97
Pre
0.001877
0.002286
-0.008224
1,904.651163
84
0.150542
43
0.001876
0.002441
-0.076986
839.153439
92.571429
0.179191
189
0.538896
17.654443
0
0.271607
0.48854
1
-0.977201
2
AAPL
2,021
Q1
pre
66
120
521.311
after_hours
521.311
Pre
0.001907
0.002331
0.017022
1,739.215686
84
0.150542
51
0.001855
0.002412
-0.100607
851.612903
93.575269
0.182596
186
-0.000011
17.654432
0
0.267491
0.485919
1
-0.977201
2
AAPL
2,021
Q1
pre
67
120
529.957
after_hours
529.957
Pre
0.001527
0.002081
0.04373
2,000
84
0.150542
34
0.00192
0.002538
-0.10086
844.270833
93.994792
0.184037
192
-0.017257
17.637175
0
0.263241
0.483477
1
-0.977201
2
AAPL
2,021
Q1
pre
68
120
536.02
after_hours
536.02
Pre
0.001488
0.002166
-0.012857
2,031.25
84
0.150542
32
0.001916
0.002518
-0.12311
891.282051
94.430769
0.185526
195
0.165715
17.802891
0
0.261807
0.480001
1
-0.977201
2
AAPL
2,021
Q1
pre
69
120
543.124
after_hours
543.124
Pre
0.00143
0.00203
0.23192
2,145.454545
83.909091
0.150199
33
0.002016
0.002673
-0.172284
855.263158
95.342105
0.189229
190
0.967689
18.77058
0
0.272037
0.483977
1
-0.977201
2
AAPL
2,021
Q1
pre
70
120
550.971
after_hours
550.971
Pre
0.001358
0.002053
0.255759
1,115.151515
83.090909
0.14711
33
0.002071
0.002792
-0.196473
910.362694
93.937824
0.186915
193
-0.000001
18.770579
0
0.268151
0.481556
1
-0.977201
2
AAPL
2,021
Q1
pre
71
120
562.1
after_hours
562.1
Pre
0.001492
0.002145
0.239881
977.5
82.275
0.14403
40
0.002039
0.002792
-0.225791
958.241758
94.510989
0.189526
182
-0.7052
18.065378
1
0.254442
0.491861
1
-0.977201
3
AAPL
2,021
Q1
pre
72
120
565.963
after_hours
565.963
Pre
0.001431
0.002005
0.214182
919.565217
81.978261
0.14291
46
0.002102
0.002816
-0.231129
967.222222
94.027778
0.189261
180
-0.924418
17.140961
0
0.238069
0.507761
1
-0.977201
3
AAPL
2,021
Q1
pre
73
120
569.486
after_hours
569.486
Pre
0.001463
0.001734
-0.046475
657.777778
81
0.139217
45
0.002132
0.002852
-0.23044
994.285714
93.422857
0.18942
175
-0.999902
16.141059
0
0.22111
0.524628
1
-0.999902
3
AAPL
2,021
Q1
pre
74
120
579.27
after_hours
579.27
Pre
0.001645
0.00186
-0.133505
611.666667
81
0.139217
60
0.002055
0.002758
-0.232662
987.431694
90.076503
0.183579
183
0.375544
16.516603
1
0.223197
0.521332
1
-0.999902
4
AAPL
2,021
Q1
pre
75
120
583.312
after_hours
583.312
Pre
0.001523
0.001523
-0.182964
682.692308
81
0.139217
52
0.002072
0.002778
-0.227433
965
90.227778
0.184318
180
0.984674
17.501277
0
0.23335
0.52521
1
-0.999902
4
AAPL
2,021
Q1
pre
76
120
593.776
after_hours
593.776
Pre
0.001538
0.001472
-0.286101
748.076923
81
0.139217
52
0.002125
0.002837
-0.227633
964.327485
90.491228
0.186403
171
0.00317
17.504446
0
0.230322
0.522364
1
-0.999902
4
AAPL
2,021
Q1
pre
77
120
603.962
after_hours
603.962
Pre
0.001146
0.000692
-0.264582
834.782609
81
0.139217
23
0.002098
0.00279
-0.258378
1,270.786517
90.921348
1.208785
178
1
18.504446
0
0.240317
0.526277
1
-0.999902
4
AAPL
2,021
Q1
pre
78
120
612.912
after_hours
612.912
Pre
0.001121
0.000625
-0.134061
688.235294
96.294118
0.191863
34
0.002154
0.002823
-0.321359
2,072.093023
89.709302
2.884751
172
0.999947
19.504393
0
0.250056
0.529876
1
-0.999902
4
AAPL
2,021
Q1
pre
79
120
613.492
after_hours
613.492
Pre
0.001121
0.000625
-0.134061
688.235294
96.294118
0.191863
34
0.002154
0.002823
-0.321359
2,072.093023
89.709302
2.884751
172
-0.000816
19.503577
1
0.246881
0.527224
1
-0.999902
5
AAPL
2,021
Q1
pre
80
120
615.334
after_hours
615.334
Pre
0.001588
0.001942
-0.10618
615.625
101.3125
0.209138
32
0.002088
0.002767
-0.335015
2,119.642857
89.25
3.068052
168
0.01063
19.514207
0
0.243928
0.524542
1
-0.999902
5
AAPL
2,021
Q1
pre
81
120
640.275
after_hours
640.275
Pre
0.002551
0.003223
-0.16311
972.857143
107
0.228716
70
0.001577
0.002238
-0.417151
3,715.942029
83.710145
7.924007
138
-0.022957
19.49125
0
0.240633
0.522096
1
-0.999902
5
AAPL
2,021
Q1
pre
82
120
645.517
after_hours
645.517
Pre
0.002702
0.003403
-0.206035
970.149254
107
0.228716
67
0.001422
0.001995
-0.434707
3,908.333333
82.469697
8.732211
132
-0.000002
19.491248
0
0.237698
0.519544
1
-0.999902
5
AAPL
2,021
Q1
pre
83
120
652.539
after_hours
652.539
Pre
0.002561
0.003371
-0.198474
1,222.44898
107
0.228716
49
0.001357
0.001982
-0.440353
4,129.655172
83.731034
10.334635
145
-0.001172
19.490076
0
0.23482
0.517031
1
-0.999902
5
AAPL
2,021
Q1
pre
84
120
659.241
after_hours
659.241
Pre
0.002687
0.003639
-0.186516
1,286.27451
107
0.228716
51
0.001426
0.001832
-0.426708
4,009.937888
84.751553
12.587652
161
0.005077
19.495153
0
0.232085
0.514518
1
-0.999902
5
AAPL
2,021
Q1
pre
85
120
661.422
after_hours
661.422
Pre
0.002775
0.003686
-0.166656
1,279.591837
107
0.228716
49
0.00143
0.001827
-0.424058
3,987.654321
84.623457
12.510502
162
-0.000105
19.495048
0
0.229354
0.512066
1
-0.999902
5
AAPL
2,021
Q1
pre
86
120
673.979
after_hours
673.979
Pre
0.002031
0.003514
-0.391406
1,664.516129
82.322581
0.166082
31
0.001504
0.001851
-0.407048
4,010.126582
85.360759
12.822252
158
-0.418432
19.076617
0
0.221821
0.513815
1
-0.999902
5
AAPL
2,021
Q1
pre
87
120
680
after_hours
680
Pre
0.00207
0.003567
-0.404453
1,713.333333
81.5
0.163995
30
0.001504
0.001851
-0.407048
4,010.126582
85.360759
12.822252
158
0.00003
19.076647
0
0.219272
0.511372
1
-0.999902
5
AAPL
2,021
Q1
pre
88
120
690.402
after_hours
690.402
Pre
0.001709
0.002578
-0.347758
1,350
62
0.114502
34
0.001437
0.001877
-0.438814
4,119.354839
85.993548
13.065934
155
0.13939
19.216037
0
0.218364
0.508496
1
-0.999902
5
AAPL
2,021
Q1
pre
89
120
711.238
after_hours
711.238
Pre
0.001633
0.001406
-0.250317
714.285714
62
0.114502
42
0.001318
0.001812
-0.348364
4,254.037267
85.484472
12.578423
161
-0.976064
18.239974
0
0.204944
0.52121
1
-0.999902
5
AAPL
2,021
Q1
pre
90
120
717.64
after_hours
717.64
Pre
0.001522
0.001141
-0.266599
636.666667
62
0.114502
30
0.001286
0.001793
-0.328171
4,328.220859
85.257669
12.424719
163
-0.000027
18.239946
0
0.202666
0.518724
1
-0.999902
5
AAPL
2,021
Q1
pre
91
120
722.656
after_hours
722.656
Pre
0.001616
0.001155
-0.481582
2,230
70.633333
4.847579
30
0.001296
0.001807
-0.289906
4,159.748428
83.81761
11.840793
159
-0.570113
17.669833
0
0.194174
0.522156
1
-0.999902
5
AAPL
2,021
Q1
pre
92
120
731.9
after_hours
731.9
Pre
0.001372
0.000727
-0.726687
7,926.923077
94.730769
18.058587
26
0.0013
0.001856
-0.185095
3,429.801325
79.940397
10.311052
151
-0.000011
17.669822
0
0.192063
0.519674
1
-0.999902
5
AAPL
2,021
Q1
pre
93
120
741.584
after_hours
741.584
Pre
0.001358
0.000717
-0.734495
7,751.851852
94.888889
18.145273
27
0.00129
0.001839
-0.156275
3,372.727273
78.805195
9.979897
154
-0.000064
17.669758
0
0.189997
0.517226
1
-0.999902
5
AAPL
2,021
Q1
pre
94
120
746.567
after_hours
746.567
Pre
0.001444
0.000868
-0.592679
7,546.428571
97.678571
19.674669
28
0.001242
0.001814
-0.163722
3,352.258065
77.43871
9.522846
155
-0.563663
17.106094
0
0.18198
0.520277
1
-0.999902
5
AAPL
2,021
Q1
pre
95
120
749.528
after_hours
749.528
Pre
0.001233
0.000871
-0.616273
7,925
99
20.39912
32
0.001267
0.001825
-0.135237
3,154.605263
76.25
9.040873
152
0.000034
17.106128
0
0.180065
0.517839
1
-0.999902
5
AAPL
2,021
Q1
pre
96
120
754.691
after_hours
754.691
Pre
0.001165
0.000884
-0.549584
8,384.615385
99
20.39912
26
0.001279
0.001817
-0.104421
3,001.960784
74.882353
8.583985
153
-0.000086
17.106042
0
0.178188
0.515434
1
-0.999902
5
AAPL
2,021
Q1
pre
97
120
757.674
after_hours
757.674
Pre
0.000875
0.000843
-0.564091
8,225.714286
99
20.39912
35
0.001356
0.001866
-0.061506
2,529.577465
72.605634
7.525662
142
0.994261
18.100303
1
0.186601
0.519395
1
-0.999902
6
AAPL
2,021
Q1
pre
98
120
770.726
after_hours
770.726
Pre
0.000574
0.000755
-0.48164
7,037.5
99
20.39912
40
0.001542
0.001994
-0.003694
1,934.328358
67.134328
5.392621
134
0.999927
19.10023
0
0.1949
0.523202
1
-0.999902
6
AAPL
2,021
Q1
pre
99
120
775.511
after_hours
775.511
Pre
0.000586
0.000958
-0.576814
6,630.612245
99
20.39912
49
0.001566
0.001973
0.071913
1,702.362205
63.094488
3.765668
127
0.000002
19.100232
0
0.192932
0.520894
1
-0.999902
6
AAPL
2,021
Q1
pre
100
120
809.817
after_hours
809.817
Pre
0.001829
0.002872
-0.397426
1,385.714286
64
0.089317
28
0.001011
0.000929
0.216004
2,712.295082
63.278689
4.157319
122
0.999985
20.100216
0
0.201002
0.524503
1
-0.999902
6
End of preview.