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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 | 0.000689 | 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 | -0.000063 | 0.710228 | 0 | 0.177557 | 0.260059 | 0.551028 | -0.000063 | 0 |
AAPL | 2,021 | Q1 | pre | 5 | 120 | 58.803 | after_hours | 58.803 | Pre | 0.000483 | 0.00052 | -0.561447 | 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 | -0.16193 | 4,473.333333 | 130 | 0.072239 | 60 | 0.00123 | 0.001589 | -0.087105 | 2,243.425076 | 164.541284 | 6.084057 | 327 | 0.238992 | 0.877656 | 0 | 0.079787 | 0.183238 | 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 |
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