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Datasets:
iwillgraduate
/
rcryptocurrencydailycomments

Tasks:
Text Classification
Languages:
English
Tags:
finance
License:
Dataset card Data Studio Files
xet
Community
Dataset Preview
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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 12 new columns ({'thread_date', 'comment_rank', 'pos_prob', 'neg_prob', 'neu_prob', 'sentiment_score', 'created_utc', 'thread_id', 'dominant_label', 'score', 'parent_id', 'comment_id'}) and 10 missing columns ({'share_neu_dominant', 'mean_sentiment_score', 'mean_neg_prob', 'net_daily_sentiment', 'share_pos_dominant', 'share_neg_dominant', 'mean_neu_prob', 'n_comments', 'date', 'mean_pos_prob'}).

This happened while the csv dataset builder was generating data using

/tmp/hf-datasets-cache/medium/datasets/42548618167170-config-parquet-and-info-iwillgraduate-rcryptocurr-54e60a22/hub/datasets--iwillgraduate--rcryptocurrencydailycomments/snapshots/05c800fd7588c59bd2b437e6369f053830fd7d5a/reddit_scored_ids.csv.gz

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              thread_date: string
              thread_id: string
              comment_id: string
              parent_id: string
              comment_rank: int64
              created_utc: int64
              score: int64
              pos_prob: double
              neg_prob: double
              neu_prob: double
              sentiment_score: double
              dominant_label: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1698
              to
              {'date': Value('string'), 'n_comments': Value('int64'), 'mean_pos_prob': Value('float64'), 'mean_neg_prob': Value('float64'), 'mean_neu_prob': Value('float64'), 'mean_sentiment_score': Value('float64'), 'share_pos_dominant': Value('float64'), 'share_neg_dominant': Value('float64'), 'share_neu_dominant': Value('float64'), 'net_daily_sentiment': 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 1339, 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 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, 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 1833, 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 12 new columns ({'thread_date', 'comment_rank', 'pos_prob', 'neg_prob', 'neu_prob', 'sentiment_score', 'created_utc', 'thread_id', 'dominant_label', 'score', 'parent_id', 'comment_id'}) and 10 missing columns ({'share_neu_dominant', 'mean_sentiment_score', 'mean_neg_prob', 'net_daily_sentiment', 'share_pos_dominant', 'share_neg_dominant', 'mean_neu_prob', 'n_comments', 'date', 'mean_pos_prob'}).
              
              This happened while the csv dataset builder was generating data using
              
              /tmp/hf-datasets-cache/medium/datasets/42548618167170-config-parquet-and-info-iwillgraduate-rcryptocurr-54e60a22/hub/datasets--iwillgraduate--rcryptocurrencydailycomments/snapshots/05c800fd7588c59bd2b437e6369f053830fd7d5a/reddit_scored_ids.csv.gz
              
              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.

date
string
n_comments
int64
mean_pos_prob
float64
mean_neg_prob
float64
mean_neu_prob
float64
mean_sentiment_score
float64
share_pos_dominant
float64
share_neg_dominant
float64
share_neu_dominant
float64
net_daily_sentiment
float64
2020-01-01
34
0.13156
0.058015
0.810425
0.073544
0.058824
0
0.941176
0.073544
2020-01-02
32
0.101073
0.177959
0.720968
-0.076886
0
0.15625
0.84375
-0.076886
2020-01-03
38
0.095885
0.184911
0.719204
-0.089026
0.026316
0.131579
0.842105
-0.089026
2020-01-04
19
0.074913
0.095374
0.829713
-0.020461
0
0
1
-0.020461
2020-01-05
31
0.151378
0.160362
0.68826
-0.008984
0.129032
0.096774
0.774194
-0.008984
2020-01-06
42
0.13911
0.195148
0.665741
-0.056038
0.071429
0.166667
0.761905
-0.056038
2020-01-07
59
0.130556
0.12507
0.744374
0.005485
0.067797
0.101695
0.830508
0.005485
2020-01-08
49
0.136882
0.177395
0.685724
-0.040513
0.081633
0.122449
0.795918
-0.040513
2020-01-09
25
0.086853
0.164233
0.748914
-0.077381
0
0.16
0.84
-0.077381
2020-01-10
31
0.092957
0.184974
0.722069
-0.092017
0.032258
0.16129
0.806452
-0.092017
2020-01-11
31
0.109966
0.148609
0.741425
-0.038644
0.064516
0.096774
0.83871
-0.038644
2020-01-12
17
0.087022
0.112762
0.800215
-0.02574
0
0.058824
0.941176
-0.02574
2020-01-13
28
0.094704
0.087246
0.81805
0.007458
0.035714
0
0.964286
0.007458
2020-01-14
72
0.100211
0.174618
0.725171
-0.074406
0.055556
0.111111
0.833333
-0.074406
2020-01-15
53
0.138075
0.202115
0.65981
-0.06404
0.09434
0.169811
0.735849
-0.06404
2020-01-16
35
0.117885
0.136138
0.745977
-0.018253
0.114286
0.085714
0.8
-0.018253
2020-01-17
58
0.172246
0.128196
0.699558
0.04405
0.137931
0.068966
0.793103
0.04405
2020-01-18
42
0.074611
0.156076
0.769313
-0.081465
0.02381
0.119048
0.857143
-0.081465
2020-01-19
54
0.105759
0.143587
0.750654
-0.037827
0.055556
0.037037
0.907407
-0.037827
2020-01-20
25
0.118293
0.121256
0.760451
-0.002963
0.08
0.04
0.88
-0.002963
2020-01-21
31
0.058179
0.125118
0.816703
-0.066939
0
0.129032
0.870968
-0.066939
2020-01-22
23
0.061422
0.118106
0.820472
-0.056683
0
0.043478
0.956522
-0.056683
2020-01-23
17
0.066916
0.200475
0.732609
-0.133558
0
0.117647
0.882353
-0.133558
2020-01-24
27
0.105358
0.060184
0.834458
0.045174
0.074074
0
0.925926
0.045174
2020-01-25
27
0.085852
0.128338
0.78581
-0.042486
0.037037
0.037037
0.925926
-0.042486
2020-01-26
21
0.091383
0.174228
0.734389
-0.082844
0.047619
0.142857
0.809524
-0.082844
2020-01-27
40
0.080979
0.161205
0.757816
-0.080226
0.025
0.15
0.825
-0.080226
2020-01-28
45
0.117792
0.093246
0.788962
0.024546
0.066667
0.044444
0.888889
0.024546
2020-01-29
35
0.149961
0.111111
0.738929
0.03885
0.057143
0.085714
0.857143
0.03885
2020-01-30
44
0.184254
0.158902
0.656844
0.025352
0.181818
0.113636
0.704545
0.025352
2020-01-31
26
0.057227
0.191385
0.751388
-0.134158
0
0.115385
0.884615
-0.134158
2020-02-01
20
0.074228
0.142785
0.782987
-0.068557
0
0.1
0.9
-0.068557
2020-02-02
40
0.133688
0.146196
0.720116
-0.012508
0.075
0.1
0.825
-0.012508
2020-02-03
35
0.076981
0.174607
0.748412
-0.097626
0
0.171429
0.828571
-0.097626
2020-02-04
50
0.100898
0.175481
0.723622
-0.074583
0.02
0.16
0.82
-0.074583
2020-02-05
59
0.133948
0.132746
0.733306
0.001202
0.033898
0.118644
0.847458
0.001202
2020-02-06
53
0.101323
0.101533
0.797144
-0.00021
0.037736
0.018868
0.943396
-0.00021
2020-02-07
48
0.120222
0.139495
0.740283
-0.019274
0.0625
0.0625
0.875
-0.019274
2020-02-08
47
0.13592
0.129316
0.734764
0.006604
0.06383
0.085106
0.851064
0.006604
2020-02-09
64
0.123754
0.103824
0.772422
0.019931
0.0625
0.0625
0.875
0.019931
2020-02-10
41
0.115855
0.14843
0.735715
-0.032575
0.04878
0.097561
0.853659
-0.032575
2020-02-11
61
0.09663
0.193749
0.709621
-0.09712
0.032787
0.180328
0.786885
-0.09712
2020-02-12
74
0.160173
0.131061
0.708766
0.029112
0.094595
0.067568
0.837838
0.029112
2020-02-13
61
0.10779
0.135826
0.756385
-0.028036
0.032787
0.081967
0.885246
-0.028036
2020-02-14
51
0.061224
0.184292
0.754484
-0.123067
0
0.156863
0.843137
-0.123067
2020-02-15
67
0.133064
0.149208
0.717728
-0.016144
0.089552
0.089552
0.820896
-0.016144
2020-02-16
62
0.091117
0.235982
0.672901
-0.144865
0.032258
0.193548
0.774194
-0.144865
2020-02-17
62
0.117254
0.173906
0.70884
-0.056652
0.064516
0.112903
0.822581
-0.056652
2020-02-18
51
0.198124
0.159879
0.641997
0.038246
0.156863
0.117647
0.72549
0.038246
2020-02-19
58
0.140012
0.226769
0.633219
-0.086757
0.103448
0.189655
0.706897
-0.086757
2020-02-20
43
0.109876
0.153139
0.736985
-0.043263
0.046512
0.093023
0.860465
-0.043263
2020-02-21
34
0.105128
0.160628
0.734244
-0.055499
0.029412
0.117647
0.852941
-0.055499
2020-02-22
36
0.111688
0.122471
0.765842
-0.010783
0.083333
0.111111
0.805556
-0.010783
2020-02-23
28
0.132445
0.195634
0.671921
-0.063189
0.107143
0.178571
0.714286
-0.063189
2020-02-24
41
0.097862
0.147612
0.754526
-0.049751
0.04878
0.073171
0.878049
-0.049751
2020-02-25
46
0.067831
0.255715
0.676455
-0.187884
0.021739
0.217391
0.76087
-0.187884
2020-02-26
69
0.106856
0.279935
0.613209
-0.173079
0.057971
0.246377
0.695652
-0.173079
2020-02-27
50
0.125481
0.179202
0.695316
-0.053721
0.06
0.14
0.8
-0.053721
2020-02-28
58
0.096456
0.156437
0.747107
-0.05998
0.017241
0.068966
0.913793
-0.05998
2020-02-29
23
0.054238
0.152024
0.793738
-0.097785
0
0.043478
0.956522
-0.097785
2020-03-01
41
0.095479
0.147399
0.757122
-0.051919
0.073171
0.04878
0.878049
-0.051919
2020-03-02
35
0.110375
0.165073
0.724552
-0.054698
0.057143
0.114286
0.828571
-0.054698
2020-03-03
32
0.073809
0.266433
0.659758
-0.192624
0.03125
0.1875
0.78125
-0.192624
2020-03-04
29
0.119693
0.12065
0.759657
-0.000957
0.068966
0.103448
0.827586
-0.000957
2020-03-05
36
0.143847
0.180197
0.675955
-0.03635
0.055556
0.166667
0.777778
-0.03635
2020-03-06
34
0.124962
0.129633
0.745405
-0.004672
0.058824
0.029412
0.911765
-0.004672
2020-03-07
32
0.085019
0.135084
0.779897
-0.050065
0.03125
0.0625
0.90625
-0.050065
2020-03-08
68
0.095708
0.258072
0.64622
-0.162364
0.044118
0.235294
0.720588
-0.162364
2020-03-09
59
0.086354
0.304133
0.609513
-0.217779
0.033898
0.288136
0.677966
-0.217779
2020-03-10
37
0.08616
0.265365
0.648475
-0.179204
0.027027
0.243243
0.72973
-0.179204
2020-03-11
39
0.089369
0.159915
0.750716
-0.070546
0.025641
0.102564
0.871795
-0.070546
2020-03-12
86
0.068478
0.28626
0.645262
-0.217783
0.023256
0.244186
0.732558
-0.217783
2020-03-13
87
0.08976
0.257291
0.65295
-0.167531
0.045977
0.206897
0.747126
-0.167531
2020-03-14
45
0.068818
0.235468
0.695714
-0.166651
0.022222
0.2
0.777778
-0.166651
2020-03-15
48
0.109922
0.180874
0.709205
-0.070952
0.083333
0.125
0.791667
-0.070952
2020-03-16
66
0.073697
0.281074
0.645229
-0.207376
0.015152
0.242424
0.742424
-0.207376
2020-03-17
40
0.11021
0.176145
0.713645
-0.065934
0.075
0.1
0.825
-0.065934
2020-03-18
46
0.143731
0.234791
0.621478
-0.09106
0.065217
0.217391
0.717391
-0.09106
2020-03-19
63
0.100262
0.252198
0.64754
-0.151936
0.079365
0.238095
0.68254
-0.151936
2020-03-20
54
0.10122
0.277226
0.621555
-0.176006
0.055556
0.296296
0.648148
-0.176006
2020-03-21
20
0.081384
0.186582
0.732034
-0.105198
0.05
0.2
0.75
-0.105198
2020-03-22
35
0.083422
0.241352
0.675226
-0.15793
0.028571
0.2
0.771429
-0.15793
2020-03-23
43
0.076849
0.256394
0.666757
-0.179545
0.023256
0.232558
0.744186
-0.179545
2020-03-24
43
0.12058
0.154496
0.724924
-0.033916
0.069767
0.093023
0.837209
-0.033916
2020-03-25
30
0.04544
0.311269
0.643291
-0.265829
0
0.333333
0.666667
-0.265829
2020-03-26
24
0.109335
0.110385
0.78028
-0.00105
0.041667
0.041667
0.916667
-0.00105
2020-03-27
27
0.09651
0.159121
0.74437
-0.062611
0.037037
0.037037
0.925926
-0.062611
2020-03-28
31
0.0498
0.265532
0.684667
-0.215732
0
0.225806
0.774194
-0.215732
2020-03-29
29
0.103057
0.253657
0.643287
-0.1506
0.068966
0.275862
0.655172
-0.1506
2020-03-30
18
0.055818
0.150811
0.793371
-0.094993
0
0.111111
0.888889
-0.094993
2020-03-31
25
0.095176
0.159776
0.745048
-0.0646
0.08
0.08
0.84
-0.0646
2020-04-01
26
0.201137
0.143683
0.65518
0.057455
0.153846
0.076923
0.769231
0.057455
2020-04-02
45
0.07344
0.142492
0.784068
-0.069053
0.022222
0.111111
0.866667
-0.069053
2020-04-03
23
0.07373
0.138495
0.787775
-0.064765
0
0.086957
0.913043
-0.064765
2020-04-04
16
0.107677
0.070891
0.821432
0.036786
0.0625
0
0.9375
0.036786
2020-04-05
24
0.079777
0.091221
0.829002
-0.011445
0
0.041667
0.958333
-0.011445
2020-04-06
25
0.177341
0.092239
0.73042
0.085102
0.12
0.04
0.84
0.085102
2020-04-07
34
0.089024
0.192275
0.718701
-0.103252
0.029412
0.176471
0.794118
-0.103252
2020-04-08
30
0.085871
0.1556
0.758529
-0.069729
0.033333
0.1
0.866667
-0.069729
2020-04-09
20
0.064014
0.196461
0.739525
-0.132447
0
0.15
0.85
-0.132447
End of preview.

r/CryptoCurrency daily discussion sentiment (2020-2023)

This repository provides comment-level sentiment scores and daily aggregates derived from daily discussion threads on /r/CryptoCurrency.

Data coverage and sampling

The dataset covers the period from 2020-01-01 to 2023-11-16 (UTC), containing 1344 daily threads/dates (72 days in the full date span are not present).

For each date we store up to 100 comments ranked by comment_rank (1 is the highest-ranked comment). In the cleaned comment-level file the number of retained comments per day varies (median 88, mean 79; min 2, max 100).

Files

  • reddit_scored_ids.csv.gz Comment-level dataset without the raw comment text and without user-identifying fields.

  • reddit_daily_clean.csv Daily aggregates computed from the deduplicated comment-level file.

Columns (comment-level)

  • thread_date: date of the daily thread (UTC, ISO format)
  • thread_id: Reddit submission ID for the daily thread
  • comment_id: Reddit comment ID
  • parent_id: parent identifier (thread or parent comment)
  • comment_rank: rank within the day’s thread (1 to 100)
  • created_utc: Unix timestamp (seconds, UTC)
  • score: Reddit comment score at the time of collection
  • pos_prob, neg_prob, neu_prob: sentiment probabilities (sum to 1)
  • sentiment_score: pos_prob - neg_prob
  • dominant_label: argmax of the three sentiment probabilities
  • body (text file only): comment text
  • body_is_deleted_or_removed (text file only): 1 if body is [deleted] or [removed]

Daily aggregates

reddit_daily_dedup.csv contains one row per date with:

  • n_comments
  • mean_pos_prob, mean_neg_prob, mean_neu_prob
  • mean_sentiment_score
  • share_pos_dominant, share_neg_dominant, share_neu_dominant
  • net_daily_sentiment (equal to mean_sentiment_score)

Cleaning notes

The raw export contained duplicate comment_id rows; the cleaned exports keep one row per comment_id. A small number of malformed lines in the raw CSV were discarded during parsing.

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