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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 14 new columns ({'HIGH_PRICE', 'PRICE_CHANGE', 'CLOSE_PRICE', 'VOLUME', 'STOCK', 'MA_30', 'LOW_PRICE', 'RETURN', 'MA_7', 'MOMENTUM', 'TREND', 'VOLATILITY_7D', 'DATE', 'OPEN_PRICE'}) and 7 missing columns ({'Close', 'Volume', 'Scrip', 'Date', 'Low', 'High', 'Open'}).

This happened while the csv dataset builder was generating data using

hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026/dse_clean_master_dataset_2026.csv (at revision d2426cf4293a273e6be7eb95e44d1eb56f9471e8), [/tmp/hf-datasets-cache/medium/datasets/60061653731957-config-parquet-and-info-mahfuzmee-eng-dse_clean_m-d4c2958f/hub/datasets--mahfuzmee-eng--dse_clean_master_dataset_2026/snapshots/d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2025.csv (origin=hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026@d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2025.csv), /tmp/hf-datasets-cache/medium/datasets/60061653731957-config-parquet-and-info-mahfuzmee-eng-dse_clean_m-d4c2958f/hub/datasets--mahfuzmee-eng--dse_clean_master_dataset_2026/snapshots/d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2026.csv (origin=hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026@d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2026.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
              DATE: string
              STOCK: string
              OPEN_PRICE: double
              HIGH_PRICE: double
              LOW_PRICE: double
              CLOSE_PRICE: double
              VOLUME: int64
              RETURN: double
              VOLATILITY_7D: double
              PRICE_CHANGE: double
              MA_7: double
              MA_30: double
              TREND: bool
              MOMENTUM: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1881
              to
              {'Date': Value('string'), 'Scrip': Value('string'), 'Open': Value('float64'), 'High': Value('float64'), 'Low': Value('float64'), 'Close': Value('float64'), 'Volume': Value('int64')}
              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 14 new columns ({'HIGH_PRICE', 'PRICE_CHANGE', 'CLOSE_PRICE', 'VOLUME', 'STOCK', 'MA_30', 'LOW_PRICE', 'RETURN', 'MA_7', 'MOMENTUM', 'TREND', 'VOLATILITY_7D', 'DATE', 'OPEN_PRICE'}) and 7 missing columns ({'Close', 'Volume', 'Scrip', 'Date', 'Low', 'High', 'Open'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026/dse_clean_master_dataset_2026.csv (at revision d2426cf4293a273e6be7eb95e44d1eb56f9471e8), [/tmp/hf-datasets-cache/medium/datasets/60061653731957-config-parquet-and-info-mahfuzmee-eng-dse_clean_m-d4c2958f/hub/datasets--mahfuzmee-eng--dse_clean_master_dataset_2026/snapshots/d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2025.csv (origin=hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026@d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2025.csv), /tmp/hf-datasets-cache/medium/datasets/60061653731957-config-parquet-and-info-mahfuzmee-eng-dse_clean_m-d4c2958f/hub/datasets--mahfuzmee-eng--dse_clean_master_dataset_2026/snapshots/d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2026.csv (origin=hf://datasets/mahfuzmee-eng/dse_clean_master_dataset_2026@d2426cf4293a273e6be7eb95e44d1eb56f9471e8/dse_clean_master_dataset_2026.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.

Date
string
Scrip
string
Open
float64
High
float64
Low
float64
Close
float64
Volume
int64
2025-01-01
00DS30
1,939.73323
1,949.43366
1,939.02778
1,941.93663
3,305,973,000
2025-01-01
PDL
6.5
6.6
6.4
6.5
139,101
2025-01-01
PARAMOUNT
41.8
41.8
40.8
40.9
34,667
2025-01-01
PADMAOIL
188
190.3
188
188.6
6,945
2025-01-01
PADMALIFE
16.4
16.8
16.2
16.4
10,095
2025-01-01
ORYZAAGRO
24.9
25.1
24.8
24.9
30,567
2025-01-01
ORIONPHARM
38
38.6
37.7
37.8
1,060,476
2025-01-01
ORIONINFU
425.1
425.1
389.4
389.4
686,718
2025-01-01
ONEBANKPLC
8.5
8.6
8.4
8.4
778,391
2025-01-01
OLYMPIC
158
158.8
155.7
156.2
26,436
2025-01-01
OIMEX
28.2
29.4
28.2
28.9
2,177,613
2025-01-01
PENINSULA
10.7
10.9
10.7
10.8
8,038
2025-01-01
OAL
7
7.2
7
7.2
270,894
2025-01-01
NTLTUBES
85.9
85.9
84.6
84.9
108,127
2025-01-01
NTC
190.4
195
190.4
193.6
2,749
2025-01-01
NRBCBANK
8.5
8.5
8.3
8.5
85,790
2025-01-01
NRBBANK
12.3
12.6
12.3
12.3
3,448,058
2025-01-01
NPOLYMER
32.2
32.2
31.9
32.1
67,188
2025-01-01
NORTHRNINS
29.1
29.9
29
29.1
10,625
2025-01-01
NORTHERN
116.1
116.1
112
113
1,987
2025-01-01
NITOLINS
24.761905
24.761905
24
24.095238
12,038
2025-01-01
NIALCO
25.4
27.7
25.4
26
195,801
2025-01-01
NHFIL
27
27
26.5
26.8
31,472
2025-01-01
NURANI
3.7
3.7
3.7
3.7
70,560
2025-01-01
NFML
8.1
8.1
7.9
8
17,166
2025-01-01
PEOPLESINS
31
31.2
30.4
30.5
175,779
2025-01-01
PHARMAID
573.3
577
565.5
569.7
6,992
2025-01-01
PTL
47
47
45.6
46
56,930
2025-01-01
PROVATIINS
37.3
37.8
36.9
37.6
827,037
2025-01-01
PROGRESLIF
37.4
39
37
37.4
305
2025-01-01
PRIMETEX
12.1
12.3
11.9
12
18,351
2025-01-01
PRIMELIFE
32.2
32.2
31
31.1
27,554
2025-01-01
PRIMEINSUR
36.2
36.2
35.3
35.4
11,032
2025-01-01
PRIMEFIN
4.4
4.4
4.1
4.2
49,100
2025-01-01
PRIMEBANK
22.829268
23.512195
22.829268
23.414634
343,562
2025-01-01
PRIME1ICBA
4.8
4.9
4.8
4.8
158,126
2025-01-01
PREMIERLEA
3.2
3.3
3.2
3.3
55,301
2025-01-01
PF1STMF
5.5
5.6
5.5
5.5
28,122
2025-01-01
PREMIERCEM
48.2
48.4
46.6
47.1
35,136
2025-01-01
PRAGATILIF
131
133.8
129
130.1
6,126
2025-01-01
PRAGATIINS
50
51.121495
49.719626
49.719626
10,414
2025-01-01
POWERGRID
41.8
42.3
41.5
41.8
146,992
2025-01-01
POPULARLIF
51
51.8
50.6
51
10,786
2025-01-01
POPULAR1MF
3.2
3.2
3.1
3.1
17,384
2025-01-01
PLFSL
2.3
2.3
2.2
2.3
94,384
2025-01-01
PIONEERINS
48.1
48.5
47.8
48
3,640
2025-01-01
PHPMF1
3.3
3.3
3.1
3.2
39,337
2025-01-01
PHOENIXFIN
3.2
3.3
3.2
3.3
345,413
2025-01-01
PHENIXINS
26
26.6
26
26.1
2,960
2025-01-01
PREMIERBAN
9
9.1
8.9
9
561,337
2025-01-01
NEWLINE
6.6
6.8
6.6
6.7
862,729
2025-01-01
NCCBLMF1
5.2
5.2
5.2
5.2
83
2025-01-01
NCCBANK
10.8
10.9
10.8
10.9
266,987
2025-01-01
MEGHNACEM
45.6
45.6
42.8
42.9
7,647
2025-01-01
MEGCONMILK
27.3
27.4
27
27.3
2,126
2025-01-01
MBL1STMF
4
4
3.9
3.9
63,385
2025-01-01
MATINSPINN
45.6
45.8
45.1
45.3
53,561
2025-01-01
MASTERAGRO
6.8
7.4
6.8
7.4
130,623
2025-01-01
MARICO
2,324
2,324
2,285.6
2,307.2
558
2025-01-01
MAMUNAGRO
33.2
34.5
33.2
34.4
329,562
2025-01-01
MALEKSPIN
25
25.1
24.7
24.8
243,852
2025-01-01
MAKSONSPIN
6.1
6.2
6
6
126,724
2025-01-01
MAGURAPLEX
105
107.4
104.2
104.5
22,533
2025-01-01
MEGHNAINS
28
28.3
27.6
27.7
139,280
2025-01-01
LRGLOBMF1
3.3
3.5
3.3
3.3
4,100
2025-01-01
LOVELLO
86.8
88.2
85.1
86.5
1,010,480
2025-01-01
LINDEBD
1,028.9
1,045
1,004.5
1,007.2
36,029
2025-01-01
LIBRAINFU
813.1
813.9
780.1
784.7
5,511
2025-01-01
LHB
54
54.5
53.3
53.5
135,343
2025-01-01
LEGACYFOOT
60.5
61.8
59.2
60.7
314,531
2025-01-01
LANKABAFIN
18.7
18.9
18.5
18.6
696,619
2025-01-01
KTL
9
9.1
8.9
8.9
194,324
2025-01-01
KPPL
8.5
9.3
8.4
9.3
798,469
2025-01-01
KPCL
13
13.1
12.8
12.8
99,476
2025-01-01
KOHINOOR
509.1
513
507
509.7
7,551
2025-01-01
LRBDL
14.2
14.2
13.7
13.8
267,308
2025-01-01
MEGHNALIFE
55.5
56
54.6
54.8
131,124
2025-01-01
MEGHNAPET
27.2
27.3
26.6
26.8
13,525
2025-01-01
MERCANBANK
10.3
10.4
10.2
10.3
534,809
2025-01-01
NBL
4.9
5
4.9
5
72,838
2025-01-01
NAVANAPHAR
49
49
48.1
48.2
148,013
2025-01-01
NAVANACNG
23.6
23.7
22.8
23
325,376
2025-01-01
NATLIFEINS
105.8
107.2
103.8
104
73,401
2025-01-01
NAHEEACP
21.3
21.4
20.9
21.2
125,532
2025-01-01
MTB
11.363636
11.363636
11.090909
11.272727
203,703
2025-01-01
MPETROLEUM
195.7
200.2
195.4
198
215,254
2025-01-01
MOSTFAMETL
11.8
12.6
11.8
12.5
404,171
2025-01-01
MONOSPOOL
110.9
111
107.1
107.6
111,476
2025-01-01
MONNOFABR
17
17
16.6
16.6
370,734
2025-01-01
MONNOCERA
65.8
65.9
64.8
65
14,437
2025-01-01
MONNOAGML
354.8
357.9
342
345
30,478
2025-01-01
MLDYEING
9.2
9.3
8.9
9
105,443
2025-01-01
MKFOOTWEAR
45.2
46.1
45
45.7
110,579
2025-01-01
MJLBD
95.3
95.3
94.1
95
123,624
2025-01-01
MITHUNKNIT
14.5
14.5
13.3
13.5
31,324
2025-01-01
MIRAKHTER
31.2
31.7
31.2
31.4
33,820
2025-01-01
MIRACLEIND
26.9
26.9
25.9
26.1
99,657
2025-01-01
MIDLANDBNK
30.291262
30.582524
30.097087
30.291262
338,269
2025-01-01
MIDASFIN
8.1
8.3
8
8.1
35,796
2025-01-01
MHSML
14.3
14.4
14
14.1
46,810
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