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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 1 new columns ({'layer'}) and 11 missing columns ({'region_new', 'align_y', 'Xcorr', 'Ycorr', 'idd', 'cell', 'cell_id', 'array', 'align_x', 'Unnamed: 0', 'celltype'}).

This happened while the csv dataset builder was generating data using

gzip://codex_duodenum_aligned.csv::hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_aligned.csv.gz, ['hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_colon.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_aligned.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_raw.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/xenium_colon.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/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              x: double
              y: double
              layer: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 597
              to
              {'Unnamed: 0': Value('int64'), 'cell_id': Value('float64'), 'cell': Value('string'), 'x': Value('float64'), 'y': Value('float64'), 'Xcorr': Value('int64'), 'Ycorr': Value('int64'), 'region_new': Value('float64'), 'array': Value('string'), 'align_x': Value('int64'), 'align_y': Value('int64'), 'idd': Value('string'), 'celltype': Value('string')}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 1 new columns ({'layer'}) and 11 missing columns ({'region_new', 'align_y', 'Xcorr', 'Ycorr', 'idd', 'cell', 'cell_id', 'array', 'align_x', 'Unnamed: 0', 'celltype'}).
              
              This happened while the csv dataset builder was generating data using
              
              gzip://codex_duodenum_aligned.csv::hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_aligned.csv.gz, ['hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_colon.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_aligned.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/codex_duodenum_raw.csv.gz', 'hf://datasets/a12910/spacemap-data@043a9a8505bd6decb9ae6fa0af49438e9f2ea7ba/xenium_colon.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.

Unnamed: 0
int64
cell_id
float64
cell
string
x
float64
y
float64
Xcorr
int64
Ycorr
int64
region_new
float64
array
string
align_x
int64
align_y
int64
idd
string
celltype
string
580,888
1
B014_1.0_1.0
8,530
6,734
8,530
81,734
1
S1
9,149
2,336
S1_9149_2336
T cells, nerve, smooth muscle, globlet, paneth
580,889
4
B014_1.0_4.0
4,374
11,883
4,374
86,883
1
S1
5,344
7,291
S1_5344_7291
Epithelial
580,890
5
B014_1.0_5.0
9,050
12,232
9,050
87,232
1
S1
9,926
7,605
S1_9926_7605
Nerve
580,891
6
B014_1.0_6.0
2,472
9,759
2,472
84,759
1
S1
3,424
5,172
S1_3424_5172
Epithelial
580,892
8
B014_1.0_8.0
4,010
5,911
4,010
80,911
1
S1
4,645
1,613
S1_4645_1613
Epithelial
580,893
9
B014_1.0_9.0
4,776
5,997
4,776
80,997
1
S1
5,439
1,729
S1_5439_1729
Epithelial
580,894
12
B014_1.0_12.0
2,043
7,232
2,043
82,232
1
S1
2,976
2,749
S1_2976_2749
null
580,895
14
B014_1.0_14.0
4,427
7,342
4,427
82,342
1
S1
5,065
2,918
S1_5065_2918
endothelial/fibroblast
580,896
15
B014_1.0_15.0
1,293
9,029
1,293
84,029
1
S1
2,254
4,505
S1_2254_4505
Epithelial
580,897
18
B014_1.0_18.0
4,082
9,006
4,082
84,006
1
S1
4,878
4,526
S1_4878_4526
endothelial/fibroblast
580,898
20
B014_1.0_20.0
9,904
6,982
9,904
81,982
1
S1
10,499
2,558
S1_10499_2558
endothelial/fibroblast
580,899
21
B014_1.0_21.0
4,946
15,975
4,946
90,975
1
S1
5,961
11,276
S1_5961_11276
null
580,900
22
B014_1.0_22.0
11,279
12,630
11,279
87,630
1
S1
12,238
8,007
S1_12238_8007
endothelial/fibroblast
580,901
23
B014_1.0_23.0
5,521
14,552
5,521
89,552
1
S1
6,644
9,801
S1_6644_9801
Epithelial
580,902
25
B014_1.0_25.0
3,510
6,813
3,510
81,813
1
S1
4,189
2,366
S1_4189_2366
endothelial/fibroblast
580,903
26
B014_1.0_26.0
5,155
13,272
5,155
88,272
1
S1
6,298
8,565
S1_6298_8565
Epithelial
580,904
27
B014_1.0_27.0
4,810
11,586
4,810
86,586
1
S1
5,799
6,999
S1_5799_6999
null
580,905
29
B014_1.0_29.0
4,286
9,903
4,286
84,903
1
S1
5,158
5,387
S1_5158_5387
Plasma cells/Epithelial cells/Stromal
580,906
30
B014_1.0_30.0
5,256
15,362
5,256
90,362
1
S1
6,233
10,647
S1_6233_10647
null
580,907
31
B014_1.0_31.0
8,041
12,568
8,041
87,568
1
S1
8,910
7,921
S1_8910_7921
endothelial/fibroblast
580,908
35
B014_1.0_35.0
4,971
6,984
4,971
81,984
1
S1
5,578
2,573
S1_5578_2573
endothelial/fibroblast
580,909
36
B014_1.0_36.0
4,699
9,792
4,699
84,792
1
S1
5,524
5,265
S1_5524_5265
B cells
580,910
37
B014_1.0_37.0
3,751
11,980
3,751
86,980
1
S1
4,632
7,414
S1_4632_7414
Plasma cells/Epithelial cells/Stromal
580,911
38
B014_1.0_38.0
4,070
11,812
4,070
86,812
1
S1
4,988
7,233
S1_4988_7233
Macrophage
580,912
39
B014_1.0_39.0
4,969
14,146
4,969
89,146
1
S1
6,154
9,411
S1_6154_9411
null
580,913
42
B014_1.0_42.0
8,667
11,970
8,667
86,970
1
S1
9,523
7,347
S1_9523_7347
Treg
580,914
44
B014_1.0_44.0
4,078
6,072
4,078
81,072
1
S1
4,707
1,753
S1_4707_1753
Epithelial
580,915
45
B014_1.0_45.0
3,724
6,024
3,724
81,024
1
S1
4,364
1,672
S1_4364_1672
Fibroblast
580,916
46
B014_1.0_46.0
6,664
11,283
6,664
86,283
1
S1
7,499
6,736
S1_7499_6736
endothelial/fibroblast
580,917
47
B014_1.0_47.0
10,047
8,074
10,047
83,074
1
S1
10,701
3,538
S1_10701_3538
endothelial/fibroblast
580,918
48
B014_1.0_48.0
5,301
13,424
5,301
88,424
1
S1
6,434
8,714
S1_6434_8714
Epithelial
580,919
49
B014_1.0_49.0
8,346
10,274
8,346
85,274
1
S1
9,142
5,695
S1_9142_5695
Treg
580,920
52
B014_1.0_52.0
1,350
8,757
1,350
83,757
1
S1
2,316
4,234
S1_2316_4234
Epithelial
580,921
53
B014_1.0_53.0
1,680
8,530
1,680
83,530
1
S1
2,680
4,001
S1_2680_4001
null
580,922
56
B014_1.0_56.0
4,596
13,381
4,596
88,381
1
S1
5,787
8,667
S1_5787_8667
Epithelial
580,923
59
B014_1.0_59.0
5,008
14,343
5,008
89,343
1
S1
6,162
9,614
S1_6162_9614
null
580,924
60
B014_1.0_60.0
4,549
12,651
4,549
87,651
1
S1
5,657
7,991
S1_5657_7991
Endothelial
580,925
62
B014_1.0_62.0
6,424
16,888
6,424
91,888
1
S1
7,600
12,033
S1_7600_12033
null
580,926
63
B014_1.0_63.0
6,428
5,863
6,428
80,863
1
S1
7,015
1,522
S1_7015_1522
endothelial/fibroblast
580,927
64
B014_1.0_64.0
5,314
12,924
5,314
87,924
1
S1
6,379
8,258
S1_6379_8258
Epithelial
580,928
66
B014_1.0_66.0
6,088
16,673
6,088
91,673
1
S1
7,228
11,831
S1_7228_11831
null
580,929
69
B014_1.0_69.0
1,651
7,216
1,651
82,216
1
S1
2,601
2,701
S1_2601_2701
null
580,930
70
B014_1.0_70.0
5,681
13,882
5,681
88,882
1
S1
6,791
9,175
S1_6791_9175
Goblet cells
580,931
73
B014_1.0_73.0
4,365
10,486
4,365
85,486
1
S1
5,300
5,934
S1_5300_5934
Epithelial
580,932
74
B014_1.0_74.0
5,458
15,759
5,458
90,759
1
S1
6,466
11,049
S1_6466_11049
null
580,933
76
B014_1.0_76.0
6,223
11,650
6,223
86,650
1
S1
7,091
7,091
S1_7091_7091
Treg
580,934
78
B014_1.0_78.0
4,868
6,012
4,868
81,012
1
S1
5,532
1,739
S1_5532_1739
Epithelial
580,935
79
B014_1.0_79.0
4,713
5,989
4,713
80,989
1
S1
5,373
1,722
S1_5373_1722
Epithelial
580,936
80
B014_1.0_80.0
5,678
12,246
5,678
87,246
1
S1
6,612
7,659
S1_6612_7659
Smooth muscle
580,937
81
B014_1.0_81.0
9,001
5,997
9,001
80,997
1
S1
9,599
1,618
S1_9599_1618
Endothelial
580,938
82
B014_1.0_82.0
2,665
8,538
2,665
83,538
1
S1
3,580
4,027
S1_3580_4027
Epithelial
580,939
83
B014_1.0_83.0
4,631
11,400
4,631
86,400
1
S1
5,620
6,817
S1_5620_6817
Fibroblast
580,940
84
B014_1.0_84.0
3,848
11,131
3,848
86,131
1
S1
4,819
6,550
S1_4819_6550
Epithelial
580,941
85
B014_1.0_85.0
4,014
12,707
4,014
87,707
1
S1
4,993
8,090
S1_4993_8090
Macrophage
580,942
87
B014_1.0_87.0
2,486
9,367
2,486
84,367
1
S1
3,432
4,804
S1_3432_4804
Epithelial
580,943
89
B014_1.0_89.0
7,884
7,339
7,884
82,339
1
S1
8,544
2,905
S1_8544_2905
T cells, nerve, smooth muscle, globlet, paneth
580,944
90
B014_1.0_90.0
5,475
15,751
5,475
90,751
1
S1
6,485
11,040
S1_6485_11040
Epithelial
580,945
91
B014_1.0_91.0
5,324
15,116
5,324
90,116
1
S1
6,336
10,379
S1_6336_10379
Plasma cells/Epithelial cells/Stromal
580,946
92
B014_1.0_92.0
5,292
16,438
5,292
91,438
1
S1
6,366
11,695
S1_6366_11695
Endothelial
580,947
93
B014_1.0_93.0
3,134
9,172
3,134
84,172
1
S1
4,009
4,663
S1_4009_4663
Epithelial
580,948
95
B014_1.0_95.0
7,100
16,951
7,100
91,951
1
S1
8,260
12,121
S1_8260_12121
endothelial/fibroblast
580,949
96
B014_1.0_96.0
10,967
12,441
10,967
87,441
1
S1
11,920
7,821
S1_11920_7821
endothelial/fibroblast
580,950
99
B014_1.0_99.0
4,957
13,287
4,957
88,287
1
S1
6,134
8,571
S1_6134_8571
null
580,951
102
B014_1.0_102.0
1,195
8,365
1,195
83,365
1
S1
2,134
3,854
S1_2134_3854
Epithelial
580,952
103
B014_1.0_103.0
4,505
9,571
4,505
84,571
1
S1
5,326
5,057
S1_5326_5057
B cells
580,953
104
B014_1.0_104.0
11,613
13,923
11,613
88,923
1
S1
12,614
9,223
S1_12614_9223
endothelial/fibroblast
580,954
105
B014_1.0_105.0
5,855
14,308
5,855
89,308
1
S1
6,958
9,579
S1_6958_9579
Endothelial
580,955
107
B014_1.0_107.0
3,942
6,045
3,942
81,045
1
S1
4,575
1,717
S1_4575_1717
Epithelial
580,956
108
B014_1.0_108.0
4,787
13,367
4,787
88,367
1
S1
5,984
8,644
S1_5984_8644
Epithelial
580,957
109
B014_1.0_109.0
6,124
17,285
6,124
92,285
1
S1
7,283
12,426
S1_7283_12426
Epithelial
580,958
111
B014_1.0_111.0
10,195
8,150
10,195
83,150
1
S1
10,861
3,601
S1_10861_3601
endothelial/fibroblast
580,959
113
B014_1.0_113.0
11,909
15,198
11,909
90,198
1
S1
13,007
10,412
S1_13007_10412
endothelial/fibroblast
580,960
114
B014_1.0_114.0
3,732
11,470
3,732
86,470
1
S1
4,666
6,889
S1_4666_6889
Epithelial
580,961
116
B014_1.0_116.0
5,633
14,252
5,633
89,252
1
S1
6,765
9,517
S1_6765_9517
Epithelial
580,962
117
B014_1.0_117.0
4,840
9,799
4,840
84,799
1
S1
5,659
5,272
S1_5659_5272
B cells
580,963
122
B014_1.0_122.0
2,299
7,278
2,299
82,278
1
S1
3,197
2,805
S1_3197_2805
Epithelial
580,964
123
B014_1.0_123.0
4,834
9,953
4,834
84,953
1
S1
5,666
5,417
S1_5666_5417
B cells
580,965
124
B014_1.0_124.0
6,375
17,915
6,375
92,915
1
S1
7,586
13,095
S1_7586_13095
Epithelial
580,966
127
B014_1.0_127.0
3,958
7,984
3,958
82,984
1
S1
4,692
3,541
S1_4692_3541
endothelial/fibroblast
580,967
128
B014_1.0_128.0
3,636
10,641
3,636
85,641
1
S1
4,582
6,068
S1_4582_6068
Epithelial
580,968
129
B014_1.0_129.0
3,998
10,421
3,998
85,421
1
S1
4,951
5,870
S1_4951_5870
Epithelial
580,969
130
B014_1.0_130.0
9,422
5,634
9,422
80,634
1
S1
9,993
1,245
S1_9993_1245
Smooth muscle/CD138/Epithelial/
580,970
132
B014_1.0_132.0
8,151
13,185
8,151
88,185
1
S1
9,055
8,530
S1_9055_8530
T cells, nerve, smooth muscle, globlet, paneth
580,971
138
B014_1.0_138.0
1,413
8,203
1,413
83,203
1
S1
2,382
3,693
S1_2382_3693
Epithelial
580,972
142
B014_1.0_142.0
4,498
10,687
4,498
85,687
1
S1
5,445
6,130
S1_5445_6130
Epithelial
580,973
143
B014_1.0_143.0
9,884
14,487
9,884
89,487
1
S1
10,866
9,729
S1_10866_9729
Treg
580,974
144
B014_1.0_144.0
5,280
16,821
5,280
91,821
1
S1
6,380
12,036
S1_6380_12036
Fibroblast
580,975
145
B014_1.0_145.0
2,550
8,517
2,550
83,517
1
S1
3,484
4,002
S1_3484_4002
endothelial/fibroblast
580,976
146
B014_1.0_146.0
1,862
10,342
1,862
85,342
1
S1
2,827
5,763
S1_2827_5763
null
580,977
148
B014_1.0_148.0
2,173
9,847
2,173
84,847
1
S1
3,150
5,251
S1_3150_5251
null
580,978
151
B014_1.0_151.0
5,290
13,388
5,290
88,388
1
S1
6,421
8,680
S1_6421_8680
Epithelial
580,979
153
B014_1.0_153.0
4,869
14,903
4,869
89,903
1
S1
5,879
10,185
S1_5879_10185
null
580,980
154
B014_1.0_154.0
10,235
16,997
10,235
91,997
1
S1
11,289
12,162
S1_11289_12162
Endothelial
580,981
155
B014_1.0_155.0
8,481
6,476
8,481
81,476
1
S1
9,091
2,093
S1_9091_2093
Treg
580,982
157
B014_1.0_157.0
5,939
18,067
5,939
93,067
1
S1
7,138
13,248
S1_7138_13248
null
580,983
160
B014_1.0_160.0
6,468
17,631
6,468
92,631
1
S1
7,671
12,797
S1_7671_12797
Smooth muscle
580,984
162
B014_1.0_162.0
10,584
11,446
10,584
86,446
1
S1
11,496
6,869
S1_11496_6869
endothelial/fibroblast
580,985
164
B014_1.0_164.0
3,837
9,042
3,837
84,042
1
S1
4,653
4,568
S1_4653_4568
Endothelial
580,986
169
B014_1.0_169.0
5,741
14,288
5,741
89,288
1
S1
6,858
9,554
S1_6858_9554
null
580,987
170
B014_1.0_170.0
8,169
7,991
8,169
82,991
1
S1
8,847
3,527
S1_8847_3527
T cells, nerve, smooth muscle, globlet, paneth
End of preview.

Space-map example datasets

Serial-section single-cell coordinate datasets used with Space-map for atlas-level 3D reconstruction. Each file is a gzipped CSV of cell coordinates with a per-section layer label.

File Platform / tissue Layer column Coord columns Layers
xenium_colon.csv.gz Xenium (transcriptomics), colon layer (1–20) x, y 20
codex_colon.csv.gz CODEX (proteomics), colon array (S1–S16) x, y 16
codex_duodenum_raw.csv.gz CODEX (proteomics), duodenum — raw index (S1–S16) raw_x, raw_y 16
codex_duodenum_aligned.csv.gz CODEX duodenum — reference aligned layer (S1–S16) x, y 16

Notes:

  • xenium_colon.csv.gz layer labels were renumbered to a contiguous 1–20 range.
  • The two codex_duodenum_* files share row order and layer labels: raw holds the input coordinates, aligned holds a reference alignment for comparison.
  • Additional columns (e.g. cell_type, cell_id) are preserved where present.

Usage

from huggingface_hub import hf_hub_download
import pandas as pd

path = hf_hub_download("a12910/spacemap-data", "xenium_colon.csv.gz",
                       repo_type="dataset")
df = pd.read_csv(path)

See the Space-map repository for registration examples (examples/run_platforms.py).

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