Dataset Preview
Duplicate
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 6 new columns ({'unemployment_rate_pct', 'households', 'gdp_nominal_usd', 'female_population', 'hdi', 'male_population'}) and 35 missing columns ({'gov_revenue_pct_gdp', 'unemployment_pct', 'exports_pct_gdp_lag2', 'unemployment_pct_lag2', 'remittances_pct_gdp', 'unemployment_pct_lag1', 'trade_balance_pct_gdp', 'hcp_datasets_count', 'internet_users_pct', 'health_expenditure_pct_gdp', 'fdi_pct_gdp', 'imports_pct_gdp_lag2', 'gdp_volatility3', 'gdp_per_capita_usd', 'labor_force_participation', 'exports_pct_gdp', 'cpi_index', 'imf_gdp_growth', 'cpi_inflation_pct_lag1', 'gov_expenditure_pct_gdp', 'fertility_rate', 'education_expenditure_pct_gdp', 'urban_population_pct', 'cpi_inflation_pct', 'current_account_pct_gdp', 'electricity_consumption_pc', 'imports_pct_gdp_lag1', 'gdp_real_growth_pct', 'imports_pct_gdp', 'gov_debt_pct_gdp', 'gdp_current_usd', 'gdp_rolling3', 'cpi_inflation_pct_lag2', 'exports_pct_gdp_lag1', 'renewable_energy_pct'}).

This happened while the csv dataset builder was generating data using

hf://datasets/YsfMO98/morocco-economic-v2/wikidata_morocco.csv (at revision 1e39217c174653c3b35ec6671f3a94093cb05628), ['hf://datasets/YsfMO98/morocco-economic-v2@1e39217c174653c3b35ec6671f3a94093cb05628/morocco_indicators_enhanced.csv', 'hf://datasets/YsfMO98/morocco-economic-v2@1e39217c174653c3b35ec6671f3a94093cb05628/wikidata_morocco.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/python3.14/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
              year: int64
              population: double
              hdi: double
              life_expectancy_years: double
              gdp_nominal_usd: double
              unemployment_rate_pct: double
              households: double
              female_population: double
              male_population: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1415
              to
              {'year': Value('int64'), 'gdp_real_growth_pct': Value('float64'), 'gdp_current_usd': Value('float64'), 'gdp_per_capita_usd': Value('float64'), 'cpi_inflation_pct': Value('float64'), 'cpi_index': Value('float64'), 'unemployment_pct': Value('float64'), 'labor_force_participation': Value('float64'), 'exports_pct_gdp': Value('float64'), 'imports_pct_gdp': Value('float64'), 'trade_balance_pct_gdp': Value('float64'), 'current_account_pct_gdp': Value('float64'), 'gov_debt_pct_gdp': Value('float64'), 'gov_expenditure_pct_gdp': Value('float64'), 'gov_revenue_pct_gdp': Value('float64'), 'population': Value('float64'), 'life_expectancy_years': Value('float64'), 'fertility_rate': Value('float64'), 'urban_population_pct': Value('float64'), 'electricity_consumption_pc': Value('float64'), 'renewable_energy_pct': Value('float64'), 'health_expenditure_pct_gdp': Value('float64'), 'education_expenditure_pct_gdp': Value('float64'), 'fdi_pct_gdp': Value('float64'), 'remittances_pct_gdp': Value('float64'), 'internet_users_pct': Value('float64'), 'imf_gdp_growth': Value('float64'), 'hcp_datasets_count': Value('int64'), 'gdp_rolling3': Value('float64'), 'gdp_volatility3': Value('float64'), 'cpi_inflation_pct_lag1': Value('float64'), 'cpi_inflation_pct_lag2': Value('float64'), 'unemployment_pct_lag1': Value('float64'), 'unemployment_pct_lag2': Value('float64'), 'exports_pct_gdp_lag1': Value('float64'), 'exports_pct_gdp_lag2': Value('float64'), 'imports_pct_gdp_lag1': Value('float64'), 'imports_pct_gdp_lag2': 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 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 6 new columns ({'unemployment_rate_pct', 'households', 'gdp_nominal_usd', 'female_population', 'hdi', 'male_population'}) and 35 missing columns ({'gov_revenue_pct_gdp', 'unemployment_pct', 'exports_pct_gdp_lag2', 'unemployment_pct_lag2', 'remittances_pct_gdp', 'unemployment_pct_lag1', 'trade_balance_pct_gdp', 'hcp_datasets_count', 'internet_users_pct', 'health_expenditure_pct_gdp', 'fdi_pct_gdp', 'imports_pct_gdp_lag2', 'gdp_volatility3', 'gdp_per_capita_usd', 'labor_force_participation', 'exports_pct_gdp', 'cpi_index', 'imf_gdp_growth', 'cpi_inflation_pct_lag1', 'gov_expenditure_pct_gdp', 'fertility_rate', 'education_expenditure_pct_gdp', 'urban_population_pct', 'cpi_inflation_pct', 'current_account_pct_gdp', 'electricity_consumption_pc', 'imports_pct_gdp_lag1', 'gdp_real_growth_pct', 'imports_pct_gdp', 'gov_debt_pct_gdp', 'gdp_current_usd', 'gdp_rolling3', 'cpi_inflation_pct_lag2', 'exports_pct_gdp_lag1', 'renewable_energy_pct'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/YsfMO98/morocco-economic-v2/wikidata_morocco.csv (at revision 1e39217c174653c3b35ec6671f3a94093cb05628), ['hf://datasets/YsfMO98/morocco-economic-v2@1e39217c174653c3b35ec6671f3a94093cb05628/morocco_indicators_enhanced.csv', 'hf://datasets/YsfMO98/morocco-economic-v2@1e39217c174653c3b35ec6671f3a94093cb05628/wikidata_morocco.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.

year
int64
gdp_real_growth_pct
float64
gdp_current_usd
float64
gdp_per_capita_usd
float64
cpi_inflation_pct
float64
cpi_index
float64
unemployment_pct
float64
labor_force_participation
float64
exports_pct_gdp
float64
imports_pct_gdp
float64
trade_balance_pct_gdp
float64
current_account_pct_gdp
float64
gov_debt_pct_gdp
float64
gov_expenditure_pct_gdp
float64
gov_revenue_pct_gdp
float64
population
float64
life_expectancy_years
float64
fertility_rate
float64
urban_population_pct
float64
electricity_consumption_pc
float64
renewable_energy_pct
float64
health_expenditure_pct_gdp
float64
education_expenditure_pct_gdp
float64
fdi_pct_gdp
float64
remittances_pct_gdp
float64
internet_users_pct
float64
imf_gdp_growth
null
hcp_datasets_count
int64
gdp_rolling3
float64
gdp_volatility3
float64
cpi_inflation_pct_lag1
float64
cpi_inflation_pct_lag2
float64
unemployment_pct_lag1
float64
unemployment_pct_lag2
float64
exports_pct_gdp_lag1
float64
exports_pct_gdp_lag2
float64
imports_pct_gdp_lag1
float64
imports_pct_gdp_lag2
float64
1,999
1.697061
46,266,428,648.1433
1,635.656738
0.684783
82.094365
13.94
51.314
22.634669
25.944207
-3.309538
-0.360658
55.444981
19.670847
20.606441
28,027,179
66.404
2.882
53.278123
460.267514
15.9
3.693046
4.62528
1.787417
4.189011
0.176
null
49
4.000356
3.253131
0.684783
0.684783
13.94
13.94
22.634669
22.634669
25.944207
25.944207
2,000
2.582181
43,017,455,401.8445
1,499.107422
1.894635
83.649753
13.58
51.322
24.196828
29.243478
-5.04665
-1.10388
55.444981
19.670847
20.606441
28,423,435
66.794
2.774
53.587247
496.421351
15.5
3.693046
4.62528
0.991582
5.023455
0.693791
null
49
4.000356
3.253131
0.684783
0.684783
13.94
13.94
22.634669
22.634669
25.944207
25.944207
2,001
7.721825
43,831,480,207.6444
1,506.245239
0.619802
84.168216
12.46
51.27
25.395545
28.096026
-2.70048
3.675583
55.444981
19.670847
20.606441
28,814,643
67.2
2.686
53.897261
530.598279
15.3
3.816012
4.62528
6.444129
7.439676
1.371438
null
49
4.000356
3.253131
1.894635
0.684783
13.58
13.94
24.196828
22.634669
29.243478
25.944207
2,002
3.730197
47,077,192,187.6418
1,596.02063
2.79562
86.521239
11.59
50.69
25.94438
28.365748
-2.421368
3.137188
48.475079
22.077126
20.582923
29,198,142
67.582
2.617
54.222746
540.719338
15.1
4.061175
4.62528
1.020358
6.111564
2.373253
null
49
4.678068
2.697745
0.619802
1.894635
12.46
13.58
25.395545
24.196828
28.096026
29.243478
2,003
6.171102
58,029,363,354.2757
1,941.872559
1.167734
87.531577
11.92
50.673
24.676487
27.655372
-2.978885
2.725832
48.475079
20.809532
19.670302
29,571,415
67.958
2.606
54.578281
585.802201
16.1
4.080375
4.62528
3.98562
6.227738
3.353367
null
49
5.874375
2.012289
2.79562
0.619802
11.59
12.46
25.94438
25.395545
28.365748
28.096026
2,004
4.57138
66,114,145,451.0067
2,183.55542
1.493444
88.838812
10.83
50.657
25.349206
30.202433
-4.853227
1.466499
48.475079
21.368418
20.435233
29,953,018
68.272
2.611
54.978757
559.008778
22.4
4.232111
4.62528
1.351186
6.384165
11.607935
null
49
4.824227
1.239941
1.167734
2.79562
11.92
11.59
24.676487
25.94438
27.655372
28.365748
2,005
3.19225
68,852,658,068.6673
2,242.988281
0.982642
89.711779
11.01
50.64
27.9959
33.497928
-5.502028
1.511296
53.666297
25.459656
22.4203
30,358,144
68.748
2.613
55.43978
589.693494
20
4.373507
4.62528
2.426355
6.665286
15.084445
null
49
4.644911
1.490787
1.493444
1.167734
10.83
11.92
25.349206
24.676487
30.202433
27.655372
2,006
7.79082
75,883,823,300.8545
2,438.126465
3.284762
92.658597
9.67
50.623
29.628967
35.043231
-5.414264
1.85973
49.57461
22.944239
23.300672
30,771,178
69.157
2.611
55.962759
641.931875
18.2
4.565866
4.62528
3.242835
7.183838
19.771192
null
49
5.184817
2.35986
0.982642
1.493444
11.01
10.83
27.9959
25.349206
33.497928
30.202433
2,007
3.441068
86,947,913,286.728
2,755.585938
2.042085
94.550765
9.56
50.607
31.427774
39.921873
-8.494099
-0.140356
46.303538
23.331035
25.550806
31,186,468
69.62
2.618
56.530384
663.749418
16.6
4.80759
4.62528
3.249993
7.74081
21.5
null
49
4.808046
2.586152
3.284762
0.982642
9.67
11.01
29.628967
27.9959
35.043231
33.497928
2,008
5.684539
101,822,906,949.063
3,183.200439
3.714843
98.063177
9.57
50.59
32.472223
45.362248
-12.890025
-4.447405
41.285131
24.413214
28.091512
31,606,767
70.051
2.612
57.125417
695.325783
14.4
4.837892
4.85339
2.422135
6.770861
33.1
null
49
5.638809
2.175237
2.042085
3.284762
9.56
9.67
31.427774
29.628967
39.921873
35.043231
2,009
3.745769
101,154,952,240.881
3,119.588623
0.971863
99.016217
8.96
50.1
25.717178
36.653778
-10.936601
-4.91457
43.625743
23.986403
25.970798
32,030,778
70.454
2.624
57.730619
709.255329
14.2
5.273122
4.83119
1.947827
6.197539
41.3
null
49
4.290459
1.216884
3.714843
2.042085
9.57
9.56
32.472223
31.427774
45.362248
39.921873
2,010
3.499557
100,865,329,473.44
3,067.985352
0.993557
100
9.09
49.61
29.788949
39.753031
-9.964082
-3.891495
47.098266
25.028145
24.560757
32,467,016
70.821
2.629
58.328752
732.99006
13.9
5.418611
4.83119
1.229982
6.367442
52
null
49
4.309955
1.196773
0.971863
3.714843
8.96
9.57
25.717178
32.472223
36.653778
45.362248
2,011
5.524645
110,080,631,332.375
3,301.98877
0.906925
100.906925
8.91
49.16
31.954484
44.871387
-12.916903
-7.267035
51.226322
27.063999
24.899028
32,912,588
71.263
2.595
58.902577
783.651532
11.8
5.370194
4.83119
2.290468
6.591814
46.107483
null
49
4.256657
1.104989
0.993557
0.971863
9.09
8.96
29.788949
25.717178
39.753031
36.653778
2,012
3.062344
106,937,392,311.129
3,164.177246
1.287122
102.205721
8.99
48.41
32.097096
46.125006
-14.02791
-8.950347
51.226322
27.36872
25.716076
33,355,241
71.674
2.543
59.434856
835.46091
10.9
5.39619
5.552948
2.657587
6.085715
55.416053
null
49
4.028849
1.313714
0.906925
0.993557
8.91
9.09
31.954484
29.788949
44.871387
39.753031
2,013
4.122213
115,739,287,305.08
3,379.743164
1.880655
104.127857
9.23
48.31
30.253266
43.604491
-13.351225
-6.777319
51.226322
25.698716
25.071893
33,787,571
72.117
2.478
59.90835
850.223889
11.6
5.255405
5.552948
2.903863
5.945863
56
null
49
4.236401
1.235116
1.287122
0.906925
8.99
8.91
32.097096
31.954484
46.125006
44.871387
2,014
2.719244
119,130,841,411.664
3,435.406982
0.44231
104.588425
9.7
48.06
30.132987
41.76058
-11.627593
-5.537833
51.226322
25.417034
24.515167
34,204,780
72.522
2.425
60.303049
882.829827
11.1
5.416266
5.48276
2.959254
6.537933
56.774638
null
49
3.301267
0.731364
1.880655
1.287122
9.23
8.99
30.253266
32.097096
43.604491
46.125006
2,015
4.344583
110,413,823,841.592
3,146.247803
1.557907
106.217816
9.46
47.47
29.995854
37.292822
-7.296968
-1.956908
51.226322
23.060608
23.691112
34,607,588
72.894
2.406
60.641712
886.308517
11.2
5.104356
5.133369
2.946111
6.252427
57.079999
null
49
3.72868
0.881239
0.44231
1.880655
9.7
9.23
30.132987
30.253266
41.76058
43.604491
2,016
0.521186
111,572,947,004.917
3,140.855469
1.635311
107.954807
9.3
46.55
30.734595
40.388065
-9.65347
-3.746132
51.226322
22.768587
23.328555
35,023,457
73.228
2.396
60.965766
903.45165
11.1
5.092034
5.085302
1.930005
5.721346
58.271236
null
49
2.528338
1.918835
1.557907
0.44231
9.46
9.7
29.995854
30.132987
37.292822
41.76058
2,017
5.057898
118,540,573,367.844
3,296.526611
0.754663
108.769503
9.22
45.5
32.606461
41.566897
-8.960436
-3.102107
51.226322
22.679271
23.367594
35,446,392
73.608
2.375
61.276106
931.603984
10.4
4.989204
4.73565
2.260922
5.755837
61.762212
null
49
3.307889
2.439568
1.635311
1.557907
9.3
9.46
30.734595
29.995854
40.388065
37.292822
2,018
3.065641
127,341,147,581.818
3,501.697998
1.803917
110.731614
9.272
45.83
33.828437
43.42645
-9.598013
-4.872902
51.226322
22.857507
23.878213
35,839,760
73.946
2.354
61.569582
923.025154
10.9
4.945167
4.960227
2.783379
5.433766
64.803865
null
49
2.881575
2.27395
0.754663
1.635311
9.22
9.3
32.606461
30.734595
41.566897
40.388065
2,019
2.890975
128,920,266,409.458
3,508.097656
0.303386
111.067558
9.191
46.161
34.093057
41.905058
-7.812001
-3.418206
51.226322
23.387678
23.683449
36,210,898
74.245
2.342
61.843045
940.18657
10.7
5.020401
5.003257
1.334798
5.400686
84.120363
null
49
3.671505
1.203824
1.803917
0.754663
9.272
9.22
33.828437
32.606461
43.42645
41.566897
2,020
-7.178207
121,353,645,057.144
3,268.030273
0.705969
111.85166
11.189
44.539
30.794107
38.049696
-7.255589
-1.127599
51.226322
27.210212
26.564914
36,584,208
73.133
2.32
62.093344
916.187662
11.1
5.789395
6.284283
1.169073
6.109531
84.120363
null
49
-0.407197
5.864517
0.303386
1.803917
9.191
9.272
34.093057
33.828437
41.905058
43.42645
2,021
8.154739
142,022,058,447.231
3,785.936279
1.401959
113.419775
10.551
45.3
33.136085
42.387332
-9.251247
-2.357868
51.226322
25.630847
24.211225
36,954,442
73.385
2.288
62.317328
950.467605
10.9
5.453145
5.642734
1.594223
7.679285
88.130319
null
49
1.289169
7.790966
0.705969
0.303386
11.189
9.191
30.794107
34.093057
38.049696
41.905058
2,022
1.812692
131,245,312,804.483
3,463.137695
6.657042
120.970177
9.413
44.3
44.711628
56.194682
-11.483054
-3.657491
51.226322
28.144875
26.827845
37,329,064
75.161
2.256
62.511847
978.272587
10.9
5.75281
5.912247
1.748143
8.511103
89.9
null
49
0.929741
7.704513
1.401959
0.705969
10.551
11.189
33.136085
30.794107
42.387332
38.049696
2,023
3.655644
146,036,093,666.762
3,813.726074
6.091142
128.338641
8.896
44.224
42.417603
50.700281
-8.282678
-1.047678
51.226322
26.611138
26.152231
37,712,505
75.313
2.23
62.673751
997.25542
10.9
6.063962
6.020969
0.725864
8.045684
91
null
49
4.541025
3.262409
6.657042
1.401959
9.413
10.551
44.711628
33.136085
56.194682
42.387332
2,024
3.793365
160,610,994,054.734
4,153.194336
0.985257
129.603106
9.103
44.129
41.998523
50.188721
-8.190198
-1.230721
51.226322
26.611138
26.152231
38,081,173
75.493
2.208
62.799812
997.25542
10.9
6.063962
6.020969
1.088504
7.788403
91.2
null
49
3.087234
1.105931
6.091142
6.657042
8.896
9.413
42.417603
44.711628
50.700281
56.194682
2,025
4.595243
182,374,250,612.28
4,672.468262
0.701902
130.512793
9
43.941
41.969214
51.132443
-9.163229
-2.498082
51.226322
26.611138
26.152231
38,430,770
75.493
2.208
63.127861
997.25542
10.9
6.063962
6.020969
1.819545
7.488222
91.2
null
49
4.014751
0.507416
0.985257
6.091142
9.103
8.896
41.998523
42.417603
50.188721
50.700281
2,026
4.595243
182,374,250,612.28
4,672.468262
0.701902
130.512793
9
43.941
41.969214
51.132443
-9.163229
-2.498082
51.226322
26.611138
26.152231
38,430,770
75.493
2.208
63.127861
997.25542
10.9
6.063962
6.020969
1.819545
7.488222
91.2
null
49
4.327951
0.462965
0.701902
0.985257
9
9.103
41.969214
41.998523
51.132443
50.188721
1,960
null
null
null
null
null
null
null
null
null
null
null
null
null
null
12,328,534
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,961
null
null
null
null
null
null
null
null
null
null
null
null
null
null
12,687,467
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,962
null
null
null
null
null
null
null
null
null
null
null
null
null
null
13,039,318
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,963
null
null
null
null
null
null
null
null
null
null
null
null
null
null
13,387,425
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,964
null
null
null
null
null
null
null
null
null
null
null
null
null
null
13,737,160
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,965
null
null
null
null
null
null
null
null
null
null
null
null
null
null
14,092,269
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,966
null
null
null
null
null
null
null
null
null
null
null
null
null
null
14,454,566
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,967
null
null
null
null
null
null
null
null
null
null
null
null
null
null
14,822,362
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,968
null
null
null
null
null
null
null
null
null
null
null
null
null
null
15,191,876
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,969
null
null
null
null
null
null
null
null
null
null
null
null
null
null
15,557,664
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,970
null
null
null
null
null
null
null
null
null
null
null
null
null
null
15,916,387
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,971
null
null
null
null
null
null
null
null
null
null
null
null
null
null
16,266,807
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,972
null
null
null
null
null
null
null
null
null
null
null
null
null
null
16,611,970
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,973
null
null
null
null
null
null
null
null
null
null
null
null
null
null
16,958,091
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,974
null
null
null
null
null
null
null
null
null
null
null
null
null
null
17,313,732
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,975
null
null
null
null
null
null
null
null
null
null
null
null
null
null
17,685,326
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,976
null
null
null
null
null
null
null
null
null
null
null
null
null
null
18,074,081
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,977
null
null
null
null
null
null
null
null
null
null
null
null
null
null
18,478,909
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,978
null
null
null
null
null
null
null
null
null
null
null
null
null
null
18,900,970
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,979
null
null
null
null
null
null
null
null
null
null
null
null
null
null
19,340,967
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,980
null
null
null
null
null
null
null
null
null
null
null
null
null
null
19,798,703
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,981
null
null
null
null
null
null
null
null
null
null
null
null
null
null
20,274,839
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,982
null
null
null
null
null
null
null
null
null
null
null
null
null
null
20,767,511
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,983
null
null
null
null
null
null
null
null
null
null
null
null
null
null
21,270,638
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,984
null
null
null
null
null
null
null
null
null
null
null
null
null
null
21,776,104
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,985
null
null
null
null
null
null
null
null
null
null
null
null
null
null
22,277,541
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,986
null
null
null
null
null
null
null
null
null
null
null
null
null
null
22,772,287
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,987
null
null
null
null
null
null
null
null
null
null
null
null
null
null
23,260,094
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,988
null
null
null
null
null
null
null
null
null
null
null
null
null
null
23,739,980
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,989
null
null
null
null
null
null
null
null
null
null
null
null
null
null
24,211,718
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,990
null
null
null
null
null
null
null
null
null
null
null
null
null
null
24,674,974
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,991
null
null
null
null
null
null
null
null
null
null
null
null
null
null
25,128,064
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,992
null
null
null
null
null
null
null
null
null
null
null
null
null
null
25,569,662
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,993
null
null
null
null
null
null
null
null
null
null
null
null
null
null
26,000,345
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,994
null
null
null
null
null
null
null
null
null
null
null
null
null
null
26,421,309
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,995
null
null
null
null
null
null
null
null
null
null
null
null
null
null
26,833,093
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,996
null
null
null
null
null
null
null
null
null
null
null
null
null
null
27,237,150
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,997
null
null
null
null
null
null
null
null
null
null
null
null
null
null
27,632,321
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,998
null
null
null
null
null
null
null
null
null
null
null
null
null
null
28,013,585
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
1,999
null
null
null
null
null
null
null
null
null
null
null
null
null
null
28,374,203
68.284
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,000
null
null
null
null
null
null
null
null
null
null
null
null
null
null
28,710,123
68.722
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,001
null
null
null
null
null
null
null
null
null
null
null
null
null
null
29,021,156
69.209
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,002
null
null
null
null
null
null
null
null
null
null
null
null
null
null
29,311,443
69.738
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,003
null
null
null
null
null
null
null
null
null
null
null
null
null
null
29,586,937
70.296
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,004
null
null
null
null
null
null
null
null
null
null
null
null
null
null
29,855,820
70.873
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,005
null
null
null
null
null
null
null
null
null
null
null
null
null
null
30,125,445
71.456
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,006
null
null
null
null
null
null
null
null
null
null
null
null
null
null
30,395,097
72.029
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,007
null
null
null
null
null
null
null
null
null
null
null
null
null
null
30,667,086
72.58
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,008
null
null
null
null
null
null
null
null
null
null
null
null
null
null
30,955,151
73.097
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,009
null
null
null
null
null
null
null
null
null
null
null
null
null
null
31,276,564
73.572
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,010
null
null
null
null
null
null
null
null
null
null
null
null
null
null
31,642,360
73.999
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,011
null
null
null
null
null
null
null
null
null
null
null
null
null
null
32,059,424
74.377
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,012
null
null
null
null
null
null
null
null
null
null
null
null
null
null
32,521,143
74.717
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,013
null
null
null
null
null
null
null
null
null
null
null
null
null
null
33,008,150
75.026
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,014
null
null
null
null
null
null
null
null
null
null
null
null
null
null
33,848,242
75.309
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,015
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
75.573
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,016
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
75.821
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,017
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,018
null
null
null
null
null
null
null
null
null
null
null
null
null
null
36,029,138
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,019
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,020
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,021
null
null
null
null
null
null
null
null
null
null
null
null
null
null
37,076,584
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,022
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,023
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
75.31
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
2,024
null
null
null
null
null
null
null
null
null
null
null
null
null
null
36,828,330
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null

Morocco Economic V2 (HCP + WB + IMF)

Enhanced Morocco socio-economic dataset with 38 indicators from 3 official sources.

Sources

  • World Bank (WDI): 25 indicators (GDP, inflation, trade, FDI, remittances...)
  • IMF WEO: GDP growth forecasts
  • HCP (data.gov.ma): 49 official Moroccan datasets downloaded

Indicators (38 columns)

  • GDP: real growth, current USD, per capita
  • Inflation: CPI index, CPI inflation
  • Employment: unemployment, labor force participation
  • Trade: exports, imports, trade balance
  • Fiscal: government debt, expenditure, revenue
  • Social: population, life expectancy, fertility, urbanization
  • Energy: electricity consumption, renewable energy
  • Finance: FDI, remittances, current account
  • Digital: internet users
  • Features: lag features, rolling averages, volatility

Years: 1999-2026 (28 rows)

Usage

import pandas as pd
df = pd.read_csv("morocco_indicators_enhanced.csv")

License: CC0-1.0

Downloads last month
48