Click here to Login |
Contact us |
User Guide |
Home
English
|
Français
Search
Getting Started
Combine Queries
Data Basket Empty
Data by theme
Popular queries
Reset
Choose Theme
All Themes
General Statistics
Agriculture and Fisheries
Demography and Population
Development
Economic Projections
Education and Training
Environment
Finance
Globalisation
Health
Industry and Services
Information and Communication Technology
International Trade and Balance of Payments
Labour
National Accounts
Monthly Economic Indicators
Productivity
Prices and Purchasing Power Parities
Public Sector, Taxation and Market Regulation
Regions and Cities
Science, Technology and Patents
Social Protection and Well-being
Transport
Regions and Cities
Regional Statistics
Short-term regional statistics
Short-term labour statistics
Excess mortality rate
Vaccination rates COVID-19
Regional Demography
Demographic indicators by access to city typology, Country level
Life Expectancy and Mortality, large TL2 and small TL3 regions
Mortality crude rates by cause of death, large TL2 regions
Population by 5-year age groups, large regions TL2
Deaths by 5-year age groups, small regions TL3
Demographic Composition and Evolution, large TL2 and small TL3 regions
Demographic indicators by rural/urban typology, Country level
Inter-regional Mobility, large TL2 and small TL3 regions
Population by 5-year age groups, small regions TL3
Population density and area, large TL2 and small TL3 regions
Regional Labour
Labour indicators, Large regions TL2
Labour indicators, Small regions TL3
Part-Time Employment, Large regions TL2
Employment at place of residence
Highest and Lowest regional values by TL2
Labour Force and Participation rate
Labour indicators by access to city typology, Country level
Labour indicators by rural/urban typology, Country level
Unemployment, Large regions TL2
Youth and Long Term Unemployment
Regional Economy
Gross Domestic Product, Large regions TL2
Average annual population (used for per capita measures)
Economic indicators by access to city typology, Country level
Economic indicators by rural/urban typology, Country level
Gross Domestic Product, Small regions TL3
GVA by industry, large TL2 and small TL3 regions
Labour utilisation rate
Reference series - deflators and PPP rates
Regional Employment by industry (ISIC rev 4)
Regional GVA per worker
Regional income per capita
Regional income per equivalised household, Large regions TL2
Regional Education
Educational attainment of the population, by age group
Employment rate, by level of educational attainment and age group
Participation in formal and/or non-formal education and learning
Enrolment rate by age
Early leavers from education and NEET
Regional Innovation
Educational Attainments of the Labour Force
Patent Applications in regions (PCT, priority year)
Patent applications by sector
Patents collaboration by regional location (total count)
Knowledge and high technology industries
R&D Expenditures by performing sector
R&D Personnel by Sector
Student Enrolment by Level of Education
Regional Business Demography
Employer enterprise demography by access to city typology, Country level
Employer enterprise demography by rural/urban typology, Country level
Establishment Regional Demography - Country view
Employer enterprise demography, Large TL2 and small TL3 regions
Enterprise Demography (all firms, incl. non employer)
Establishment Regional Demography
Regional Social and Environmental indicators
Health Access
Environmental indicators in regions
Exclusion indicators
Housing indicators
Internet broadband access
Safety in regions
Voters Turnout in regions
Database on Migrants in OECD Regions
Foreign-Born - Socio-demographic chararacteristics
Foreign- and Native-Born Populations by 10 year age groups
Foreign-Born Labour Market
Foreign-Born Education
Regional Well-Being
Regional Well-Being
Regional Well-Being
Regional income distribution and poverty
Subnational government structure and finance
Subnational governments in OECD countries: key data
1. Socio-economic data
2. SNG and municipal structure
3. SNG expenditures
4. SNG expenditures by category
5. SNG expenditures and investment by function
6. SNG investment
7. SNG revenue
8. SNG revenue by type
9. SNG budget balance and debt
Regional Government Finance and Investment Database
Metropolitan areas
Population
Crime
Digitalization
Income distribution
Economy
Environment
Labour
Population by age groups
Territorial organization
TiVA 2021: Principal Indicators
Economic Outlook
Gross domestic product (annual)
Gross domestic product (quarterly)
Composite Leading Indicators
Consumer price indices - inflation
Health Status
Labour Market Statistics
Monthly Monetary and Financial Statistics (MEI)
Agricultural Outlook
Bilateral Trade by Industry and End-use (ISIC4)
Statistics from A to Z
>> Data by theme
This dataset preview is momentarily unavailable.
Please try again or select another dataset.
Metropolitan areas
Customise
Selection…
Metropolitan areas [730 / 730]
Variables [8 / 89]
Year [22]
Layout
Table options
Export
Excel
Text file (CSV)
PC-axis
Developer API
SDMX (XML)
Related files
My Queries
Save
Combine
Manage
Page:
1
2
3
4
5
6
7
/7
Variables
Population, all ages, administrative data
Population of the core area
Population of the hinterland area
Growth/shrinking index of the total population (2001=100)
Population of the metropolitan area as a share of the national population
Population density (inhabitants per km2)
Population density of the core area (inhabitants per km2)
Population density of the hinterland area (inhabitants per km2)
Unit
Persons
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Metropolitan areas
AUS: Australia
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
AUS01: Greater Sydney
..
4 102 580
4 135 637
4 162 593
4 184 763
4 217 563
4 256 161
4 325 525
4 409 562
4 492 380
4 555 516
4 608 949
4 677 196
4 757 364
4 841 349
4 930 189
5 024 923
5 136 919
5 225 098
5 310 099
5 367 206
..
AUS02: Greater Melbourne
..
3 500 249
3 545 579
3 594 031
3 641 951
3 697 372
3 760 760
3 841 760
3 931 438
4 031 787
4 105 857
4 169 366
4 265 843
4 370 067
4 476 030
4 586 012
4 714 387
4 843 928
4 964 713
5 079 123
5 159 211
..
AUS03: Greater Brisbane
..
1 693 556
1 735 730
1 780 650
1 823 496
1 866 210
1 908 265
1 958 907
2 012 204
2 068 479
2 108 348
2 147 436
2 196 288
2 241 944
2 281 740
2 318 653
2 362 672
2 412 517
2 461 597
2 513 806
2 560 720
..
AUS04: Greater Perth
..
1 455 361
1 474 536
1 496 016
1 520 232
1 544 977
1 576 912
1 628 467
1 682 860
1 739 342
1 781 132
1 833 567
1 892 862
1 943 855
1 973 923
1 998 937
2 019 263
2 037 902
2 058 568
2 087 555
2 125 114
..
AUS05: Greater Adelaide
..
1 148 006
1 154 981
1 162 250
1 168 541
1 177 345
1 189 243
1 204 210
1 219 523
1 237 354
1 253 097
1 264 091
1 277 850
1 289 696
1 302 079
1 313 419
1 324 057
1 334 438
1 345 860
1 360 474
1 376 601
..
AUS06: Gold Coast
..
390 177
405 477
422 113
435 960
448 933
462 573
479 818
494 599
509 133
519 630
528 766
542 072
554 567
564 952
576 016
589 933
606 073
621 798
636 035
650 996
..
AUS07: Canberra
..
321 538
324 627
327 357
328 940
331 399
335 170
342 644
348 368
354 785
361 766
367 985
376 539
383 257
388 799
395 813
403 104
412 025
420 379
426 285
431 380
..
AUS08: Newcastle
..
400 509
404 000
407 476
410 167
412 756
414 592
418 949
423 741
428 766
433 597
438 522
442 072
445 887
449 806
452 929
456 395
460 759
465 338
470 135
476 583
..
AUS10: Wollongong
..
252 537
254 785
256 147
256 712
257 196
257 646
260 133
263 853
267 219
270 661
272 923
274 564
277 146
279 901
282 672
285 688
289 465
293 206
296 701
299 989
..
AUS14: Geelong
..
222 969
226 737
229 493
231 658
233 794
236 055
239 456
243 415
247 731
252 091
256 580
261 251
266 726
272 154
278 436
286 384
293 975
301 832
310 133
317 857
..
AUT: Austria
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
AT001: Vienna
..
..
2 518 900
2 545 953
2 571 147
2 603 478
2 633 622
2 651 048
2 669 653
2 687 263
2 702 410
2 720 884
2 741 423
2 771 168
2 804 165
2 844 897
2 901 726
2 939 030
2 967 197
2 983 513
3 004 660
3 022 500
AT002: Graz
..
..
568 224
572 564
576 920
583 010
588 413
592 661
596 744
600 619
604 354
608 948
613 579
618 467
624 540
631 194
640 574
647 531
652 485
657 316
662 531
665 390
AT003: Linz
..
..
591 621
594 743
597 624
601 456
604 788
607 231
608 882
610 593
611 788
612 547
615 347
618 431
622 945
629 153
637 739
643 455
647 800
651 950
655 268
657 095
AT004: Salzburg
..
..
339 265
339 431
341 728
344 070
346 562
348 289
348 571
349 919
350 261
351 577
353 263
355 448
357 837
361 479
367 279
370 368
373 262
375 489
378 171
380 146
AT005: Innsbruck
..
..
303 798
305 285
307 289
310 318
313 371
315 496
316 900
318 760
320 813
322 786
325 464
329 174
333 280
338 352
345 143
348 723
351 215
352 507
353 941
354 699
AT006: Klagenfurt
..
..
244 805
245 088
245 078
246 261
247 014
247 443
248 119
248 796
248 553
248 567
248 854
249 445
250 334
251 839
253 761
254 574
255 079
255 519
256 003
256 857
BEL: Belgium
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
BE001: Brussels
2 769 461
2 781 804
2 804 458
2 827 467
2 843 811
2 862 117
2 886 716
2 914 916
2 945 854
3 004 212
3 041 084
3 089 022
3 124 065
3 152 112
3 172 245
3 196 299
3 222 431
3 239 670
3 260 987
3 284 548
3 310 251
3 322 650
BE002: Antwerp
1 012 059
1 011 754
1 015 752
1 021 202
1 025 622
1 030 199
1 036 465
1 043 208
1 051 648
1 060 707
1 069 023
1 082 500
1 094 846
1 102 492
1 107 980
1 113 745
1 120 439
1 127 171
1 133 255
1 139 663
1 146 565
1 148 671
BE003: Gent
573 863
574 948
576 892
579 040
581 152
584 173
588 486
592 275
597 251
601 508
607 530
614 134
617 197
619 452
623 185
627 460
632 921
637 132
640 828
645 813
649 716
651 569
BE004: Charleroi
490 065
489 387
489 897
490 138
490 777
492 133
492 911
494 281
495 268
497 237
498 901
501 467
503 353
504 668
504 609
505 209
505 466
505 179
506 096
506 620
507 107
506 282
BE005: Liege
733 987
733 759
736 032
736 528
738 937
741 396
744 995
749 663
753 644
758 042
763 206
770 104
774 678
778 308
781 645
784 042
787 156
789 989
791 850
793 118
795 113
794 052
BE007: Namur
239 210
240 254
241 254
242 682
244 268
245 877
247 210
249 009
250 620
252 656
254 315
256 296
257 910
259 292
260 219
261 584
262 671
263 712
264 986
265 753
266 796
267 592
BGR: Bulgaria
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
BG001: Sofia
1 482 405
1 488 664
1 460 718
1 473 836
1 485 334
1 494 724
1 503 007
1 510 219
1 516 932
1 524 058
1 531 454
1 537 727
1 539 994
1 542 927
1 547 644
1 551 663
1 552 980
1 553 835
1 553 081
1 553 106
1 551 056
..
BG002: Plovdiv
585 746
584 782
571 682
568 322
565 175
562 603
559 847
557 068
554 618
552 367
550 746
548 688
546 750
545 125
544 592
542 496
540 646
539 273
537 846
536 672
535 441
..
BG003: Varna
376 681
372 373
396 620
397 605
398 743
399 825
400 853
401 955
402 974
403 990
405 273
405 933
405 564
404 770
405 335
405 102
404 352
404 119
403 663
402 920
401 752
..
BG004: Burgas
280 212
279 040
277 209
276 365
275 756
275 278
274 788
274 358
273 990
273 606
273 473
272 836
272 205
271 685
271 902
271 705
271 508
270 721
269 996
269 177
268 478
..
CAN: Canada
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
CAN01: Toronto
..
5 699 947
5 837 915
5 936 721
6 036 606
6 133 751
6 239 933
6 328 403
6 422 259
6 515 751
6 617 633
6 712 184
6 807 189
6 895 647
6 970 817
7 026 425
7 120 321
7 224 189
7 356 925
7 498 434
7 604 848
..
CAN02: Montreal
..
3 833 389
3 873 667
3 907 100
3 942 396
3 974 007
4 010 654
4 048 200
4 090 001
4 141 813
4 192 403
4 236 554
4 276 966
4 313 755
4 342 676
4 361 056
4 395 130
4 451 009
4 527 585
4 599 452
4 637 176
..
CAN03: Vancouver
..
2 069 794
2 093 463
2 110 829
2 128 373
2 153 701
2 183 524
2 211 838
2 248 305
2 295 842
2 338 763
2 369 294
2 413 301
2 453 584
2 501 415
2 538 348
2 575 988
2 610 493
2 651 874
2 700 025
2 730 780
..
CAN04: Ottawa
..
1 246 312
1 263 101
1 278 801
1 290 273
1 300 839
1 309 159
1 324 809
1 345 197
1 366 859
1 390 939
1 412 217
1 427 568
1 440 894
1 453 700
1 464 997
1 486 404
1 510 712
1 538 334
1 566 483
1 591 252
..
CAN05: Calgary
..
1 065 408
1 098 280
1 122 833
1 148 992
1 187 062
1 228 613
1 263 822
1 299 931
1 336 732
1 359 701
1 384 554
1 423 786
1 470 901
1 514 984
1 544 221
1 570 523
1 591 385
1 617 001
1 648 521
1 678 718
..
CAN06: Edmonton
..
994 103
1 016 844
1 033 646
1 049 990
1 075 348
1 106 987
1 137 407
1 165 037
1 196 420
1 216 902
1 238 671
1 267 176
1 305 412
1 345 705
1 372 203
1 398 763
1 423 081
1 447 637
1 474 072
1 499 101
..
CAN07: Quebec
..
776 316
781 618
786 052
790 598
795 482
801 963
811 252
822 190
833 604
845 344
856 336
863 089
869 847
875 751
881 171
887 952
894 360
901 992
910 973
919 207
..
CAN08: Winnipeg
..
759 569
763 842
768 392
774 866
778 086
782 248
786 092
790 057
797 283
804 582
814 645
826 551
836 698
847 161
857 182
873 361
890 123
904 275
916 217
922 229
..
CAN09: Hamilton
..
590 629
596 865
602 122
605 867
608 620
609 004
609 533
612 018
614 731
618 262
621 450
624 954
628 776
632 373
636 152
642 171
650 754
659 677
668 798
676 736
..
CAN10: London
..
519 875
525 387
529 450
534 476
538 654
542 966
545 423
548 547
550 201
553 256
555 950
559 060
561 208
564 150
568 022
576 626
588 367
601 588
612 434
621 999
..
CAN11: Kitchener
..
481 215
489 916
497 069
506 234
514 491
523 342
527 980
533 234
537 356
542 663
548 554
553 695
558 510
562 679
567 545
579 198
591 253
606 094
620 649
632 842
..
CAN12: Halifax
..
423 453
428 660
432 438
435 312
436 492
439 473
441 316
444 809
448 735
453 801
457 708
460 154
461 222
462 429
463 336
469 278
477 139
485 463
495 040
504 024
..
CAN13: Victoria
..
340 622
342 921
345 350
347 738
351 006
355 474
357 565
360 330
364 339
367 855
368 581
375 308
381 882
387 746
393 977
402 596
408 754
414 978
421 679
427 506
..
CAN14: Windsor
..
362 253
368 861
373 021
376 397
378 636
378 897
377 782
374 698
370 748
370 422
370 377
372 117
376 062
377 605
378 959
383 307
386 434
392 423
396 833
400 991
..
CAN15: Saskatoon
..
225 537
227 312
228 879
231 214
232 711
234 749
238 771
243 924
250 176
256 677
263 319
271 803
278 517
284 553
289 473
297 391
304 922
311 785
318 373
323 875
..
CAN16: Sherbrooke
..
229 249
231 396
233 580
235 567
237 257
238 821
240 679
242 552
245 149
247 939
250 738
252 724
254 476
255 884
256 821
259 381
261 571
264 551
267 897
271 624
..
CHE: Switzerland
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
CH001: Zurich
1 076 299
1 133 849
1 145 439
1 157 029
1 168 619
1 180 209
1 191 800
1 203 390
1 214 980
1 226 570
1 238 160
1 249 750
1 266 313
1 280 944
1 296 646
1 315 669
1 334 269
1 354 140
1 369 041
1 384 728
1 401 783
1 414 771
CH002: Geneva
471 590
485 651
491 563
497 475
503 387
509 299
515 212
521 124
527 036
532 948
538 860
544 772
549 411
552 305
560 285
570 222
579 227
585 400
592 060
597 269
603 204
606 748
CH003: Basel
497 081
501 790
503 734
505 678
507 622
509 566
511 510
513 453
515 397
517 341
519 285
521 229
523 992
527 225
532 185
537 051
541 011
545 326
547 761
550 152
552 863
555 526
CH004: Bern
374 485
387 380
387 861
388 341
388 822
389 303
389 784
390 264
390 745
391 226
391 706
392 187
394 859
399 159
403 393
407 144
411 198
415 784
418 525
419 983
422 129
424 161
CH005: Lausanne
310 924
348 387
351 465
354 542
357 620
360 698
363 776
366 853
369 931
373 009
376 086
379 164
385 643
389 618
397 538
402 874
409 290
415 596
420 757
424 622
427 850
433 676
CHL: Chile
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
CL004: Antofagasta
..
..
300 303
305 302
310 271
315 097
319 944
325 014
330 287
335 467
340 633
345 973
351 234
356 933
363 207
369 028
374 882
381 635
395 387
410 618
425 725
433 712
CL006: Coquimbo-La Serena
..
..
350 065
357 592
365 205
372 917
380 828
388 828
397 283
406 196
415 374
424 852
434 560
444 242
454 156
464 253
474 125
484 341
495 466
506 847
518 182
528 074
CL010: Valparaiso
..
..
893 007
902 445
911 629
920 631
929 669
938 877
948 575
958 547
968 609
978 852
989 379
998 919
1 008 687
1 018 876
1 028 935
1 040 298
1 053 101
1 066 313
1 079 318
1 089 321
CL011: Santiago
..
..
6 169 568
6 239 575
6 309 965
6 377 577
6 446 603
6 517 770
6 592 538
6 666 632
6 739 593
6 816 491
6 894 165
6 957 877
7 025 923
7 100 158
7 186 990
7 322 872
7 513 321
7 721 712
7 927 699
8 042 097
CL014: Rancagua
..
..
309 636
313 575
317 775
322 070
326 437
330 990
335 858
340 860
345 916
350 984
356 022
360 926
365 822
370 813
375 963
381 585
387 367
393 205
398 952
403 755
CL017: Talca
..
..
227 833
230 597
233 468
236 398
239 445
242 708
246 198
249 914
253 744
257 695
261 599
265 565
269 646
273 955
278 299
282 854
287 513
292 164
296 724
300 737
CL020: Concepcion
..
..
875 850
881 465
887 121
892 849
898 790
905 332
912 074
919 205
926 553
934 192
941 298
947 741
954 261
960 914
967 415
973 473
979 538
985 593
991 420
995 992
CL022: Temuco
..
..
376 419
380 981
385 513
389 940
394 327
398 817
403 393
408 150
412 773
417 500
422 172
426 403
430 660
435 118
439 416
443 737
448 054
452 348
456 553
460 203
CL025: Puerto Montt
..
..
182 575
188 364
194 013
199 531
205 025
210 384
215 871
221 363
226 627
231 795
236 727
241 293
245 735
250 087
254 391
258 579
262 245
265 863
269 398
272 555
COL: Colombia
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
COL01: Bogota D.C.
6 732 825
6 868 651
6 996 637
7 118 673
7 236 153
7 350 938
7 464 831
7 573 797
7 678 106
7 780 285
7 880 199
7 973 180
8 056 860
8 132 962
8 204 660
8 275 953
8 360 041
8 458 904
8 606 595
8 873 361
9 102 358
9 246 786
COL02: Medellin
2 871 521
2 924 226
2 975 712
3 026 394
3 076 608
3 125 705
3 176 762
3 227 303
3 277 752
3 328 504
3 380 314
3 431 457
3 481 263
3 529 771
3 578 863
3 628 775
3 683 545
3 744 028
3 818 089
3 915 980
4 000 949
4 063 807
COL03: Cali
2 267 533
2 290 715
2 312 259
2 333 071
2 354 114
2 376 086
2 397 982
2 417 557
2 433 988
2 449 622
2 465 405
2 480 920
2 494 493
2 505 571
2 516 661
2 529 036
2 543 247
2 557 800
2 586 678
2 607 722
2 624 043
2 638 246
COL04: Barranquilla
1 736 790
1 768 985
1 800 130
1 830 258
1 859 878
1 889 367
1 917 569
1 945 369
1 972 221
1 998 615
2 024 576
2 049 524
2 073 576
2 097 472
2 120 851
2 145 204
2 175 623
2 213 083
2 273 642
2 366 223
2 441 942
2 485 915
COL05: Cartagena
955 855
974 527
992 708
1 010 018
1 026 738
1 042 759
1 058 475
1 073 449
1 086 984
1 103 644
1 116 703
1 129 053
1 140 835
1 152 286
1 163 229
1 174 360
1 186 968
1 201 731
1 223 368
1 263 650
1 296 411
1 315 555
COL06: Bucaramanga
857 887
877 880
897 720
917 071
936 587
955 742
975 401
994 787
1 013 781
1 032 540
1 051 262
1 069 256
1 086 737
1 104 028
1 120 986
1 138 187
1 157 001
1 177 635
1 204 093
1 240 794
1 270 187
1 284 495
COL07: Cucuta
717 262
730 891
743 588
755 618
766 856
777 656
788 247
798 393
807 766
816 455
824 615
832 084
838 893
845 544
851 555
857 686
867 669
881 969
909 736
957 681
993 370
1 007 156
COL08: Pereira
578 451
585 973
592 813
599 198
605 577
611 906
618 321
624 456
629 698
634 975
640 586
645 979
650 920
655 193
659 462
664 670
670 625
676 831
684 447
693 177
700 809
706 357
COL09: Ibague
444 266
450 923
457 111
463 139
468 632
473 220
478 255
482 895
487 511
492 013
496 428
500 754
504 843
508 870
512 749
516 759
520 856
525 076
529 635
536 087
541 101
542 724
COL10: Manizales
440 641
443 688
446 490
449 060
451 372
453 125
455 219
457 664
460 085
462 626
465 633
468 697
471 895
475 240
478 927
482 731
487 469
492 748
499 055
506 797
513 589
518 094
COL11: Santa Marta
351 041
363 433
371 261
379 029
386 883
394 687
402 708
410 646
418 511
426 275
433 916
441 291
448 452
455 526
462 394
469 272
477 190
486 246
499 192
521 239
538 612
546 979
COL12: Pasto
344 512
349 707
353 375
356 963
360 469
363 816
367 356
370 582
373 304
375 760
378 072
380 245
382 333
384 087
385 710
387 388
389 184
390 727
392 930
392 748
392 589
392 567
COL13: Armenia
360 692
363 001
364 900
366 487
367 951
369 359
370 964
372 356
373 590
374 815
376 306
378 034
379 683
381 222
383 000
385 105
387 932
391 474
396 153
402 697
408 714
413 672
COL14: Villavicencio
331 663
345 880
359 715
372 957
385 719
398 309
410 314
421 747
432 864
443 635
454 178
464 527
474 503
484 216
493 721
503 042
512 462
521 700
531 275
538 824
545 302
549 922
COL15: Monteria
385 065
392 259
399 292
406 055
412 751
419 219
425 734
432 186
434 989
440 801
446 519
452 158
457 571
462 946
468 171
473 413
478 806
484 400
490 935
498 858
505 334
509 558
COL16: Valledupar
334 100
341 894
350 235
359 142
368 337
377 260
386 014
394 429
402 539
410 263
417 914
425 252
432 509
439 872
447 218
454 906
463 923
474 596
490 075
513 685
532 956
544 134
COL17: Buenaventura
276 643
278 922
281 018
283 050
285 118
287 378
289 561
291 494
293 067
294 554
296 080
297 593
298 906
299 904
300 895
302 099
303 516
305 003
308 188
310 194
311 827
313 508
COL18: Neiva
287 912
292 050
296 036
299 865
303 633
307 365
311 129
314 910
318 661
322 439
326 219
330 022
333 717
337 452
341 232
345 066
349 048
352 999
357 392
361 049
364 408
367 400
COL19: Palmira
310 949
313 701
316 254
318 691
321 229
323 868
326 564
328 949
330 898
332 743
334 667
336 520
338 121
339 398
340 670
342 079
343 835
345 649
349 294
352 016
354 285
356 259
COL20: Popayan
249 792
256 541
260 679
264 657
268 568
272 261
276 137
276 645
282 115
285 751
289 412
292 988
296 431
299 819
303 267
306 782
310 409
314 054
318 059
321 991
325 477
328 139
COL21: Sincelejo
219 691
223 225
225 038
229 035
232 250
235 222
238 311
241 380
244 436
247 432
250 413
253 394
256 326
259 277
262 199
265 212
268 622
272 534
277 773
286 635
293 951
298 062
COL25: Riohacha
134 226
135 869
136 588
136 682
136 704
137 204
138 725
140 977
143 929
147 265
150 847
154 539
158 325
162 196
166 070
170 031
174 676
180 175
188 014
195 747
201 839
206 435
CZE: Czech Republic
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
CZ001: Prague
1 944 232
1 934 802
1 923 769
1 926 524
1 932 646
1 940 840
1 958 887
1 974 540
2 014 205
2 052 638
2 077 773
2 095 890
2 113 274
2 126 871
2 130 441
2 155 132
2 171 374
2 192 659
2 216 056
2 241 416
2 267 817
..
CZ002: Brno
711 053
705 268
703 497
702 229
703 121
703 975
704 497
706 365
711 888
716 642
720 249
722 987
724 648
726 097
726 980
728 697
730 047
732 389
735 117
737 883
740 563
..
CZ003: Ostrava
761 158
751 576
748 755
746 242
744 252
742 072
739 987
738 526
738 366
738 122
736 073
733 418
730 982
728 600
725 767
723 302
720 706
718 669
716 299
714 760
713 121
..
CZ004: Plzen
333 329
332 686
331 893
331 682
332 060
331 690
332 762
334 507
338 413
343 554
344 896
345 039
345 312
345 903
346 375
347 374
348 276
349 492
350 813
353 142
356 299
..
DEU: Germany
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
DE001: Berlin
4 921 724
4 934 715
4 951 416
4 961 991
4 965 313
4 971 408
4 984 909
4 996 348
5 010 263
5 025 350
5 036 300
4 849 354
4 898 219
4 951 756
5 005 288
5 066 433
5 143 120
5 207 987
5 259 440
5 303 922
5 342 958
..
DE002: Hamburg
3 044 273
3 067 018
3 090 666
3 102 702
3 114 808
3 122 395
3 137 098
3 152 000
3 172 195
3 174 916
3 179 894
3 100 558
3 118 027
3 139 992
3 161 555
3 189 487
3 230 590
3 269 439
3 296 381
3 315 036
3 328 679
..
DE003: Munich
2 409 291
2 445 204
2 482 195
2 500 764
2 520 498
2 530 874
2 550 897
2 592 863
2 622 392
2 643 952
2 653 866
2 649 026
2 689 303
2 729 747
2 767 620
2 803 118
2 848 014
2 878 204
2 882 464
2 907 752
2 926 802
..
DE004: Cologne
1 851 100
1 854 429
1 863 259
1 867 418
1 867 607
1 873 109
1 886 057
1 892 436
1 898 824
1 897 966
1 899 457
1 890 767
1 903 173
1 916 605
1 929 558
1 946 680
1 972 962
1 987 415
1 994 029
2 002 550
2 004 984
..
DE005: Frankfurt am Main
2 481 433
2 494 854
2 499 521
2 510 210
2 509 501
2 517 932
2 521 306
2 517 908
2 526 003
2 532 337
2 539 964
2 504 069
2 525 261
2 547 515
2 574 107
2 607 200
2 650 351
2 671 729
2 693 488
2 710 501
2 729 936
..
DE007: Stuttgart
2 600 863
2 613 132
2 633 912
2 649 353
2 657 174
2 663 408
2 667 513
2 668 579
2 672 262
2 674 270
2 673 206
2 613 073
2 626 605
2 646 871
2 668 174
2 693 741
2 735 155
2 757 656
2 778 315
2 787 449
2 794 283
..
DE008: Leipzig
1 013 115
1 014 207
1 009 252
1 006 022
1 004 993
1 002 210
1 001 906
1 000 971
999 598
999 052
997 576
966 780
971 372
979 011
986 838
999 498
1 016 815
1 027 810
1 038 105
1 043 613
1 049 342
..
DE009: Dresden
1 396 186
1 389 456
1 379 623
1 372 125
1 367 848
1 365 047
1 364 607
1 364 181
1 357 892
1 353 233
1 350 322
1 323 268
1 323 803
1 326 555
1 328 667
1 332 484
1 342 661
1 341 725
1 341 894
1 343 213
1 343 747
..
DE011: Dusseldorf
1 516 612
1 518 961
1 523 498
1 525 109
1 524 015
1 523 065
1 522 781
1 523 742
1 525 731
1 525 077
1 523 842
1 499 547
1 503 429
1 508 433
1 514 050
1 522 933
1 543 583
1 543 529
1 550 191
1 554 077
1 557 269
..
DE012: Bremen
1 226 557
1 229 854
1 235 307
1 239 773
1 244 000
1 246 775
1 247 499
1 247 559
1 247 046
1 244 620
1 242 736
1 230 128
1 229 608
1 231 914
1 234 669
1 241 658
1 256 669
1 267 134
1 271 977
1 274 968
1 274 429
..
DE013: Hanover
1 280 881
1 285 211
1 289 690
1 293 736
1 294 107
1 295 553
1 295 197
1 294 976
1 295 304
1 293 857
1 293 085
1 260 649
1 264 309
1 269 779
1 276 187
1 284 945
1 301 757
1 307 385
1 311 630
1 316 467
1 316 006
..
DE014: Nuremberg
1 266 610
1 270 901
1 278 914
1 283 380
1 285 560
1 287 779
1 292 243
1 294 492
1 297 674
1 298 007
1 297 371
1 270 601
1 279 860
1 289 950
1 297 812
1 304 437
1 323 107
1 332 024
1 339 862
1 348 820
1 352 002
..
DE017: Bielefeld
321 511
322 151
323 770
325 214
328 847
328 413
327 331
326 256
325 325
324 030
323 498
327 499
327 597
328 712
329 263
330 186
333 506
333 870
332 976
334 211
334 621
..
DE018: Halle an der Saale
474 232
465 672
459 403
453 465
452 075
448 754
445 707
442 275
438 686
434 682
431 738
422 632
421 615
421 026
419 622
419 346
423 788
424 320
425 027
424 195
422 930
..
DE019: Magdeburg
543 672
537 266
533 579
529 625
526 231
522 465
521 418
518 563
515 105
510 852
508 332
498 865
497 175
496 118
495 524
496 321
500 716
502 267
501 389
500 187
497 906
..
DE020: Wiesbaden
450 836
452 467
453 752
454 996
455 260
457 396
457 607
457 604
457 754
457 976
458 537
446 473
449 262
451 338
452 844
455 006
458 104
461 045
463 004
463 252
463 388
..
DE021: Gottingen
503 504
501 608
499 558
497 945
495 763
493 743
490 353
487 617
485 262
481 239
477 749
462 934
460 389
458 328
456 954
457 594
464 104
460 348
460 754
460 511
458 000
..
DE025: Darmstadt
422 975
424 735
426 632
428 386
429 587
430 702
430 564
430 602
430 973
430 722
431 961
423 554
429 027
432 054
434 865
439 557
447 833
451 886
454 006
456 309
457 424
..
DE026: Trier
236 809
236 607
237 805
238 653
239 042
239 357
239 355
243 362
244 474
245 417
245 644
247 636
248 351
250 005
251 137
253 263
262 469
257 501
258 099
259 134
260 478
..
DE027: Freiburg im Breisgau
591 631
597 061
604 290
610 082
614 657
618 467
622 229
624 825
627 242
627 464
630 133
610 940
617 394
623 153
628 600
634 660
645 818
651 257
656 753
658 419
661 204
..
DE028: Regensburg
408 076
411 253
416 211
419 469
421 804
423 262
425 289
426 657
428 304
429 457
430 334
429 813
432 704
436 636
441 488
445 992
453 820
459 088
464 213
468 440
470 222
..
Page:
1
2
3
4
5
6
7
/7
Data extracted on 25 Jan 2022 10:06 UTC (GMT) from
OECD.Stat
Loading...
Information
Please check the i to get information