[LE0105Mottagna03] Population. Number by region, age, sex, observations and year
Updated on DBnomics on February 22, 2023 (11:00 AM).
[Region] region
- [00] Sweden
- [01] Stockholm county
- [0114] Upplands Väsby
- [0115] Vallentuna
- [0117] Österåker
- [0120] Värmdö
- [0123] Järfälla
- [0125] Ekerö
- [0126] Huddinge
- [0127] Botkyrka
- [0128] Salem
- [0136] Haninge
- [0138] Tyresö
- [0139] Upplands-Bro
- [0140] Nykvarn
- [0160] Täby
- [0162] Danderyd
- [0163] Sollentuna
- [0180] Stockholm
[Alder] age
- [-4] 0-4 years
- [00-04] 0-4 years
- [5-9] 5-9 years
- [5-14] 5-14 years
- [10-14] 10-14 years
- [15-19] 15-19 years
- [15-24] 15-24 years
- [20-24] 20-24 years
- [25-29] 25-29 years
- [25-34] 25-34 years
- [30-34] 30-34 years
- [35-39] 35-39 years
- [35-44] 35-44 years
- [40-44] 40-44 years
- [45-49] 45-49 years
- [45-54] 45-54 years
- [50-54] 50-54 years
- [55-59] 55-59 years
- [55-64] 55-64 years
- [60-64] 60-64 years
- [65-69] 65-69 years
- [65-74] 65-74 years
- [70-74] 70-74 years
- [75-79] 75-79 years
- [75-84] 75-84 years
- [80-84] 80-84 years
- [85-89] 85-89 years
- [85-94] 85-94 years
- [90-94] 90-94 years
- [95-99] 95-99 years
- [95+] 95+ years
- [100+] 100+ years
- [totalt] total
[Kon] sex
- [TOT2] total
- [100] women
- [200] men
[ContentsCode] observations
- [000004TP] Inbound migration
- [000004TT] Outbound migration
- [000004TN] Immigration
- [000004TL] Emigration
- [000004TM] Migration surplus
- [000004TO] Immigration surplus
- [000004TR] Internal inbound migration
- [000004TS] Internal outbound migration
- [000004TQ] Internal migration surplus
Search filters
region [Region] (19)
age [Alder] (33)
sex [Kon] (3)
observations [ContentsCode] (9)
This dataset has 277,992 series:
- from
- 2016=14
- to
- 2020=8
- min:
- 7
- max:
- 18
- avg:
- 11
- σ:
- 4.29
- from
- 2016=3,418
- to
- 2020=380
- min:
- 380
- max:
- 3,418
- avg:
- 1,650.8
- σ:
- 1,106.886
- from
- 2016=3,432
- to
- 2020=388
- min:
- 388
- max:
- 3,432
- avg:
- 1,661.8
- σ:
- 1,107.078
- from
- 2016=3,418
- to
- 2020=380
- min:
- 380
- max:
- 3,418
- avg:
- 1,650.8
- σ:
- 1,106.886
- from
- 2016=3,432
- to
- 2020=388
- min:
- 388
- max:
- 3,432
- avg:
- 1,661.8
- σ:
- 1,107.078
- from
- 2016=0
- to
- 2020=0
- min:
- 0
- max:
- 0
- avg:
- 0
- σ:
- 0
- from
- 2016=0
- to
- 2020=0
- min:
- 0
- max:
- 0
- avg:
- 0
- σ:
- 0
- from
- 2016=0
- to
- 2020=0
- min:
- 0
- max:
- 0
- avg:
- 0
- σ:
- 0
- from
- 2016=14
- to
- 2020=8
- min:
- 7
- max:
- 18
- avg:
- 11
- σ:
- 4.29
- from
- 2016=8
- to
- 2020=10
- min:
- 4
- max:
- 14
- avg:
- 9.8
- σ:
- 3.6
Series code | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|
[00.-4.100.000004TL] | 14 | 7 | 8 | 18 | 8 |
[00.-4.100.000004TM] | 3418 | 2358 | 1335 | 763 | 380 |
[00.-4.100.000004TN] | 3432 | 2365 | 1343 | 781 | 388 |
[00.-4.100.000004TO] | 3418 | 2358 | 1335 | 763 | 380 |
[00.-4.100.000004TP] | 3432 | 2365 | 1343 | 781 | 388 |
[00.-4.100.000004TQ] | 0 | 0 | 0 | 0 | 0 |
[00.-4.100.000004TR] | 0 | 0 | 0 | 0 | 0 |
[00.-4.100.000004TS] | 0 | 0 | 0 | 0 | 0 |
[00.-4.100.000004TT] | 14 | 7 | 8 | 18 | 8 |
[00.-4.200.000004TL] | 8 | 4 | 13 | 14 | 10 |
Showing results 1 - 10 / 277,992