State of Connecticut

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Author
mzagaja
Description
These projections are created based upon several datasets and while these estimates are developed based on multiple data sources, actual population changes may vary from these projections. To assist in planning, analysis, and decision making, the population projections have been developed based on state and locally derived fertility rates.
Category
Government
Rating
Current value: 0 out of 5
Data Provided By
Connecticut State Data Center
Source Link
http://ctsdc.uconn.edu/projections.html
License
Attribution | Share Alike 3.0 Unported
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Size
  • 500x425

  • 760x646

  • 950x808

Custom Size

425x425 is the minimum size

The Socrata Open Data API (SODA) provides programmatic access to this dataset including the ability to filter, query, and aggregate data. For more more information, view the API docs for this dataset or visit our developer portal

API Endpoint:

Field Names:

TOWN
town
2015 TOTAL
_2015_total
2015 Male TOTAL
_2015_male_total
2015 Male 00-04
_2015_male_00_04
2015 Male 05-09
_2015_male_05_09
2015 Male 10-14
_2015_male_10_14
2015 Male 15-19
_2015_male_15_19
2015 Male 20-24
_2015_male_20_24
2015 Male 25-29
_2015_male_25_29
2015 Male 30-34
_2015_male_30_34
2015 Male 35-39
_2015_male_35_39
2015 Male 40-44
_2015_male_40_44
2015 Male 45-49
_2015_male_45_49
2015 Male 50-54
_2015_male_50_54
2015 Male 55-59
_2015_male_55_59
2015 Male 60-64
_2015_male_60_64
2015 Male 65-69
_2015_male_65_69
2015 Male 70-74
_2015_male_70_74
2015 Male 75-79
_2015_male_75_79
2015 Male 80-84
_2015_male_80_84
2015 Male 85-89
_2015_male_85_89
2015 Male 90-OV
_2015_male_90_ov
2015 Female TOTAL
_2015_female_total
2015 Female 00-04
_2015_female_00_04
2015 Female 05-09
_2015_female_05_09
2015 Female 10-14
_2015_female_10_14
2015 Female 15-19
_2015_female_15_19
2015 Female 20-24
_2015_female_20_24
2015 Female 25-29
_2015_female_25_29
2015 Female 30-34
_2015_female_30_34
2015 Female 35-39
_2015_female_35_39
2015 Female 40-44
_2015_female_40_44
2015 Female 45-49
_2015_female_45_49
2015 Female 50-54
_2015_female_50_54
2015 Female 55-59
_2015_female_55_59
2015 Female 60-64
_2015_female_60_64
2015 Female 65-69
_2015_female_65_69
2015 Female 70-74
_2015_female_70_74
2015 Female 75-79
_2015_female_75_79
2015 Female 80-84
_2015_female_80_84
2015 Female 85-89
_2015_female_85_89
2015 Female 90-OV
_2015_female_90_ov
2020 TOTAL
_2020_total
2020 Male TOTAL
_2020_male_total
2020 Male 00-04
_2020_male_00_04
2020 Male 05-09
_2020_male_05_09
2020 Male 10-14
_2020_male_10_14
2020 Male 15-19
_2020_male_15_19
2020 Male 20-24
_2020_male_20_24
2020 Male 25-29
_2020_male_25_29
2020 Male 30-34
_2020_male_30_34
2020 Male 35-39
_2020_male_35_39
2020 Male 40-44
_2020_male_40_44
2020 Male 45-49
_2020_male_45_49
2020 Male 50-54
_2020_male_50_54
2020 Male 55-59
_2020_male_55_59
2020 Male 60-64
_2020_male_60_64
2020 Male 65-69
_2020_male_65_69
2020 Male 70-74
_2020_male_70_74
2020 Male 75-79
_2020_male_75_79
2020 Male 80-84
_2020_male_80_84
2020 Male 85-89
_2020_male_85_89
2020 Male 90-OV
_2020_male_90_ov
2020 Female TOTAL
_2020_female_total
2020 Female 00-04
_2020_female_00_04
2020 Female 05-09
_2020_female_05_09
2020 Female 10-14
_2020_female_10_14
2020 Female 15-19
_2020_female_15_19
2020 Female 20-24
_2020_female_20_24
2020 Female 25-29
_2020_female_25_29
2020 Female 30-34
_2020_female_30_34
2020 Female 35-39
_2020_female_35_39
2020 Female 40-44
_2020_female_40_44
2020 Female 45-49
_2020_female_45_49
2020 Female 50-54
_2020_female_50_54
2020 Female 55-59
_2020_female_55_59
2020 Female 60-64
_2020_female_60_64
2020 Female 65-69
_2020_female_65_69
2020 Female 70-74
_2020_female_70_74
2020 Female 75-79
_2020_female_75_79
2020 Female 80-84
_2020_female_80_84
2020 Female 85-89
_2020_female_85_89
2020 Female 90-OV
_2020_female_90_ov
2025 TOTAL
_2025_total
2025 Male TOTAL
_2025_male_total
2025 Male 00-04
_2025_male_00_04
2025 Male 05-09
_2025_male_05_09
2025 Male 10-14
_2025_male_10_14
2025 Male 15-19
_2025_male_15_19
2025 Male 20-24
_2025_male_20_24
2025 Male 25-29
_2025_male_25_29
2025 Male 30-34
_2025_male_30_34
2025 Male 35-39
_2025_male_35_39
2025 Male 40-44
_2025_male_40_44
2025 Male 45-49
_2025_male_45_49
2025 Male 50-54
_2025_male_50_54
2025 Male 55-59
_2025_male_55_59
2025 Male 60-64
_2025_male_60_64
2025 Male 65-69
_2025_male_65_69
2025 Male 70-74
_2025_male_70_74
2025 Male 75-79
_2025_male_75_79
2025 Male 80-84
_2025_male_80_84
2025 Male 85-89
_2025_male_85_89
2025 Male 90-OV
_2025_male_90_ov
2025 Female TOTAL
_2025_female_total
2025 Female 00-04
_2025_female_00_04
2025 Female 05-09
_2025_female_05_09
2025 Female 10-14
_2025_female_10_14
2025 Female 15-19
_2025_female_15_19
2025 Female 20-24
_2025_female_20_24
2025 Female 25-29
_2025_female_25_29
2025 Female 30-34
_2025_female_30_34
2025 Female 35-39
_2025_female_35_39
2025 Female 40-44
_2025_female_40_44
2025 Female 45-49
_2025_female_45_49
2025 Female 50-54
_2025_female_50_54
2025 Female 55-59
_2025_female_55_59
2025 Female 60-64
_2025_female_60_64
2025 Female 65-69
_2025_female_65_69
2025 Female 70-74
_2025_female_70_74
2025 Female 75-79
_2025_female_75_79
2025 Female 80-84
_2025_female_80_84
2025 Female 85-89
_2025_female_85_89
2025 Female 90-OV
_2025_female_90_ov

Use OData to open the dataset in tools like Excel or Tableau. This provides a direct connection to the data that can be refreshed on-demand within the connected application.

Socrata OData documentation

Tableau users should select the OData v2 endpoint option.

OData V4 Endpoint:

OData V2 Endpoint:

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