This data is public data that organizes the housing supply rate and housing type distribution by year in Seosan-si, Chungcheongnam-do. The items are composed of year, number of general households, total, single-family homes, multi-family homes, apartments, townhouses, multi-family homes, non-residential buildings, housing supply rate, and data base date. The year refers to the base point in time, and the number of general households refers to the total number of households in the corresponding year. Each housing type item classifies the number of houses by structure, and the housing supply rate indicates the supply level as the ratio of the number of houses to general households. This data is used for establishing housing policies, analyzing housing conditions, real estate statistics, and urban planning data, and also contributes to understanding citizens' housing environments and predicting policy demands.
The Public Data Utilization Support Center automatically converts and provides open-format file data of three or more steps open to public data portals into open APIs (RestAPI-based JSON/XML).
To use the open API, you need to sign up for a public data portal membership and apply for utilization. For inquiries about utilization, please contact the Public Data Utilization Support Center.
File data can be used by downloading without logging in.
A file data information table with a Seosan-si, Chungcheongnam-do_Housing supply rate indicates information such as classification system, provider, etc.
General Public Administration - General administration
Retention
Department
Department NO
Retention
Collected by
Update Cycle
yearly
Next Registration Date
2027-03-31
Media Type
Text
All Rows
9
File Extension
CSV
Download
345
Data Limit
Keyword
house,statistics,Statistical Yearbook,Housing Statistics,Housing by Structure
Registered
2026-03-31
Edited
2026-03-31
Provided
Download from open data Portal (the original text file registration)
Description
This data is public data that organizes the housing supply rate and housing type distribution by year in Seosan-si, Chungcheongnam-do. The items are composed of year, number of general households, total, single-family homes, multi-family homes, apartments, townhouses, multi-family homes, non-residential buildings, housing supply rate, and data base date. The year refers to the base point in time, and the number of general households refers to the total number of households in the corresponding year. Each housing type item classifies the number of houses by structure, and the housing supply rate indicates the supply level as the ratio of the number of houses to general households. This data is used for establishing housing policies, analyzing housing conditions, real estate statistics, and urban planning data, and also contributes to understanding citizens' housing environments and predicting policy demands.
A file data information table with a Seosan-si, Chungcheongnam-do_Housing supply rate indicates information such as classification system, provider, etc.
General Public Administration - General administration
Retention
Department
Department NO
Retention
Collected by
Update Cycle
yearly
Next Registration Date
2027-03-31
Media Type
Text
All Rows
9
File Extension
CSV
Download
345
Data Limit
Keyword
house,statistics,Statistical Yearbook,Housing Statistics,Housing by Structure
Registered
2026-03-31
Edited
2026-03-31
Provided
Download from open data Portal (the original text file registration)
Description
This data is public data that organizes the housing supply rate and housing type distribution by year in Seosan-si, Chungcheongnam-do. The items are composed of year, number of general households, total, single-family homes, multi-family homes, apartments, townhouses, multi-family homes, non-residential buildings, housing supply rate, and data base date. The year refers to the base point in time, and the number of general households refers to the total number of households in the corresponding year. Each housing type item classifies the number of houses by structure, and the housing supply rate indicates the supply level as the ratio of the number of houses to general households. This data is used for establishing housing policies, analyzing housing conditions, real estate statistics, and urban planning data, and also contributes to understanding citizens' housing environments and predicting policy demands.
The Public Data Utilization Support Center automatically converts and provides open-format file data of three or more steps open to public data portals into open APIs (RestAPI-based JSON/XML).
To use the open API, you need to sign up for a public data portal membership and apply for utilization. For inquiries about utilization, please contact the Public Data Utilization Support Center.
File data can be used by downloading without logging in.
General Public Administration - General administration
Provider
Management Agency
Public Data Utilization Support Center
Management agency phone number
1566-0025
Basis For Retention
Collection Method
Update Cycle
yearly
Next Enrollment Date
2027-03-31
Media Type
Text
Whole Row
9
Extension
XML, JSON
Application For Use
0
Data Limit
Keyword
house,statistics,Statistical Yearbook,Housing Statistics,Housing by Structure
Enrollment
2026-03-31
Correction
2026-03-31
Form Of Provision
Download from open data Portal (the original text file registration)
Explanation
This data is public data that organizes the housing supply rate and housing type distribution by year in Seosan-si, Chungcheongnam-do. The items are composed of year, number of general households, total, single-family homes, multi-family homes, apartments, townhouses, multi-family homes, non-residential buildings, housing supply rate, and data base date. The year refers to the base point in time, and the number of general households refers to the total number of households in the corresponding year. Each housing type item classifies the number of houses by structure, and the housing supply rate indicates the supply level as the ratio of the number of houses to general households. This data is used for establishing housing policies, analyzing housing conditions, real estate statistics, and urban planning data, and also contributes to understanding citizens' housing environments and predicting policy demands.