Dataset Description

This dataset contains rental property listings scraped from Tonaton.com, one of Ghana's leading online classifieds platforms. It provides valuable information on rental prices across various regions in Ghana, along with other property details. The dataset is designed to support analysis, visualization, and modeling of rental prices in the Ghanaian real estate market.

Research paper: https://arxiv.org/abs/2501.06241 Analysis source code: https://github.com/epigos/house-prices-prediction

Features

The dataset includes the following columns:
- url: The link to the listing.
- name: The headline or title of the rental property listing.
- price: The rental price of the property in Ghanaian Cedis (GHS).
- category: The type of rental property (e.g., apartment, house, room, office).
- bedrooms: The number of bedrooms available in the property.
- bathrooms: The number of bathrooms available in the property.
- floor_area: The floor area of the property in square meters.
- location: The address location where the property is located.
- condition: Condition of the property e.g new, used, off-plan etc. - amenities: Amenities provided in the property. - region: Geographic administrative region of the property location. - locality: Represent the town or city where the property is located. - parking_space: Indicates if there is parking space available. - is_furnished: Indicates if the property is furnished. - lat: Longitude location of the property. - lng: Latitude location of the property.

Potential Use Cases

1. Real Estate Market Analysis: Analyze rental price trends across different locations and property types in Ghana.
2. Price Prediction Models: Train machine learning models to predict rental prices based on features like location, property type, and number of bedrooms.
3. Geographical Insights: Investigate how location impacts rental prices across urban and rural areas in Ghana.
4. Consumer Trends: Study patterns in rental property preferences, such as the most popular types of properties or regions.

Source

The data was scraped from Tonaton.com as of November, 2024. Please note that this dataset reflects the listings available during that period and may not include all rental properties in Ghana.

Disclaimer

This dataset is shared for educational and research purposes only. It is not intended for commercial use or to reproduce Tonaton.com’s proprietary information. Users are responsible for ensuring their use complies with Tonaton.com’s terms and conditions.

Conflict of Interest

There are no conflicts of interest associated with the creation or use of this dataset.

Abstract

The population and housing census (PHC) is the unique source of reliable and comprehensive data about the size of population and also on major socio-economic & socio-demographic characteristics of the country. It provides data on geographic and administrative distribution of population and household in addition to the demographic and socio-economic characteristics of all the people in the country. Generally, it provides for comparing and projecting demographic data, social and economic characteristics, as well as household and housing conditions at all levels of the country’s administrative units and dimensions: national, regional, districts and localities. The data from the census is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various multi-sectorial development programs at the national and community levels. Data on all key variables namely area, household, population, economic activity, literacy and education, fertility and child survival, housing conditions and sanitation are collected and available in the census data. The 2021 PHC in Ghana had an overarching goal of generating updated demographic, social and economic data, housing characteristics and dwelling conditions to support national development planning activities.

Geographic coverage

National Coverage , Region , District

Analysis unit

• Individuals
• Households
• Emigrants
• Absentee population
• Mortality
• Type of residence (households and non household)

Universe

All persons who spent census night (midnight of 27th June 2021) in Ghana

Kind of data

Census/enumeration data [cen]

Sampling procedure

This 10% sample data for the 2021 PHC is representative at the district/subdistrict level and also by the urban rural classification.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

GSS developed two categories of instruments for the 2021 PHC: the listing form and the enumeration instruments. The listing form was only one, while the enumeration instruments comprised six questionnaires, designated as PHC 1A, PHC 1B, PHC 1C, PHC 1D, PHC 1E and PHC 1F. The PHC 1A was the most comprehensive with the others being its subsets.

1. Listing Form: The listing form was developed to collect data on type of structures, level of completion, whether occupied or vacant and use(s) of the structures. It was also used to collect information about the availability, number and types of toilet facilities in the structures. It was also used to capture the number of households in a structure, number of persons in households and the sex of the persons residing in the households if occupied. Finally, the listing form was used to capture data on non-household populations such as the population in institutions, floating population and sex of the non-household populations.

2. PHC 1A: The PHC 1A questionnaire was used to collect data from all households in the country. Primarily, it was used to capture household members and visitors who spent the Census Night in the dwelling of the household, and their relationship with the head of the household. It was also used to collect data on homeless households. Members of the households who were absent were enumerated at the place where they had spent the Census Night. The questionnaire was also used to collect the following household information: emigration; socio-demographic characteristics (sex, age, place of birth and enumeration, survival status of parents, literacy and education; economic activities; difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

3. PHC 1B: The PHC 1B questionnaire was used to collect data from persons in stable institutions comprising boarding houses, hostels and prisons who were present on Census Night. Other information that was captured with this instrument are socio-demographic characteristics, literacy and education, economic activities, difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

4. PHC 1C: The PHC 1C questionnaire was used to collect data from persons in “unstable” institutions such as hospitals and prayer camps who were present at these places on Census Night. The instrument was used to capture only the socio-demographic characteristics of individuals.

5. PHC 1D: The PHC 1D questionnaire was used to collect data from the floating population. This constitutes persons who were found at airports, seaports, lorry stations and similar locations waiting for or embarking on long-distance travel, as well as outdoor sleepers on Census Night. The instrument captured the socio-demographic information of individuals.

6. PHC 1E: All persons who spent the Census Night at hotels, motels and guest houses were enumerated using the PHC 1E. The content of the questionnaire was similar to that of the PHC 1D.

7. PHC 1F: The PHC 1F questionnaire was administered to diplomats in the country.

Cleaning operations

The Census data editing was implemented at three levels: 1. data editing by enumerators and supervisors during data collection 2. data editing was done at the regional level by the regional data quality monitors during data collection 3. Final data editing was done at the national level using the batch edits in CSPro and STATA Data editing and cleaning was mainly digital.

Response rate

100 percent

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

CPI Housing Utilities in Ghana decreased to 323.90 points in October from 324.30 points in September of 2025. This dataset provides - Ghana Cpi Housing Utilities- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A structurally separate and independent place of abode. It could be a building or some form of space or shelter arranged for human habitation which was occupied at the time of the Census (e.g. a hut or group of huts). It may contain one or more households. - Households: A household consists of a person or a group of persons, who live together in the same house or compound, share the same house-keeping arrangements and are catered for as one unit. It is important to remember that members of a household are not necessarily related (by blood or marriage) because nonrelatives (e.g. house helps) may form part of a household. - Group quarters: Institutions include educational Institutions such as boarding schools, universities; seminaries and convents; children's homes, orphanages, nurseries, and hostels (e.g. Y.W.C.A.); hospitals, including mental hospitals, maternity homes, divine healers' and herbalists' establishments, rehabilitation centers, and similar institutions for the physically and mentally handicapped; prisons, including borstal institutions, remand homes and industrial schools; service barracks, army camps, military academies, police training schools and colleges.

Universe

All persons in households and all living quarters in Ghana at midnight of Census Night Floating population: Outdoor sleepers, persons who on census night were travelling in lorries, trains, or on foot, persons who spent census night in hotels, rest houses, transit quarters, road camps and labour transit camps, soldiers on field exercise, hunting and fishing groups, beggars, and vagrants (mentally sick or otherwise).

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Ghana Statistical Service

SAMPLE SIZE (person records): 1894133.

SAMPLE DESIGN: Systematic sample of every tenth private dwelling. Drawn by the IPUMS from 100% microdata. Floating population: Outdoor sleepers, persons who on census night were travelling in lorries, trains, or on foot, persons who spent census night in hotels, rest houses, transit quarters, road camps and labour transit camps, soldiers on field exercise, hunting and fishing groups, beggars, and vagrants (mentally sick or otherwise).

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form requested information about dwellings, households and individuals.

Abstract

The 2010 Census was undertaken to update current information on the size, sex, age, composition and other characteristics of Ghana's population and to ascertain the specific changes in these characteristics which had taken place since the last census was conducted in 2000. The Census was expected to ensure the continuation of a time series of demographic and socio-economic benchmark data at the national and sub-national levels and enhance the capability-building programme of the Statistical Service.

The main objective of the 2010 Population and Housing Census was to update the statistical information on the characteristics of the population of Ghana.

The 2010 Population and Housing Census is the second time a full-scale housing census was conducted with a population census in one single operation.

Geographic coverage

National coverage

Analysis unit

Households (including household emigrants, ameneties and agricultural activities) Individuals (including females 12 years and older and females 12-54 years) communities (including education, health and sanitation facilities)

Universe

The 2010 census covered a de-facto population count of Ghana on Census Night (26th September 2010). These were all usual residents, infants sick as well as the mentally challenged, inmates of institutions. out-door sleepers and all persons who spend census night within the boarders of Ghana, semi-stable floating population enumeration was done immediately after midnight of Census Night. Enumeration was done on Census Night of fishermen, other persons at sea and other persons in Field Camps.

All types of housing structures were listed a week before the census night.

All enumeration of institutional population was done a week before the Census Night

Kind of data

Census/enumeration data [cen]

Sampling procedure

There was no sampling

Mode of data collection

Face-to-face [f2f]

Research instrument

PHC-1A: Household questionnaire - admistered to household population. This questionnaire includes modules on Household roster, Usual household members absent, Emigration, Population, Mortality, ICT, Agriculture and Housing

PHC-1A Usual Members Absent Continuation Sheet

PHC-1A Emigration Continuation Sheet

PHC-1B: Group quarter questionnaire - administered to homeless households and group quarter population. This excludes usual members absent, emigration, mortality, ICT at household level, agricultural and housing modules.

PHC-1C: Group quarter questionnaire which was administered to individual members and later transferred to PHC-1B questionnaire

PHC-3: EA Result Sheet - Captured summary information on population by sex and the number of localities in each Enumeration Area (EA).

PHC-4: Final Summary Sheet - Captured summary information on the number of residential structures, number of households, population by sex and household and non-household population and the availability of telecommunication, education, health and toilet facilities in the locality.

Cleaning operations

The Census data editing was implemented at three levels: 1. Field editing by interviewers and supervisors 2. Office editing and coding of occupation and industry 3. Data cleaning and imputation

Data editing was partly manual and partly automatic. Occupation and Industry coding was done by the Field Supervisors but they were edited in the office after the field work. The questionnaire reference numbers were also reviewed as part of the preparatory activities before scanning.

Response rate

100 per cent

Sampling error estimates

There was no sampling.

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error. ( See Adminstrative Report )

Comprehensive dataset containing 13 verified Housing association businesses in Ghana with complete contact information, ratings, reviews, and location data.

The dataset includes responses from two rounds of a Delphi study conducted among experts in the real estate sector, policymakers, and government officials in Ghana. The data captures both quantitative and qualitative insights on factors influencing rental housing decisions.

Round 1: Initial ratings of factors such as rental cost, proximity to work, landlord responsiveness, and availability of amenities.

Round 2: Pairwise comparisons of the top factors identified in Round 1, used for AHP analysis to determine their relative importance.

Abstract

Population censuses have been conducted in Ghana at approximately ten-year intervals since 1891 except in 1941, when the series was interrupted as a result of World War II but was resumed in 1948. The first post-independence census was conducted in 1960 and the next in 1970, with the expectation that a decennial census programme would be maintained. Due to circumstances beyond the control of the statistical organization, however, the third post-independence census could not be conducted until 1984. Similarly, the next census which was expected to have been conducted in 1994 was delayed. Only in 1995 was it possible to have the needed commitment to ensure the conduct of the fourth post-independence census which was scheduled for the year 2000.

The 2000 Population and Housing Census was undertaken to update current information on the size, sex, age, composition and other characteristics of Ghana's population and to ascertain the specific changes in these characteristics which had taken place since the last census was conducted in 1984. The Census was expected to ensure the continuation of a time series of demographic and socio-economic benchmark data at the national and sub-national levels and enhance the capability-building programme of the Statistical Service.

The main objective of the 2000 Population and Housing Census was to update the statistical information on the characteristics of the population of Ghana. The 2000 Population and Housing Census was the first time a full-scale housing census was conducted with a population census in one single operation.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Dwellings

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

Consultation with Users Work on the census questionnaire started in 1998 bearing in mind the data needs of the country. A simple questionnaire was sent to the ministries, relevant government departments, research institutions, relevant departments in the universities, private business associations and other users seeking information on the following: · whether the organization had used any previous census data · the specific census data used · what use the census data were put · any data that were needed but had not been provided in previous censuses · general comments on population censuses. Response to the questionnaire was encouraging; some respondents sent in the completed forms while others came over to discuss their data needs.

Selection of Topics Selecting topics for inclusion in the questionnaire involved the review and consideration of the following: · topics covered in the 1984 population census, · recommended topics from the United Nations Principles and Recommendations for the 2000 round of Population and Housing Censuses, · data requests and suggestions from users based on the answers to the questionnaire sent to them, · list of users' requests compiled by the Statistical Service over a period of time.

A number of meetings were held at both the Census Secretariat and the Technical Advisory Committee levels to discuss the topics and requests. Decisions on topics for inclusion were based on the relevance of topics and the data needs of the country as well as practical considerations of application of concepts.

The final questionnaire consisted of 15 questions on housing characteristics and 20 questions on population covering the following areas: · household characteristics · geographical location and internal migration · demographic and social characteristics · economic characteristics · literacy and education · fertility and mortality.

All the population topics investigated in 1970 and 1984 censuses were maintained, because they were considered as still relevant to the country's data needs, especially in terms of maintaining a time series of socio-economic data.

The questionaires were published in English.

Cleaning operations

The Census data editing was implemented at three levels:

1. Field editing by interviewers and supervisors
2. Office editing and coding
3. Data cleaning and imputation

Data editing was partly manual and partly automatic.

Editing of the census data involved correcting errors from the field and those introduced during the capturing process. Both Structural Edits and Within Record Edits were used to clean the census data.

a) Structural Edits

• Structure edits check coverage and relationships between different units: persons, households, housing units, enumeration areas, etc. Specifically, they checked that: · all households and collective quarters records within an enumeration area were present and were in the proper order; · all occupied housing units have person records, but vacant units have no person records; · households have neither duplicate person records, nor missing person records; · enumeration areas have neither duplicate nor missing housing records.

• Each EA have the right geographic codes (region, district, locality, EA number, etc.)

• Every housing unit in an EA is entered and every record has a valid EA code

The Structural edit looked at the following situations:

· Geography edits · Hierarchy of records · Correspondence between housing and population records · Editing relationships in a household · Family nuclei

b) Within Record Edits: This consisted of validity checks and consistency edits.

· Validity checks: were performed to see if the values of individual variables are plausible or lie with a reasonable range.

· Consistency edits were performed to ensure that there is coherence between two or more variables.

The Top-down editing approach, which starts by editing top priority variables, (such as age, sex, etc.) and moves sequentially through all variables in decreasing priority was used to edit the census data.

The Hot Deck or Dynamic Imputation was also used for both missing data and inconsistent/invalid items.

The Census Secretariat carefully developed Editing and Imputation rules with written sets of consistency rules and corrections. These rules were translated into three CONCOR editing applications (Pop-Edit.exe, Hse-Edit.exe and Fertility.exe), which were used to 'clean' the data. This was done at the Regional level.

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

Ghana Annual Household Expenditure: HW: Actual Rentals for Housing data was reported at 749.210 GHS mn in 2013. This records an increase from the previous number of 90.000 GHS mn for 2006. Ghana Annual Household Expenditure: HW: Actual Rentals for Housing data is updated yearly, averaging 419.605 GHS mn from Dec 2006 (Median) to 2013, with 2 observations. The data reached an all-time high of 749.210 GHS mn in 2013 and a record low of 90.000 GHS mn in 2006. Ghana Annual Household Expenditure: HW: Actual Rentals for Housing data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.H002: Annual Household Expenditure.

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system. The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

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Abstract

The Ghana Living Standards Survey (GLSS) is a nationwide survey carried out by the Government of Ghana (Ghana Statistical Service) with the support of the World Bank (Social Dimensions of Adjustment Project Unit). The objective of the survey is to provide data to the government for measuring the living standards of the population and the progress made in raising them. The survey data will permit a more effective formulation and implementation of policies designed to improve the welfare of the population.

The GLSS was launched in September 1987 and is currently planned to be undertaken over a five-year period. The five interval ensures that a steady stream of data becomes available to monitor the impact of the Government's Economic Recovery Program, including the Program of Actions to Mitigate the Social Costs of Adjustment (PAMSCAD). GLSS provides data on various aspects of the GHanaian household economic and social activities and the interactions between these activities. Data are collected at three levels; the individual level, the household level and community level. The results from the household questionnaire administered to 1525 households over the six month period from september 1987 to march 1988. These results provides a first and useful look at key economic indicators however, because the data base does not cover a complete twelve month period, inferences from this sample should be made with caution.

Geographic coverage

National

Analysis unit

Household

Universe

The survey covered all household members of all age and sex category who reside in Ghana.

Kind of data

Sample survey data [ssd]

Sampling procedure

The methodology that was used reflects the purpose of the survey. To balance the desire for a large, representative sample with the expense of a long, detailed survey instrument, a sample size of 3,200 households was selected. The households were to be chosen in such a manner that each household had an equal probability of being selected. At the same time, the logistics of locating the households and conducting all interviews within a specific time frame required that the households be grouped into "workloads" of 16 households each. A final concern was that all three of the country's ecological zones (coastal, forest and savannah), and each of urban, semi-urban and rural areas (population greater than 5000, 1500 to 5000, and less than 1500, respectively) form the same proportion in the sample as they do in the national population.

To achieve the three objectives simultaneously, a stratified selection process was used. For the 1984 Census, all of Ghana was divided into approximately 13,000 enumeration areas (EAs). From this list it was determined what proportion of the 200 GLSS workloads should be selected from each of the nine zone/urban categories. Two hundred sampling areas were then selected from the enumeration areas in the sub-divided list. For each enumeration area, the probability of being selected was proportional to the number of households contained in that area.

After the 200 sampling areas were selected, households in those areas were enumerated in 1987. Therefore it was possible to take into account changes in the number of households and preserve the self-weighting nature of the sample. The 200 workloads were assigned among the 200 sampling areas with probability equal to the number of households in that area in 1987 divided by the number of households in that area in 1984 and multiplied by the total number of households in 1984 divided by the total number of households in 1987. That is, sampling areas that had greater than average increases in size had a greater than one chance of being selected. Thus, each sampling area was assigned zero, one, two, or even three workloads of sixteen households. The households (sixteen selected and four replacement for each workload) were then chosen randomly from the household list for each sampling area. The resulting list is 3200 households and 800 replacement households in something less than 200 sampling areas (specifically 178 in 1987-88 and 170 in 1988-89). Each group of 16, 32 or 48 households within a sampling area is referred to as a cluster in the GLSS data sets and in this document.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household survey contains modules (sections) to collect data on household demographic structure, housing conditions, schooling, health, employment, migration, expenditure and income, household non-agricultural businesses, agricultural activities, fertility and contraceptive use, savings and credit, and anthropometric (height and weight) measures.

The community questionnaire collected data on the population of the community, a list of principal ethnic groups and religions, the length of time the community has existed and whether or not it has grown, principal economic activities, access to a motorable road, electricity, pipe-borne water, restaurant or food stall, post office, bank, daily market and public transport, employment, migration for jobs, existence of community development projects, schools and how far from the community, information is obtained on whether it is public or private, data on distance and travel time to the nearest of each of several types of health post, dispensary, pharmacy, maternity home, family planning clinic, type of crops grown in the community, how often and when they are planted and harvested, and how the harvest is generally sold.

Price questionnaire collected information on prices from up to three vendors i.e. food, pharmaceutical and other non-food items.

Cleaning operations

The quality control of the data collection occurs at three instances. First, on the field, the supervisor randormly visits 25% of the households already surveyed to verify the answers to some key questions. In addition the supervisor periodically attends interviews conducted by each interviewer. Second, in the regional office, the data entry computer package used performs consistency checks, so that inconsistencies and errors in data collected during the first round are immediately reported to the interviewers for verification during the second round. Finally, daily supervisory checks of the data entry process are performed.

As of September 2023, the rate of inflation for housing, electricity, water, gas, and other fuels in Ghana stood at 28.6 percent. The rate declined, following the downward trend visible since the beginning of the year.

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

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Ghana Annual Household Expenditure: Avg per Capita: HW: Actual Rentals for Housing data was reported at 192.260 GHS in 2013. This records an increase from the previous number of 8.000 GHS for 2006. Ghana Annual Household Expenditure: Avg per Capita: HW: Actual Rentals for Housing data is updated yearly, averaging 100.130 GHS from Dec 2006 (Median) to 2013, with 2 observations. The data reached an all-time high of 192.260 GHS in 2013 and a record low of 8.000 GHS in 2006. Ghana Annual Household Expenditure: Avg per Capita: HW: Actual Rentals for Housing data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.H004: Annual Household Expenditure: Average: per Capita.

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Ghana Consumer Price Index (CPI): Weights: Housing, Water, Electricity, Gas & Other Utilities data was reported at 8.635 % in 2018. This stayed constant from the previous number of 8.635 % for 2017. Ghana Consumer Price Index (CPI): Weights: Housing, Water, Electricity, Gas & Other Utilities data is updated yearly, averaging 6.980 % from Dec 2002 (Median) to 2018, with 17 observations. The data reached an all-time high of 8.635 % in 2018 and a record low of 6.980 % in 2014. Ghana Consumer Price Index (CPI): Weights: Housing, Water, Electricity, Gas & Other Utilities data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.I003: Consumer Price Index: COICOP: Weights.

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