Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Where is the data from?

The data was scraped from Immoscout24, the biggest real estate platform in Germany. Immoscout24 has listings for both rental properties and homes for sale, however, the data only contains offers for rental properties. The scraping process is described in this blog post and the corresponding code for scraping and minimal processing afterwards can be found in this Github repo. At a given time, all available offers were scraped from the site and saved. This process was repeated three times, so the data set contains offers from the dates 2018-09-22, 2019-05-10 and 2019-10-08.

Content

The data set contains most of the important properties, such as living area size, the rent, both base rent as well as total rent (if applicable), the location (street and house number, if available, ZIP code and state), type of energy etc. It also has two variables containing longer free text descriptions: description with a text describing the offer and facilities describing all available facilities, newest renovation etc. The date column was added to give the time of scraping.

Inspiration

Did rents increase over time? Which areas are the most expensive? Which areas saw the largest increase, which areas became cheaper? Are there any duplicates? How many? What could be gained from a text analysis of the free text variables?

Acknowledgements

The data belongs to www.immobilienscount24.de and is for research purposes only. The data was created with .

Context

This dataset includes the median list price divided by the square footage of a 1-bedroom home for a select number of neighborhoods around the United States.

Content

When available, data includes median price per square foot on a monthly basis between January 2010 and September 2016.

Selected neighborhoods include:

• Upper East Side, New York, NY
• Spring Valley, Las Vegas, NV
• Hollywood, Los Angeles, CA
• Williamsburg, New York, NY
• Harlem, New York, NY
• Enterprise, Las Vegas,NV
• Downtown, San Jose, CA
• Sheepshead Bay, New York, NY
• Forest Hills, New York, NY
• Jackson Heights, New York, NY
• Gramercy, New York, NY
• Flagami, Miami, FL
• Downtown, Memphis, TN
• Chelsea, New York, NY
• Oak Lawn, Dallas, TX
• Greater Uptown, Houston, TX
• South Loop, Chicago, IL
• Makiki-Lower Punchbowl-Tantalus, Honolulu, HI
• Downtown, Los Angeles, CA
• Capitol Hill, Seattle, WA
• Clinton, New York, NY
• Alexandria West, Alexandria, VA
• Financial District, New York, NY
• Flatiron District, New York, NY
• Landmark-Van Dom, Alexandria, VA
• Flamingo Lummus, Miami Beach, FL
• Winchester, Las Vegas, NV
• Brickell, Miami, FL
• Waikiki, Honolulu, HI
• Back Bay, Boston, MA
• Sutton Place, New York, NY
• and several others

Inspiration

• What neighborhoods have the most expensive real estate per square foot? Least expensive?
• Which neighborhoods and/or cities have the fastest growth rates in price?
• Are there any neighborhoods that remain relatively steady in price?
• Given that this metric is listing price per square foot, is there a similar dataset that could help you compare median square footage in a 1-bedroom home across neighborhoods?

Acknowledgement

This dataset is part of Zillow Data, and the original source can be found here, under the Neighborhoods link.

Context☜(ﾟヮﾟ☜)

Story?

Predicting House Prices is too mainstream😆

Well, it's very simple. I wanted to buy a Monitor for work, and while shortlisting one, realized that this would be a great problem to work on. Wrote a quick script(wasn't quick at all, lol) to scrape data and saved it into the old fashioned csv.

Content👩‍💻👨‍💻

To start with this is pure RAW data. It has lot's of NULL, empty and unexpected data. So if you are looking for an intensive Data Cleaning/Preprocessing or Feature Engineering, this is the right place to start. There are 90 columns and some of them are:

• Length(In): Length in Inches
• Width(In): Width in Inches
• Height(In): Height in Inches
• Weight: Weight in Pounds
• Price: Price of the Monitor in Dollars
• Brand: Brand of the Monitor
• Manufacturer: Manufacturer name
• Country of Origin

Acknowledgements

Well, definitely Amazon for the this bag full of data😁

Inspiration😯

Starter questions that might surprise you: 1. Which is the most expensive Brand out there? 2. What's the average LengthXWidthXHeight Monitor's available in the market? 3. What are top 5 features that play an important role in deciding the Price of a Monitor.

The house price for Ontario is forecast to decrease by eight percent in 2023, followed by a minor increase of one percent in 2024. From roughly 932,000 Canadian dollars, the average house price in Canada's second most expensive province for housing is expected to fall to 861,000 Canadian dollars in 2024. After British Columbia, Ontario is Canada's most expensive province for housing. Ontario Ontario is the most populated province in Canada, located on the eastern-central side of the country. It is an English speaking province. To the south, it borders American states Minnesota, Michigan, Ohio, Pennsylvania, and New York. Its provincial capital and largest city is Toronto. It is also home to Canada’s national capital, Ottawa. Furthermore, a large part of Ontario’s economy comes from manufacturing, as it is the leading manufacturing province in Canada. The population of Ontario has been steadily increasing since 2000. The population in 2018 was an estimated 14.3 million people. The median total family income in 2016 came to 83,160 Canadian dollars. Ontario housing market The number of housing units sold in Ontario is projected to rise until 2024. Additionally, the average home prices in Ontario have significantly increased since 2007.

Housing Index in Portugal increased to 247.05 points in the first quarter of 2025 from 235.68 points in the fourth quarter of 2024. This dataset provides - Portugal House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The average resale house price in Canada was forecast to reach nearly ******* Canadian dollars in 2026, according to a January forecast. In 2024, house prices increased after falling for the first time since 2019. One of the reasons for the price correction was the notable drop in transaction activity. Housing transactions picked up in 2024 and are expected to continue to grow until 2026. British Columbia, which is the most expensive province for housing, is projected to see the average house price reach *** million Canadian dollars in 2026. Affordability in Vancouver Vancouver is the most populous city in British Columbia and is also infamously expensive for housing. In 2023, the city topped the ranking for least affordable housing market in Canada, with the average homeownership cost outweighing the average household income. There are a multitude of reasons for this, but most residents believe that foreigners investing in the market cause the high housing prices. Victoria housing market The capital of British Columbia is Victoria, where housing prices are also very high. The price of a single family home in Victoria's most expensive suburb, Oak Bay was *** million Canadian dollars in 2024.

Abstract copyright UK Data Service and data collection copyright owner. The purpose of this survey was to collect data about parents' intentions about family size and family spacing, the factors that are related to these intentions and influences on their achievement or failure to achieve their intentions. Main Topics: Attitudinal/Behavioural Questions Ease of caring for child, most helpful person, source of advice about babycare, need for advice, space between new baby and previous live born child of same marriage, baby's place of birth, total number of other pregnancies, type of other pregnancies, desire for more children, reasons for any inability to produce more children, ideal number of children (smallest and largest number of children ever wanted). Attitude to wife's future pregnancies, whether abortion considered, disagreement between husband and wife over desired number of children, preferred sex of next child, ideal space between children, shortest/longest space considered reasonable, whether respondent/spouse pregnant now, opinion on whether a population problem exists in the country. Attitude to birth control and limiting size of families, experience of various methods of birth control, current method of birth control, duration of use, opinion of reliability, preference for other methods (criteria of health and pleasantness), whether more information required about any type of contraception, likelihood of change in method, knowledge of women's monthly variations in fertility. Reasons for not using pill, reasons for non-sterilization, whether birth control discussed with medical staff, social/professional workers or relatives or friends, person respondent found most helpful. Details of discussion about prescription for and symptoms or difficulties with pill. Reasons for discontinuation. Satisfaction with timing of pregnancy, whether birth control used at time of conception (type), length of time birth control not used before conception, whether pregnancy intended, discussion of sterilization, attitude to male and female sterilization. Opinion on effect of sterilisation on man's/woman's sex life, attitude to abortion. Whether house suitable for child-rearing, reasons for inadequacy, number of moves since marriage, number of jobs since one year before marriage, intention to remain with present employer, period of unemployment since marriage. Length of husband and wife's friendship before marriage, length of marriage at birth of baby, frequency of intercourse, whether woman had period in last 7 days. Effect of an extra $5 a week on desired number of children, largest number of children respondent feels capable of bringing up reasonably. Opinion on age at which children are most expensive, expectation of change in level of family income in five years, change in level of family income over last 18 months, comparison of standard of living with other families respondent knew well, adequacy of present family income, whether savings made. Most recent visit to parents/in-laws, length of journey. Number of siblings (actual and preferred), persons seen most/felt closest to. Child care from husband and help with domestic chores. Patterns of decision making in the family for general matters and for birth control, ease of discussion about sex with marital partner. Attitude to working mothers of children under school age. Woman's intentions to start work part or full-time. Age of respondent and spouse at baby's birth, age of woman at first pregnancy. Reasons for not wanting more children and circumstances which would alter decision. Reasons for sterilisation. Views about children when first married and reasons for any change of mind. Satisfaction with birth control method currently used (criteria of health and pleasantness), reasons for change in method, preferences for source of contraception (GP or clinic). Discussion of and attitude to abortion and sterilization. Particular items respondent had saved money for before marriage, reasons for starting/not starting a family straight away. Background Variables For respondent and spouse: age, sex, place of birth, multiple births, number of children, social class (General Registrar's Office 1966 classification of occupations), method of payment. Household composition, number of persons in household, number of rooms, persons per room, amenities (whether shared), garden. Tenure (date of first mortgage where appropriate), type of housing, level of dwelling (eg ground, basement). Further education, religion, church attendance. Baby's month of birth, whether another baby born since, birth interval. Simple random sample random sample of parents of legitimate births in 25 selected local authority areas Face-to-face interview 1973 ABORTION ADVICE AGE ATTITUDES BIRTH CONTROL CATHOLICISM CHILD CARE CHILDBIRTH CHILDREN CONTRACEPTIVE DEVICES COSTS DECISION MAKING DOMESTIC RESPONSIBI... EARLY CHILDHOOD EDUCATIONAL BACKGROUND EMPLOYMENT EMPLOYMENT HISTORY England and Wales FAMILY MEMBERS FAMILY PLANNING FAMILY ROLES FAMILY SIZE FATHERS FERTILITY FINANCIAL EXPECTATIONS FINANCIAL RESOURCES Family life and mar... GENDER GENERAL PRACTITIONERS HEALTH VISITORS HOME OWNERSHIP HOME SHARING HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING TENURE History INCOME INFANTS INTERPERSONAL COMMU... INTERPERSONAL CONFLICT INTERPERSONAL RELAT... JOB CHANGING KNOWLEDGE AWARENESS MARRIAGE MEDICAL CENTRES MENSTRUATION MOTHERS MULTIPLE BIRTHS PARENTAL ROLE PARENTS PHYSICIANS PLACE OF BIRTH POPULATION PROBLEMS PREGNANCY PRESCHOOL CHILDREN PRIVATE GARDENS RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RESIDENTIAL MOBILITY ROOM SHARING ROOMS SATISFACTION SAVINGS SEXUAL BEHAVIOUR SIBLINGS SOCIAL CLASS SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPOUSE S PLACE OF B... SPOUSES STANDARD OF LIVING STERILIZATION MEDICAL UNEMPLOYED VISITS PERSONAL WORKING MOTHERS

Key quality of life indicators - cost index, housing.