Steel rose to 3,076 CNY/T on September 2, 2025, up 0.89% from the previous day. Over the past month, Steel's price has fallen 3.78%, but it is still 1.02% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Steel - values, historical data, forecasts and news - updated on September of 2025.

India - Home Prices - Historical chart and current data through 2025.

Context

Analyzing stock price is interesting.

Content

Data from yahoo.com/finance AMD and GOOGLE historical price 5/22/2009 ~ 5/03/2017 daily price and volume. There are 7 columns; Date, open, high, low, close, volume, adj close (2001, 7) each of stock

Acknowledgements

Yahoo/finance

Inspiration

I want to find relationship between volume and price.

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

This statistic displays the annual change in the price for paper in the United States from 2009 to 2016, with forecasted figures for 2017 to 2022. In 2016, there was a *** percent decrease in the price of paper in the U.S.

Residential Property Prices in Czech Republic increased 9.94 percent in March of 2025 over the same month in the previous year. This dataset includes a chart with historical data for Czech Republic Residential Property Prices.

The house prices of all house types in Norway increased steadily between 2009 and 2022, followed by a slight decline in 2023. Unlike houses, prices for multi-dwellings did not fall in 2023. Multi-dwelling were also the property type that experienced the strongest growth. At ***** index points, the index for multi-dwelling properties suggests an increase of ** percent since 2015 - the baseline year. How much did Norwegians pay for dwellings in 2021? Oslo appeared to be the most expensive city by dwelling prices that year, followed by Tromsø and Bergen.  Number of residential buildings The number of residential buildings in Norway constantly increased during the past decade, peaking in 2023. There were nearly *** million residences in the country. That was an increase of over 100 thousand units, compared to 2010. More than half of Norwegians lived in detached houses The share of residents by housing type was distributed unevenly in Norway in 2023. Approximately ** percent of Norwegian citizens lived in detached houses, whereas ** percent lived in multi-dwelling buildings. The least common housing type was houses with two dwellings that year.

Residential Property Prices in Portugal increased 16.29 percent in March of 2025 over the same month in the previous year. This dataset includes a chart with historical data for Portugal Residential Property Prices.

Key information about House Prices Growth

• UK house prices grew 3.8% YoY in Feb 2025, following an increase of 4.0% YoY in the previous month.
• YoY growth data is updated monthly, available from Jan 1992 to Feb 2025, with an average growth rate of 4.3%.
• House price data reached an all-time high of 26.4% in Jan 2003 and a record low of -17.5% in Feb 2009.

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.

Core Consumer Prices in El Salvador increased to 118.60 points in July from 118.46 points in June of 2025. This dataset provides - El Salvador Core Consumer Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

The Colombo Consumers' Price Index (CCPI) which was introduced in 1952 by the Department of Census and Statistics and which is now published on the last working day of every month is the official index by which changes in price levels of consumer goods and services in Sri Lanka are measured. Since then the index has been used to date for very vital purposes as described below. It is used for multi-purpose functions such as :

                              for conversion of total current values of national income up to fixed values, 
                              policy making on monetary income and wages, 
                              payment of salaries and wages, 
                              providing social security facilities and analysis of economic and social activities. 

Thus the government mechanism and the non-government organizations use this index as the vital official measurement unit in the fields of financial, revenue, salaries, wages and socio-economic policy making.

Geographic coverage

All urban Divisions in Colombo District

Analysis unit

Commodities (in Retail outlets in Colombo City)

Universe

Retail commodity prices of the goods in Colombo MC and suburban areas

Kind of data

Observation data/ratings [obs]

Sampling procedure

The Weekly Test Purchases operation is not a sample survey. But the following points should be noted:-

From each market, about five outlets have been identified for this operation. Out of the five outlets three are visited by the enumeretors regularly. The selected three outlets in each market are usually visited in every price collection day of the week. The fourth & the fifth outlets will be kept as optional in case the regular outlets are not operational due to some reason.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two types of questionnaires,

  01  A , B , C , D , E - Food Items

  02  Mis01,Mis02,Mis03,Mis04,Mis05,Mis06,Mis07,Mis08 - Non Food Items

General Instructions in filling Forms:

***Group I Form

Price quotations should be collected in few representative and fixed open market retail outlets or stalls in the main marketing area of the Town on morning (9 to 12) of Tuesdays 1st and 3rd week

This price schedule should be perfected and sent by post to the Director Prices and Wages Division in the same week.

***Group II Form

Price quotations required should be obtained once a month from the same outlets, which should be chosen from the selected establishments listed above.

If a particular item is not available in the selected retail outlet, Price quotations may be obtained from the other establishments, whose address should be given. If the item is not available at all in the town, the price of substitute item which resembles most closely the specified item should be priced and brand name, weight should be entered in the form. Brand name and weight of "other" item where it is priced should also be given.

***Group III Form

The item should be selected under specification which has been mentioned here. Two price quotations should be obtained quarterly from the same establishments as far as possible and prices should be collected from the same establishment in future too.

If a particular item is not available in the selected retail outlets, price quotations may be obtained from the reserve or other establishments whose address should be given. If the item is not available at all in the town, the price of a substitute item which resembles most closely the specified item should be entered in the form. Brand name and Weight of "Other" item where it is priced should also be given.

Where transactions take place in other than metric units, the weight of volume of the item priced should be carefully recorded in grams or milli-liters in the space provided.

When you complete item 4 in 1st page of schedule cross-out months except the price collection month.

***Producers' Prices Form

You are instructed to obtain the Producers' prices once a month from selected two main producing centers, and few other production centers are selected for all other agriculture production. The district officer can select the producing centers with the help of the field officer in the respective DS Division. The farm-gate price of every item should be completed in column 4,5,and 6 by the field officer and monthly average prices given in the pricing schedules should be recorded systematically in a price list or in the register maintained in your office.

The average price for three columns (4,5 and 6) should be computed and recorded in the 7th column. If there is noticeable change in average price of column 7 and 8 or if current available price in column 7 is not available. Please give your reasons in column 9. Livestock prices should be collected quarterly and for this purpose the second month of each quarter is more appropriate. (Feb, May, Aug, Nov)

You are advised to collect the prices during the second week of each month and the completed forms should be sent to the Director, Prices and Wages Division by post on or before the given date.

PRODUCERS' PRICE - This is at the farm-gate price or at village market price (pola) charged to customer/buyer. This value figures should include all duties and taxes which fall on products when they leave the farm-gate, but should exclude any subsidies received. This valuation should exclude any transport charges that may be invoiced to the purchaser or user.

Cleaning operations

Usually the prices collected should fall within a range accepted by the Prices and Wages Division staff. If by chance, an abnormally high or a low price have been recorded, that price item will be discarded and not taken for computation purposes.

In a rare situation where the prices of a commodity have not been recorded due to a problem in the market, then the previous day's recording will be assumed for the respective price collection round.

Residential Property Prices in Philippines increased 7.56 percent in March of 2025 over the same month in the previous year. This dataset includes a chart with historical data for Philippines Residential Property Prices.

Kenya National Bureau of Statistics Gross Domestic Product Growth Rates at Constant Prices 2002-2009 Statistical Abstract

The purpose of this study was to understand the relationship between happiness and housing prices in Canada. The happiness data were obtained from the General Social Survey between 2009 and 2013, asking respondents to report overall happiness level by using scale ranging between 1 to 10 points. House Price Indexes at the provincial level were constructed to cover the same period. The relationship between average house price change and average happiness was estimated using Ordinary Least Square and Logistic Regression techniques. Individual's characteristics were used as control variables. The study found that average happiness level is positively and significantly related to the change in housing prices for one group and not for another - for homeowners but not for renters. In addition, individuals with better health are much happier than individuals with poor health. Similarly, individuals with higher income are happier than individuals with less income. The implication of this study is that the government should design attractive policies to encourage homeownerships.

Romania Real Home Prices - Historical chart and current data through 2025.

This table contains figures on the housing costs of private households in independent homes. Households living (temporarily) in a house free of charge are not included. The figures are presented for both owners and tenants and can be further divided into various characteristics of the household and the dwelling.

Data available as of year: 2009

Status of the figures: final.

Changes as of 4 April 2019: None, this table was stopped.

When will new figures be published? This table is stopped. This table is stopped as a consequence of a revision of the income data in 2015. The housing costs are based on this income data. Therefore it is no longer possible to determine the housing costs for WoON 2018 in the same way as before. Consequently the housing costs for WoON 2012 and 2015 have also been revised. For WoON 2009 this however was not possible, since 2011 was the last year of the revision. Subsequently the housing costs for WoON 2012, 2015 and 2018 are included in the new table Housing costs of households; dwelling characteristics, region. See the link in paragraph 3.

Key information about House Prices Growth

• Thailand house prices grew 8.5% YoY in Sep 2021, following an increase of 4.9% YoY in the previous month.
• YoY growth data is updated monthly, available from Mar 2009 to Sep 2021, with an average growth rate of 5.7%.
• House price data reached an all-time high of 20.2% in Dec 2009 and a record low of -6.1% in Dec 2020.

Background:
A household food consumption and expenditure survey has been conducted each year in Great Britain (excluding Northern Ireland) since 1940. At that time the National Food Survey (NFS) covered a sample drawn solely from urban working-class households, but this was extended to a fully demographically representative sample in 1950. From 1957 onwards the Family Expenditure Survey (FES) provided information on all household expenditure patterns including food expenditure, with the NFS providing more detailed information on food consumption and expenditure. The NFS was extended to cover Northern Ireland from 1996 onwards. In April 2001 these surveys were combined to form the Expenditure and Food Survey (EFS), which completely replaced both series. From January 2008, the EFS became known as the Living Costs and Food (LCF) module of the Integrated Household Survey (IHS). As a consequence of this change, the questionnaire was altered to accommodate the insertion of a core set of questions, common to all of the separate modules which together comprised the IHS. Some of these core questions are simply questions which were previously asked in the same or a similar format on all of the IHS component surveys. For further information on the LCF questionnaire, see Volume A of the LCF 2008 User Guide, held with SN 6385. Further information about the LCF, including links to published reports based on the survey, may be found by searching for 'Living Costs and Food Survey' on the ONS website. Further information on the NFS and Living Costs and Food Module of the IHS can be found by searching for 'Family Food' on the GOV.UK website.

History:
The LCF (then EFS) was the result of more than two years' development work to bring together the FES and NFS; both survey series were well-established and important sources of information for government and the wider community, and had charted changes and patterns in spending and food consumption since the 1950s. Whilst the NFS and FES series are now finished, users should note that previous data from both series are still available from the UK Data Archive, under GNs 33071 (NFS) and 33057 (FES).

Purpose of the LCF
The Office for National Statistics (ONS) has overall project management and financial responsibility for the LCF, while the Department for Environment, Food and Rural Affairs (DEFRA) sponsors the food data element. As with the FES and NFS, the LCF continues to be primarily used to provide information for the Retail Prices Index, National Accounts estimates of household expenditure, analysis of the effect of taxes and benefits, and trends in nutrition. The results are multi-purpose, however, providing an invaluable supply of economic and social data. The merger of the two surveys also brings benefits for users, as a single survey on food expenditure removes the difficulties of reconciling data from two sources. Design and methodology The design of the LCF is based on the old FES, although the use of new processing software by the data creators has resulted in a dataset which differs from the previous structure. The most significant change in terms of reporting expenditure, however, is the introduction of the European Standard Classification of Individual Consumption by Purpose (COICOP), in place of the codes previously used. An additional level of hierarchy has been developed to improve the mapping to the previous codes. The LCF was conducted on a financial year basis from 2001, then moved to a calendar year basis from January 2006 (to complement the IHS) until 2015-16, when the financial year survey was reinstated at the request of users. Therefore, whilst SN 5688 covers April 2005 - March 2006, SN 5986 covers January-December 2006. Subsequent years cover January-December until 2014. SN 8210 returns to the financial year survey and currently covers April 2015 - March 2016.

Northern Ireland sample
Users should note that, due to funding constraints, from January 2010 the Northern Ireland (NI) sample used for the LCF was reduced to a sample proportionate to the NI population relative to the UK.

Family Food database:
'Family Food' is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the Family Food Module of the LCFS. Further information about the LCF food databases can be found on the GOV.UK Family Food Statistics web pages.

Secure Access version
A Secure Access version of the LCF from 2006 onwards is available from the UK Data Archive under SN 7047, subject to stringent access conditions. The Secure Access version includes variables that are not included in the standard End User Licence (EUL) version, including geographical variables with detail below Government Office Region, to postcode level; urban/rural area indicators; other sensitive variables; raw diary information files (derived variables are available in the EUL) and the family expenditure codes files. Users are strongly advised to check whether the EUL version is sufficient for their needs before considering an application for the Secure Access version.

Occupation data for 2021 and 2022 data files
The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.

For the second edition (May 2011), the variables A012p and A013p in file dvper were replaced with new versions to correct data errors. For the third edition (June 2011), a new version of the DV Set89 data file was deposited. The variable COI_PLUS (Coicop-plus expenditure code) has been updated to correct truncated codes that were present in the previous version. For the fourth edition (July 2011), the Specs2009 document was replaced with an updated version. The previous version contained some notes that were no longer needed.

DEFRA Family Food database:
This is available as a separate Access download zip file for those users who require it.

Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q2 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.