View data of the CPI, or an inflation measure derived from tracking the changes in the weighted-average price of a basket of common goods and services.

Analysis of ‘🚊 Consumer Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/consumer-price-indexe on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

9The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods.(1) It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.(1)

The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas.(1) To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date.(1) In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays.(1)

The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (Consumer Price Index for All Urban Consumers: All Items Less Food & Energy [CPILFESL]) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs.(1) Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average.(1)

Attribution: US. Bureau of Labor Statistics from The Federal Reserve Bank of St. Louis

For more information on the consumer price indexes, see:

• (1) Bureau of Economic Analysis. “CPI Detailed Report.” 2013
• (2) Handbook of Methods
• (3) Understanding the CPI: Frequently Asked Questions

This dataset was created by Finance and contains around 900 samples along with Consumer Price Index For All Urban Consumers: All Items, Title:, technical information and other features such as: - Consumer Price Index For All Urban Consumers: All Items - Title: - and more.

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Acknowledgements

If you use this dataset in your research, please credit Finance

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--- Original source retains full ownership of the source dataset ---

The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods. It can be used to recognize periods of inflation and deflation.

Content

This series is constructed as Advance Retail and Food Services Sales (https://fred.stlouisfed.org/series/RSAFS) deflated using the Consumer Price Index for All Urban Consumers (1982-84=100) (https://fred.stlouisfed.org/series/CPIAUCSL).

Context

This is a dataset from the Federal Reserve Bank of St. Louis hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve Bank of St. Louis using Kaggle and all of the data sources available through the St. Louis Fed organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1992-01-01

• Observation End : 2019-10-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Ive Erhard on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Content

This series deflates M1 money stock (https://fred.stlouisfed.org/series/M1SL) with CPI (https://fred.stlouisfed.org/series/CPIAUCSL).

Context

This is a dataset from the Federal Reserve Bank of St. Louis hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve Bank of St. Louis using Kaggle and all of the data sources available through the St. Louis Fed organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1959-01-01

• Observation End : 2019-10-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Precondo CA on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

The observation for 2020 is missing because the U.S. Census Bureau released experimental estimates (https://www.census.gov/programs-surveys/acs/data/experimental-data.html) instead of the standard 1-year data products for the 2020 American Community Survey (ACS). There was no 2020 experimental data provided for the American Community Survey (ACS) 1-year variable S1901_C01_013E.

Mean household income, American Community Survey (ACS) 1-year variable S1901_C01_013E, is adjusted by CPI (https://fred.stlouisfed.org/series/CPIAUCSL) where the price index is re-based to 1999 dollars. Then the series is adjusted for cost of living using regional price parities (RPP) from the U.S. Bureau of Economic Analysis' Real Personal Income for States and Metropolitan Areas (https://fred.stlouisfed.org/release?rid=403&soid=18). Finally to approximate the wage, the series is divided by (52 * 40), which assumes there are 52 weeks in a year and 40 work hours in a week. Note that household income can include additional sources of income beyond wages. See page 83 in the ACS's Subject Definitions (https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2019_ACSSubjectDefinitions.pdf) for more information.

ACS 1-year estimates are not available for all geographic areas. If a county is not included in the 1-year estimates for a given year, the series will not revise or there will be a missing observation. See the Areas Published (https://www.census.gov/programs-surveys/acs/geography-acs/areas-published.html) for more details about the geographies included in the ACS 1-year estimates.

The RPP used to calculate this series is NYNMPRPPALL (https://fred.stlouisfed.org/series/NYNMPRPPALL). If the RPP for the region is zero or missing for a given year, the series will not revise or there will be a missing observation.

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