Inflation Rate is the percentage change in the Consumer Price Index (CPI) from one period to another. It is a measure of the rate of price increases in the economy.

Data comes from the Global Macro Database (GMDB), further information about the variable can be found within https://www.globalmacrodata.com/documentation.html

The rate is expressed as a decimal fraction (0.0412 for 4.1166%) on an annual basis. The GMDB extends its series with IMF World Economic Outlook projections, so the current year and any later years the end_date reaches are forecasts rather than outturns.

Changed in v2.2.0: this used to be returned in percentage points (4.1166 for 4.1166%). It is now a decimal fraction, matching every other rate in the Finance Toolkit.

Also known as: CPI-based inflation, price increases, consumer prices.

No programming experience? With the Finance Toolkit MCP server, AI assistants such as Claude and ChatGPT can calculate the Inflation Rate for you. Just ask in plain English.

Calculate the Inflation Rate in Python

The Inflation Rate is available in the Economics module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_inflation_rate as shown below.

from financetoolkit import Economics

economics = Economics(start_date='2003-01-01', end_date='2009-03-01')

economics.get_inflation_rate(countries=['Germany', 'France', 'Portugal'])

Which returns:

  Germany France Portugal
2003 0.0103 0.021 0.0322
2004 0.0167 0.0214 0.0237
2005 0.0155 0.0175 0.0228
2006 0.0158 0.0168 0.0311
2007 0.023 0.0149 0.0245
2008 0.0263 0.0281 0.0259
2009 0.0031 0.0009 -0.0084

Parameters

get_inflation_rate accepts the following parameters:

  • countries (list[str] | str | None, optional): The countries to include in the data. Defaults to None.
  • rolling (int, optional): The rolling window size to use for smoothing the data (simple moving average). Defaults to None.
  • trailing (int, optional): The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None.
  • growth (bool, optional): Whether to return the growth data or the actual data.
  • lag (int, optional): The number of periods to lag the data by.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
  • rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.
Consumer Price Index Consumer Confidence Index Business Confidence Index Composite Leading Indicator House Prices Rent Prices Share Prices Exchange Rates Producer Price Index Real Effective Exchange Rate Household Savings Rate Household Debt to Income Ratio

The Economics module page introduces the module, and the sidebar lists all of its functions.

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