These are time series datasets. Most are economic (with a focus on inflation) or financial datasets.
The ONS provide consumer price inflation tables here. This page has a link to a large spreadsheet with may tables. Tables 6a, 6b, 6c provide monthly inflation over the last 20 years and are a good place to start. This data contains three measures:
You can download a copy of this data (as of November 2025) from here.
Here is an official summary time-series data of the consumer price index in an Excel file.
The UK inflation data does require cleaning and reshaping. Some tables are in wide format. Other tables contain yearly and month data in the same column. We will need to do some data wrangling to get the data into a useful format for analysis.
The US Federal Reserve provides a time series of the US Consumer Price Index (CPI) from 1947 to present. This is a quarterly index. The data is available from the Federal Reserve Economic Data (FRED) website here
You can also download a copy of this data (as of November 2025) from here.
The main datasets page also contains some time-series datasets including London Bike Hire Dataset and a Share Prices Dataset
### How to calculate annual inflation rates from index values Some of the datasets above are chain type index values. To calculate the annual inflation rate from these index values, you can use the formula: ```math \text{Inflation Rate (\%)} = \left( \frac{\text{Index Value this period} - \text{Index Value same period last year}} {\text{Index Value same period last year}} \right) \times 100 ``` For example, for quarterly rates ```math \text{Annualized Continuous Rate (\%)} = 4 \times \big( \ln(\text{Index}_t) - \ln(\text{Index}_{t-1}) \big) \times 100 ``` The key differences are: * the continuous rate uses log difference directly, good for analysis and modeling. * the discrete rate converts back to a standard annualized percentage, often used for reporting. -->