Resampling data for different time frames
Two types of resampling are upsampling, where data is converted into a higher frequency (such as daily data to hourly data), and downsampling, where data is converted into a lower frequency (such as daily data to monthly data). In financial data analysis, resampling can help in various ways. For instance, if you have daily stock prices, you can resample this data to calculate monthly or yearly average prices, which can be useful for long-term trend analysis. A common use case is when aligning trade and quote data. There are a lot more quotes than trades – often an order of magnitude more – and we may need to align the open, high, low, and closing quote prices to the open, high, low, and closing trade data. Since the quotes and trades will have different timestamps, resampling to a 1-second resolution is a great way to align these disparate data sources.
How to do it…
We’ll work on resampling stock price data...
