A time series is a measurement of one or more variables over a period of time and at a specific interval. Once a time series is captured, analysis is often performed to identify patterns in the data, in essence, determining what is happening as time goes by. Being able to process time-series data is essential in the modern world, be it in order to analyze financial information or to monitor exercise on a wearable device and match your exercises to goals and diet.
pandas provides extensive support for working with time-series data. When working with time-series data, you are frequently required to perform a number of tasks, such as the following:
Converting string-based dates and time into objects
Standardizing date and time values to specific time zones
Generating sequences of fixed-frequency dates and time intervals
Efficiently reading/writing the value at a specific time in a series
Converting an existing time series to another with a new frequency of sampling
Computing...