Time Series Data Analysis — Resample

How to use Resample in Pandas to enhance your time series data analysis

When it comes to time series analysis, resampling is a critical technique that allows you to flexibly define the resolution of the data you want. You can either increase the frequency like converting 5-minute data into 1-minute data (upsample, increase in data points), or you can do the other way around (downsample, decrease in data points).

Quoting the words from documentation, resample is a “Convenient method for frequency conversion and resampling of time series.”

In practice, there are 2 main reasons why using resample.

1. To inspect how data behaves differently under different resolutions or frequency.
2. To join tables with different resolutions.

Without further ado, let’s get our hands dirty and learn it from hands-on practice!

python resampling data-analysis pandas

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