Building a Data Pipeline in Python – Part 2 of N – Data Exploration

This article is originally published at https://www.stoltzmaniac.com

Initial data acquisition and data analysis

In order to get an idea of what our data looks like, we need to look at it! The Jupyter Notebook, embedded below, will show steps to load your data into Python and find some basic statistics to use them to identify potentially issues with new data that arrives.

This process is simply the exploratory step, we will build part of the pipeline in the next step. It’s imporant to have notebooks involved once in a while in order to make sure we know what we’re looking at.

Keep in mind, this is the first look at the data and we’re checking out some very basic testing. These tests will become more robust and meaningful as we continue to build out this pipeline.

You’re always welcome to look at my GitHub for the repository.

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This article is originally published at https://www.stoltzmaniac.com
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