How to Merge Data Vertically in Pandas

Discover how to merge data vertically in Pandas using simple steps to avoid creating multiple columns. Perfect for aligning datasets with different lineage steps!
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How to Merge Data Vertically in Pandas: A Beginner's Guide

When working with dataframes in Python's Pandas library, one common challenge many face is merging data in a way that retains the clarity and organization of the dataset. Specifically, if you want to merge data vertically so that there are multiple rows instead of multiple columns, it can get a bit tricky.

In this guide, we'll go through a practical example that mirrors a typical real-world scenario and show you step-by-step how to achieve this using Pandas.

Understanding the Problem

Consider you have two dataframes representing lineage data. The first one contains a person's journey through various locations, while the second represents previous routes that should slot into the existing journey based on certain matching fields.

Sample Dataframes

Current Route Dataframe:

[[See Video to Reveal this Text or Code Snippet]]

Upstream Route Dataframe:

[[See Video to Reveal this Text or Code Snippet]]

Goal

The goal is to incorporate the upstream route data into the current route dataframe such that each journey (including the upstream routes) is listed in a vertical alignment, maintaining the relationship between the different lineage steps.

The Solution

To achieve this, you can follow these steps:

Step 1: Merge the Dataframes

Start by merging the sample data with the upstream data. This will help you find matches based on specified columns:

[[See Video to Reveal this Text or Code Snippet]]

This df_up now contains the new route data with Lineage Step set to 0 to mark it as a preceding step.

Step 2: Append and Sort the Data

Next, append the modified upstream dataframe back to the original sample data and sort it:

[[See Video to Reveal this Text or Code Snippet]]

Result

After executing the above steps, you should see a new dataframe df_jn that looks something like this:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Merging dataframes vertically allows for more intuitive data analysis and can help in scenarios where lineage or route information needs to be appended in a hierarchical fashion. By following the steps outlined above, you can easily achieve a neatly arranged dataset that accurately reflects the journeys along with any prior steps.

No matter the complexity of your data, knowing how to manipulate dataframes effectively in Pandas is an invaluable skill for data analysis. Happy coding!