How to Append Data from One Pandas DataFrame into Another

Learn how to effectively append latitude and longitude data from one DataFrame to another using the Pandas library in Python.
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How to Append Data from One Pandas DataFrame into Another

Are you working with geographical data using Pandas and need to append data from one DataFrame into another? If you're trying to combine latitude and longitude information for a set of cities, you've come to the right place! In this blog, we'll look at how to properly append such data and create a well-structured final DataFrame that holds all the information you need.

The Problem

Imagine you have a DataFrame containing cities along with their latitude and longitude coordinates. You also have another DataFrame with pairs of cities, and you want to expand this DataFrame to include the corresponding latitude and longitude for each city in the pairs. Here's the scenario laid out clearly:

You have a DataFrame (df) with city names, latitudes, and longitudes.

You have another DataFrame (df_pair) that contains pairs of cities (like start_city and end_city).

The goal is to append the latitude and longitude information from df into the df_pair DataFrame, resulting in a new DataFrame (df_pair_geo) with additional columns: start_latitude, start_longitude, end_latitude, and end_longitude.

This was the initial DataFrame created from the dictionary:

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

Following this, a DataFrame with city pairs is created.

The Solution

To achieve the desired output, we can utilize the merge() function provided by Pandas. This function allows us to join two DataFrames based on a common key, in this case, the city names.

Step-by-Step Guide to Appending the Data

Merge the First DataFrame: We will first merge df_pair with df to get the latitude and longitude for the starting cities.

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

Here, we are setting the index of df to the 'city' column, which allows us to merge it with the start_city from df_pair seamlessly.

Merge the Second DataFrame: Next, we need to perform a second merge to get the latitude and longitude corresponding to the ending cities.

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

You might notice that we add suffixes to distinguish between the latitude and longitude of the starting city and the ending city.

Examine the Result: After running those merges, df2 will have the desired structure, which includes both latitudes and longitudes for the given pairs.

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

The output will look like this:

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

Conclusion

By following these simple steps, you can efficiently append latitude and longitude data from one DataFrame into another using Pandas. Using the merge() function is a powerful way to combine datasets, and it scales impressively when dealing with larger datasets. Thank you for reading, and happy coding!