How to Append Rows in Pandas Dataframe using Python

Learn how to effectively append rows in a Pandas dataframe with a practical example, creating a new column based on a list of values.
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Mastering Row Appending in Pandas DataFrame

When working with data in Python, the Pandas library is often your best friend. However, many beginners encounter challenges when it comes to manipulating dataframes. A common task is appending rows to a dataframe based on a list of values. In this post, we'll explore how to efficiently achieve this in a straightforward manner.

The Problem

Suppose you have a DataFrame called df and a list of values. The goal is to create a new column that incorporates each item from the list into the dataframe while repeating the existing rows accordingly. Here's an example setup:

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From this setup, you want the resulting DataFrame to look like this:

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The Solution

Step 1: Setup Your DataFrame

You’ll start with your initial DataFrame and the list of values:

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Step 2: Create a New DataFrame

Initiate an empty DataFrame where you will concatenate your results:

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

Step 3: Loop Through the List

Use a loop to iterate through each item in your list. Within the loop, you will assign the current week value to the 'week' column in the DataFrame:`

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

Step 4: Reset the Index

After the loop, reset the index of the new DataFrame to have a clean index from 0:

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

Final Output

If you print final_df, you will see your desired structure:

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This should display:

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

Conclusion

Remember, practice makes perfect! Try different scenarios with larger data sets to deepen your understanding.