Dynamic Content Generation in Pandas DataFrames

How to generate content dynamically using Pandas

In data processing tasks, dynamically generating content based on existing data is a common requirement. In this tutorial, we’ll explore how to leverage the power of pandas to dynamically fill columns in a DataFrame using Python.

Problem Statement

We have a pandas DataFrame containing various columns, and we want to dynamically generate content for one column based on the values of other columns. This could be applicable to scenarios such as generating personalized messages, calculating derived values, or formatting data for specific outputs.

Solution

We can use pandas’ apply function along with custom functions to dynamically fill columns based on data from other columns.

Step 1: Import Required Libraries

import pandas as pd

Step 2: Create a DataFrame

# Sample DataFrame
data = {
    "name": ["Alice", "Bob", "Charlie"],
    "surname": ["Smith", "Jones", "Brown"],
    "message_template": ["Hello {name} {surname}!", "Hey {name}, how's it going?", "Hi there, {name} {surname}!"]
}

df = pd.DataFrame(data)