pandas dataframe create new column using function
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Title: Creating a New Column in a Pandas DataFrame Using a Function - A Step-by-Step Tutorial
Introduction:
Pandas is a powerful data manipulation library in Python that provides data structures like DataFrames for efficient data analysis. One common task in data analysis is creating new columns based on existing data or applying a function to transform values. In this tutorial, we'll explore how to create a new column in a Pandas DataFrame using a custom function.
Requirements:
Make sure you have Pandas installed in your Python environment. If not, install it using:
Step 1: Import Pandas
Start by importing the Pandas library into your Python script or Jupyter notebook.
Step 2: Create a Sample DataFrame
For demonstration purposes, let's create a sample DataFrame with some data.
Step 3: Define the Function
Now, define a custom function that you want to apply to create the new column. In this example, let's create a function that adds a bonus to the salary.
Step 4: Apply the Function to Create a New Column
Use the apply function to apply your custom function to a column and create a new one.
This will add a new column named 'Salary_with_bonus' to the DataFrame, where each value is the result of applying the add_bonus function to the corresponding 'Salary' value.
Step 5: Alternative Approach using Lambda Function
You can achieve the same result using a lambda function, which is a concise way to define small, one-time-use functions.
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