Python - How to Update Multiple Columns in Dataframe

In this tutorial, you will learn "How to Update Multiple Columns in Dataframe" in Pandas. For this I used Python 3.12 runtime.

Pandas is a powerful and flexible open-source data analysis and data manipulation library for Python. It provides data structures and functions needed to manipulate structured data seamlessly.

Python - How to Add Multiple Columns in Dataframe https://youtu.be/JJ06bhTTmnQ

Explanation: Create a Sample DataFrame: We start by creating a sample DataFrame.

Define a Function to Generate Multiple Columns: This function takes a row of the DataFrame as input and returns a pd.Series object with new columns as # SellingAmt = Quantity * SellingPrice # Profit = SalesAmount - ProductCost

Use apply to Apply the Function Row-wise: We use the apply method with axis=1 to apply the custom function to each row of the DataFrame.

A pd.Series in pandas is a one-dimensional labeled data structure that can hold various types of data, such as integers, floats, strings, and other Python objects.

Indexing: Each element in a pd.Series has a unique identifier called an index. You can think of a pd.Series as a column in a spreadsheet or a single column of a database table.

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