How you can master pandas Apply and Transform methods with or without groupby?

Why use apply() and transform() on DataFrame?

• Both apply() and transform() are used to manipulate an entire DataFrame or any specific column in given DataFrame.

There are 3 main differences when using apply() and transform():

1. transform() can take a function, a string function, a list of functions, and a dict. However, apply() is only allowed a function.
2. transform() cannot produce aggregated results
3. apply() works with multiple Series at a time. But, transform() is only allowed to work with a single Series at a time.

In this hands-on tutorial you will learn the following:

• What is function calling in pandas?
• How to perform transformation in pandas at dataframe level or at single column level?
• What are apply and transform methods in Pandas?
• When you can use apply() and when to use transform()?
• How to combine lambda with both apply and transform methods
• Combing both apply and transform methods with groupby

You can get the code used in this tutorial from the link below: https://github.com/prodramp/publiccode/tree/master/pandas/function-calling

Dataset URL: https://github.com/prodramp/publiccode/tree/master/datasets

Please visit: https://prodramp.com @prodramp https://www.linkedin.com/company/prodramp

Content Creator: Avkash Chauhan (@avkashchauhan) https://www.linkedin.com/in/avkashchauhan

Tags: #webdevelopment, #frontend #react #python #layout #fullstackdevelopment #pandas #matplotlib #datavisualization #conda #webapp #apply #transform #github #groupby #prodramp #wetogethervc ... https://www.youtube.com/watch?v=T9q1hXqGXao