Python Pandas Tutorial: Pandas Apply Function and Vectorization #15

In this video we are going to discuss about Pandas apply function in greater details. Applying a function to all rows in Pandas DataFrame is one of the most common operations for cleaning and unifying messy and complex data sets for easy access and analysis.

This video tutorial will cover complete understanding of below points:
1.) What is Pandas Apply function?
2.) How to use Pandas Apply function?
3.) How to use apply function on pandas series?
4.) Use loc with Pandas apply function
5.) How to create sales bucket using user define function with Pandas apply function?
6.) Use apply function with lambda (anonymous function).
7.) Why Pandas apply function works slow on large data set?
8.) How to use vectorization for fast execution on large data set?
9.) Calculate the execution time between pandas apply and vectorization.
10.) More...

[alkeshkumar]

Sir when we passes calcSales fun in lambda expression what is x[total sale amount] and how it x is referring to df column at 6:47

[alokjena]

Hi Sir I am beginner in python programming can you guide me where I will start from. Sir if you provide a class please let me know.

[tobedeleted]

3:10 doesn't make sense, so are you getting the max price for that customer or overall? wouldnt max(df.Quantity) give you the max quantity of the entire DataFrame, not just for this customer? .. why was only 1 customer record shown for Willie Oliver, I don't understand that part?
wouldnt df.loc[:, "Customer", "Total Sales Amount"].apply(max, axis=rows) give all records and the max values for each record ? , a bit confused