Python Joins/Merge and common Attributes/Methods in Pandas

What you'll learn
Inner Join/Merge in Pandas
Left Join/Merge in Pandas
Right Join/Merge in Pandas
Outer Join/Merge in Pandas
Concatenation in Pandas
Merging/Joining on multiple columns
Join/Merge more than 2 dataframes in single line of code
Join/Merge on different column names
Join/Merge on Index
Validating concatenation
Join/Merge on Multi-Index
Some common methods/attributes: group by( ), agg ( ), Description ( ), astype ( ) etc.

Requirements
Some basic knowledge of Python might be helpful.
Description
In this course you will learn about Python Joins with simple examples so you can understand the syntax and how merge/joins actually work.

You will further learn:-

All types of Joins have been explained with the help of diagram and then executed in python

Concatenation along with indexes have been explained very well. This will help to understand basic difference between concatenation and merge.

Powerful techniques like merging/Joining on Single index, Multi-Index have been demonstrated.

The dataset is built on-screen (values in dictionary and then converted into dataframe), so that you can learn and change it accordingly (if needed) to experiment and understand concepts better.

The tricks to handle merge/join when the column name is different have been explained.

To Merge/Join more than 2 dataframes in single line of code have been demonstrated.

Python common attributes along with methods have been explained very well. You will be able to understand the basics of it in a better way.

How to handle multiple valuesets using matDescriptionlib have been demonstrated as well.

As you all know python is the number #1 programming language of 2021. There are various job opportunities in the market if you have a solid understanding of this language. The syntax is simple and easy to learn. As it is bit comprehensive, in this course, I have primarily kept my focus on python joins/merge/concatenation and some basic attributes so that you can build your own dataset in python and explore that using the attributes/methods/ techniques (as explained in this course).

Who this course is for:
Python developers

Screenshots