Essential Business Data Manipulation Using Python and Pandas

PYTHON bner data analysis using the Pandas library to manipulate datasets and automate tasks practical application

How to use Python and Pandas to manipulate datasets

How to use Python as an alternative to Excel

Learn object-oriented programming using Python

Understand how functions work

Understand the difference between Series and Dataframes

Understand how to clean data using Python Pandas Functions

Python Anaconda installation

Basic knowledge of programming or coding concepts and logic

These lectures are the result of my personal crash course Python programming learning experience. I have recently changed jobs and have had the opportunity to learn Python programming to analyse and manipulate data. I have compiled some essential techniques as well as tips to make sure you understand how Python object-oriented programming works.

I am a real world finance professional and I have compiled these lectures on the basis of my experience in my actual job. We will go through the basics as well as some more advanced techniques to help you create a more streamlined process of data manipulation. We will mostly be working with CSV and Excel files, however we also discuss how to import data in other formats.

We start with a background of Python programming language as well as the Pandas library. We will also go through essentials of using the Jupyter Notebooks programming environment. We will then explore ways to import data, and then go through a multitude of examples on how to inspect and manipulate data. We also discuss how to clean data using string functions, as well as how to avoid errors when creating or adding data. Finally, we will look at how to summarise and then export our cleaned and finalised data.

Those wanting to explore alternative data manipulation software aside from Excel

Bner Python Pandas data analysts

Students that don't have much to learn Python Pandas

Transitioning students from SAS or SQL to Python Pandas



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