Course Introduction

What is Pandas?

Starting With Pandas And iPython

Working with Jupyter Notebooks

Important Jupyter Notebook Commands

Working with CSV, Excel, TXT and JSON Files

Working with API Response

Indexing and Slicing Dataframe Tables [Part 1]

Indexing and Slicing Dataframe Tables [Part 2]

Deleting Columns and Rows

Adding and Updating new Columns and Rows

Learn Data Analysis Fundamentals: Pandas, DataFrames, Jupyter, iPython, and Commands

Shubham is a software developer with a passion for teaching. He has worked with many funded startups, self-projects and as a top-rated freelancer on marketplaces.

Shubham has taught programming and digital marketing to over 50,000 students online and offline as an Instructor.

Shubham has mastered explaining very complex topics in the simplest manner that is easy to understand and follow. His video courses are also used by companies to train their employees and by colleges to prepare their students and upgrade skills according to industry requirements.

Shubham Sarda

Welcome to the Data Analysis Crash Course. The beauty of this course is that it aims at simplifying the complex concepts for beginners, while focusing on practical aspects of data analysis. There's no need to feel overwhelmed by large chunks of data anymore. We will teach you how to navigate through it with ease using Python and the Pandas library.

In this course, we will start with the very basics of data analysis. As we progress, we'll dive deep into using tools such as Pandas, iPython, and Jupyter Notebook. We understand how important it is to work comfortably with different data formats. Therefore, we will also cover working with various types of files like CSV, Excel, TXT, JSON, and even API responses. You will learn how to efficiently handle and manipulate these files for your data analysis needs.

One key component we will focus on is the 'DataFrame', an essential aspect of the Pandas library. Here, you will learn everything from indexing, slicing to adding, and deleting within DataFrames. Our goal is to equip you with the necessary skills to leverage the benefits of these high-performance, easy-to-use data structures and data analysis tools provided by the open-source Pandas library.

This course brings value not only to those interested in data science. It is also useful for fields like finance, neuroscience, economics, advertising, web analytics, statistics, social science, and many areas of engineering where data analysis plays a vital role.

By the end of this course, we promise that you will immerse yourself not just in the know-how of Pandas, but also imbibe a solid understanding of data analysis. You will be one step closer to mastering data analysis, being ready to explore this vast field in-depth in the future.

Certificate Details

Data Analysis Crash Course For Beginners

Course Goals

Shubham Sarda