Quick and expressive data analysis requires good tools and knowledge of them. In this course, you'll explore the world of data science by learning core Pandas functionalities, including its IO capabilities, plotting methods, and DataFrames.
As an individual working with data, from business analysts to data scientists, you desire a quick feedback loop that enables you to materialize and easily visualize your ideas. Time spent on developing and debugging programs or clicking around spreadsheets is often wasted. In this course, Pandas Fundamentals, you'll learn how to quickly read the data, perform desired analysis, and output it in a neat format along with pleasant plots. First, you'll explore data input and output. Next, you'll discover how to index and filter your data. Finally, you'll delve into how to work with groups, along with creating plots. After finishing this course, you'll have the necessary knowledge to manipulate data in basic forms, and be able to utilize your time more efficiently when figuring out how to transform your data to reach the desired effect. Software required: Anaconda Python.
Paweł is a software engineer passionate about knowledge sharing. He's especially focused on processing and exploring data sets (be it big or small) and is always searching for emerging tools that will make working with data simpler in the future.
Course Overview Hi everyone. My name is Pawel Kordek, and welcome to my course, Pandas Fundamentals. Currently I am a software engineer at TomTom where I develop geography cross search functionality for the online APIs. Data scientist has been called the sexiest job of the 21st century. Regardless of this statement being true, digitalized data is everywhere, and skills that contain these never-ending streams of information are sought like never before, so why not do some data science yourself? In this course we are going to learn Pandas, a fantastic data analysis library for Python, which along the art programming languages is the most complete and popular open source programming tool for doing data science. We'll start this course by introducing core Pandas concepts, and then we'll cover topics that form the foundations of data analysis. This includes data input and output, indexing and filtering your data, working with groups, and creating plats. By the end of this course you will know how to manipulate your data in basic forms with the use of Python. Before beginning the course you should have a basic understanding of Python programming language, but no prior experience with any data analysis library is assumed. I hope you will join me on this journey to learn this amazing tool with the Pandas Fundamentals course at Pluralsight.