Numpy,pandas and data visualisation course 2023

Practically each scientist working in Python attracts on the facility of NumPy.

NumPy brings the computational energy of languages like C and Fortran to Python, a language a lot simpler to study and use. With this energy comes simplicity: an answer in NumPy is usually clear and elegant.

We’ll begin with a NumPy primer to introduce arrays and array properties, apply frequent operations like indexing, slicing, filtering and sorting, and discover necessary ideas like vectorization and broadcasting.

Pandas is an open-source library that’s made primarily for working with relational or labeled data each simply and intuitively. It gives varied data constructions and operations for manipulating numerical data and time collection. This library is constructed on high of the NumPy library. Pandas is quick and it has excessive efficiency & productiveness for customers.

Why study pandas?

In case you’ve hung out in a spreadsheet software program like Microsoft Excel, Apple Numbers, or Google Sheets and are desirous to take your data evaluation abilities to the subsequent degree, this course is for you!

Data Evaluation with Pandas and Python introduces you to the favored Pandas library constructed on high of the Python programming language.

Pandas is a powerhouse instrument that lets you do something and all the things with colossal data units — analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleansing, calculating, and extra!

I name it “Excel on steroids”!

Over the course of greater than 19 hours, I’ll take you step-by-step by way of Pandas, from set up to visualization! We’ll cowl a whole bunch of various strategies, attributes, options, and functionalities packed away inside this superior library. We’ll dive into tons of various datasets, brief and lengthy, damaged and pristine, to display the unimaginable versatility and effectivity of this bundle.

Data Evaluation with Pandas and Python is bundled with dozens of datasets so that you can use. Dive proper in and comply with together with my classes to see how straightforward it’s to get began with pandas!

Whether or not you’re a brand new data analyst or have spent years (*cough* too lengthy *cough*) in Excel, Data Evaluation with pandas and Python affords you an unimaginable introduction to probably the most highly effective data toolkits accessible right this moment!

Matplotlib is straightforward to make use of and a tremendous visualizing library in Python. It’s constructed on NumPy arrays and designed to work with the broader SciPy stack and consists of a number of plots like line, bar, scatter, histogram, and so forth.

Matplotlib Anatomy

Because the title implies, on this part you’ll find out how Matplotlib works and how a wide range of charts are generated.

It offers you a stable understanding and a whole lot of aha-moments in the case of creating and / or customizing charts that you just haven’t handled earlier than.

Create 2D Charts

On this part, you’ll generate plethora of charts utilizing Matplotlib OOP, and Pandas and combine them collectively to attain the utmost effectivity and granular management over graphs.

Axes Statistical Charts

Right here we’ll learn to make statistical charts corresponding to Auto Correlation, Boxplots, Violinplots and KDE plots with Matplotlib OOP and Pandas.

Seaborn

Seaborn, a high-level interface to Matplotlib helps make statistical plots with ease and appeal. It’s a must-know library for data exploration and tremendous straightforward to study. And on this part, we’ll create Regression plots, Rely plots, Barplots, Factorplots, Jointplots, Boxplots, Violin plots and extra.