Basic And Advanced Graph Plotting In Python Masterclass

Data visualization using Python | Create high quality visually appealing plots | Import variety of data formats

What you'll learn
You will learn how to use Python to create stunning charts and data visualizations
Create complex data visualizations using Matplotlib
Create custom Matplotlib settings for journals, and conference plots
Student, researchers, data scientist and teachers who wants to elevate their figures to the next level
Explore dimensionality of the data, data interpretation
Import multiple datasets and plot
Requirements
No prior knowledge in programming is required
You will need a desktop or a laptop computer
People curious about data analysis, data visualization, or data science
Description
Welcome to the finest data visualization or graph plotting course using Matplotlib  on the web, in my viewpoint. The technical skills you learn in this course will help you advance in your career as a data scientist, researcher, or science student. This course is designed for students of science & engineering interested in producing top-notch scientific graphics as well as researchers and data scientists. First,  I'll give you a brief overview of Python. Along with that, I'll cover the essential packages, such as Numpy, Pandas, and Matplotlib, that we'll use often in this course. Before getting into more complex preparation for posters and scientific publications, I'll start with the fundamentals. At the completion of this course, You will be able to plot any form of data from different varieties of data files.In this course, you will learn:Working with JupyterLabCreate complex data visualizations using MatplotlibImport and extract data from CSV, TXT, MAT, and H5 filesImport multiple datasets and plotCreate custom Matplotlib settings for journals, and conference plots2D colormap plots and customization3D plots and customization  What distinguish this course from the hundreds of others available online?While most online courses follow simply descriptive material and take endless hours, this short course highlights the necessity of visually appealing plots as a need for any kind of scientific or professional presentation, as well as the integration of visualizations from various datasets. Instead of spending endless hours on hypothetical data, this combines the ideas, tactics, and crucial settings.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Installing Python

Section 2: Plotting using Matplotlib

Lecture 3 Matplotlib Introduction | Basic line plots

Lecture 4 Customization of line plot part I

Lecture 5 Customization of line plot part II

Lecture 6 Export settlings vector (PDF, SVG) and raster graphics (PNG, JPG)

Section 3: Advanced Plotting

Lecture 7 Subplots: Introduction

Lecture 8 Semilog, loglog plots

Lecture 9 Double y-axis plots

Lecture 10 Inserting Image to a data plot

Section 4: Importing experimental data and plotting

Lecture 11 Importing (*.txt) data file and plotting

Lecture 12 Importing CSV files and plotting

Lecture 13 Importing Matlab's MAT file and plotting

Lecture 14 Importing (*.H5) files and plotting

Lecture 15 Importing multiple data files from a folder

Section 5: 2D Colormap plots

Lecture 16 Introduction to 2D Colormap plots

Lecture 17 Customization of 2D colormap plots, eg colorbar, colormap

Students (undergrad and graduate) keen in data visualization,Researchers, data scientists,Anyone who wants to learn data visualization,Explore dimensionality of the data