Graph plotting in Python for scientific Journals & papers


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

What you will 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

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 JupyterLab
  • Create complex data visualizations using Matplotlib
  • Import and extract data from CSV, TXT, MAT, and H5 files
  • Import multiple datasets and plot
  • Create custom Matplotlib settings for journals, and conference plots
  • 2D colormap plots and customization
  • 3D plots and customization

  What distinguish this course from the hundreds of others available online?


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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.

English
language

Content

Introduction

Introduction
Installing Python

Plotting using Matplotlib

Matplotlib Introduction | Basic line plots
Quiz 1
Customization of line plot part I
Quiz 2
Customization of line plot part II
Quiz 2a
Quiz 3
Export settlings vector (PDF, SVG) and raster graphics (PNG, JPG)
Quiz 4

Advanced Plotting

Subplots: Introduction
Quiz 5
Semilog, loglog plots
Quiz 6
Double y-axis plots
Quiz 7
Inserting Image to a data plot

Importing experimental data and plotting

Importing (*.txt) data file and plotting
Quiz 8
Importing CSV files and plotting
Quiz 9
Importing Matlab’s MAT file and plotting
Quiz 10
Importing (*.H5) files and plotting
Quiz 11
Importing multiple data files from a folder
Quiz 12
Using Pandas to import data files and plot
Quiz 13

2D Colormap plots

Introduction to 2D Colormap plots
Quiz 12
Customization of 2D colormap plots, eg colorbar, colormap
Quiz 13

Custom Plot settings for journals, and conference papers

Plot settings for Journal or conference paper | Export Figures
Quiz 14

Vector fields , contour, and 3D plots

Visualizing Vector Fields
Quiz 15
Contour and Contourf plots
Quiz
3D plots

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