Graph plotting in Python for scientific Journals & papers

Graph plotting in Python for scientific Journals & papers

Graph plotting in Python for scientific Journals & papers

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

Language: english

Note: 4.9/5 (8 notes) 1,079 students  New course 

Instructor(s): Dr. Manabendra Kuiri

Last update: 2022-07-22

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 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?

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.

 

Who this course is for

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

 

Course content

  • Introduction
    • Introduction
    • Installing Python
  • Plotting using Matplotlib
    • Matplotlib Introduction | Basic line plots
    • Quiz 1
    • Assignment 1: Basic Plots
    • Customization of line plot part I
    • Quiz 2
    • Customization of line plot part II
    • Quiz 2a
    • Quiz 3
    • Customization of Plots
    • 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

 

Graph plotting in Python for scientific Journals & papersGraph plotting in Python for scientific Journals & papers

 

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