Learn R and Python Programming for Data Visualization

From Raw Data to Insightful Narratives: Creating Visual Charts
Free tutorial
Rating: 4.6 out of 5 (15 ratings)
2,295 students
1hr 56min of on-demand video
English [Auto]

Fundamental Programming Concepts in R: Grasp the core elements of R programming, including string manipulation, Boolean logic, control structures.
Versatile Data Visualization Techniques: Explore a wide array of charts and plots, from basic plot charts and scatterplots in R, to more complex visualizations
Utilization of Key Data Visualization Libraries: Harness the power of industry-leading Python libraries such as Matplotlib and Seaborn
Data Analysis and Insight Extraction: Go beyond just creating visuals. Learn to interpret charts, identify underlying patterns, and extract actionable insights


  • No programming experience required for R, you will learn everything from the beginning.
  • If you have some previous knowledge of python programming, it would be useful.


Unlock the power of data visualization by mastering both R and Python, the leading programming languages in the realm of data science. This comprehensive course is designed for learners of all levels, whether you're a beginner with no prior coding experience or a professional looking to enhance your data representation skills.

Course Highlights:

  1. Foundation in R Programming: Dive into the world of R, a language crafted specifically for statistical analysis and data visualization.

    • String Manipulation: Understand the intricacies of working with text data, an essential skill for data cleaning and preprocessing.

    • Boolean Logic: Get to grips with logical operations, a cornerstone of any programming language.

    • Control Structures: Master the "if-else" conditional statements, and loop constructs like "while" and "for," giving you the tools to handle data more flexibly.

    • Data Structures: Delve into the heart of R with structures like Vectors, Lists, Matrices, and Arrays. Learn how to efficiently organize, access, and modify your data.

  2. Visualizing Data with R: Translate your data into meaningful visuals.

    • Plot Charts: Learn the basics of plotting and customize your charts to represent data effectively.

    • Scatterplots: Dive into bivariate data analysis and observe relationships and patterns.

    • Bar, Pie, and Line Charts: Showcase categorical data, compare parts-to-whole relationships, and track changes over periods, respectively.

  3. Introductory Python for Visualization: Transition into Python, another titan in the data science world, renowned for its flexibility and robust libraries.

  4. Crafting Visual Stories with Python:

    • Bar and Horizontal Bar Charts: Ideal for representing categorical data, understand when and how to use both vertical and horizontal bar charts.

    • Bubble and Donut Charts: Add an element of depth and segment your data with these visually appealing charts.

    • Line and Time Series Charts: Track changes over time, be it stock prices or temperature fluctuations.

    • Pie and Sunburst Charts: From simple pie charts to hierarchical sunbursts, comprehend the best way to represent hierarchical datasets.

Why This Course?

In the digital age, data is abundant, but the true power lies in harnessing this data, analyzing it, and translating it into actionable insights. Visualization is the bridge that can transform complex datasets into comprehensible, insightful visuals. Through this course, not only will you acquire the skills to craft compelling data stories using R and Python, but you will also sharpen your analytical edge, making you an indispensable asset in any data-driven decision-making process.

Whether you're a budding data analyst, a researcher, a business professional, or simply curious about the world of data visualization, this course will provide you with a holistic learning experience. So, embark on this enlightening journey and turn raw data into insightful narratives.

Who this course is for:

  • Budding Data Enthusiasts: Individuals eager to kickstart their journey in the realm of data science and analytics, looking for a comprehensive introduction to data visualization using R and Python.
  • Researchers and Academics: Professionals in research fields who deal with vast amounts of data and need effective ways to visualize, interpret, and present their findings.
  • Business Professionals: Decision-makers, managers, and analysts seeking to enhance their data-driven decision-making skills by learning to create and understand insightful visual representations of their data.
  • Career Switchers: Individuals from non-technical backgrounds aiming to transition into data roles and seeking a foundational understanding of data visualization tools and techniques.
  • Educators and Trainers: Those involved in teaching or training roles, wanting to integrate powerful data visualization examples and practices into their curriculum or training sessions.


Docker | Kubernetes | AWS | Azure | ML | Linux | Python
Pranjal Srivastava
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I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer.

I have authored 78 courses with over 115,000 students worldwide across 175+ countries on wide array of technologies like devops, containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

Cloud Professional | Content Creator | Edupreneur
Harshit Srivastava
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I am Self-Taught developer who had worked on various platforms using varied languages, and involved in various Projects both Open Source and Proprietary.

I have developed Web and Android Applications, chrome Extension, worked on various frameworks, fixed bugs for some projects, and explored numerous others. I think education and learning should be free and open, not be bound with restrictions like attending classes or going to college, People from all age groups, gender, faith, race, nations, etc must get equal privilege. When entire world would act this way like being a single FAMILY, we would truly realize VALUE of Knowledge and Human Life.

Currently I am teaching more than 152,000 students from 189 countries across the world.

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