Python-based data visualization uses the Python programming language and its libraries to transform data into visual representations, such as charts, graphs, and interactive dashboards. Python’s libraries, including Matplotlib, Seaborn, Plotly, and Bokeh, offer customizable plot types and interactive features to craft compelling visual narratives. Through data storytelling and customization, Python shares insights and effectively communicates them, making it an indispensable skill for anyone working with data.
In this course, we will begin by grasping the importance of data visualization and exploring essential Python libraries such as Matplotlib, Seaborn, and Plotly. You will learn to customize and enhance visualizations, adjust colors, labels, and legends, and understand the principles of effective data storytelling. The course delves into advanced topics such as creating interactive dashboards and dynamic data plots. We will work on practical projects and real-world examples to equip us with the skills to turn raw data into informative visuals using Python.
Upon completion, we will master Python-based data visualization from core principles to practical skills, Matplotlib, Seaborn, and Plotly, and transform raw data into compelling visuals. We will acquire tools to create visuals, convey insights, and make data-driven decisions with confidence.
publication date
2023-09-22
what you will learn
Understand the importance/principles of effective data visualization
Learn Matplotlib, Seaborn, and Plotly to create various visualizations
Learn to tailor colors, labels, and styles to enhance visuals
Craft data visualizations to create compelling narratives
Create engaging and user-friendly interactive data displays
Explore geospatial data mapping and location-based visualizations
key features
Learn to create various visualizations with Python libraries such as Matplotlib, Seaborn, and Plotly * Acquire skills to create visuals and communicate insights, explore storytelling and visualization * Work on real-world projects and case studies to apply data visualization techniques to real data
approach
The course adopts a practical, hands-on approach to Python-based data visualization. It explains the fundamentals and progressively guides learners through using libraries such as Matplotlib, Seaborn, and Plotly, and engages in real-world examples to build skills in customization and storytelling. The complexity of the subjects is progressively addressed, guiding learners through a gradual learning curve. Interactive dashboards are incorporated to facilitate skill development.
audience
This course caters to a wide audience from beginners with no programming experience to experienced data professionals, programmers looking to expand their skillsets, business professionals seeking practical data visualization knowledge, and students/researchers aiming to strengthen their data visualization proficiency using Python. There are no specific prerequisites for this course. However, having a basic understanding of mathematics and readiness to learn are helpful attributes for successfully completing the course.
short description
This beginner-friendly course takes us on a journey into data visualization. You will learn to transform raw data into stunning visuals using Matplotlib, Seaborn, and Plotly. From charts to dynamic heatmaps, we will master the essentials. Fuel your curiosity, enhance your skills, and communicate insights effectively to become a Python data visualization pro!
subtitle
Transform data into visual insights with this comprehensive guide on Python-based data visualization
keywords
Data Visualization, Python, Matplotlib, Seaborn, Plotly, Interactive Dashboards, Data Storytelling, Python Charting, Geospatial Mapping, customize visuals with Python, Data Analysis, Visualization Tools
Product ISBN
9781805127598
