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Panel And Hvplot: A High-Level Data Visualization For Python

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Published 1/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.97 GB | Duration: 12h 58m

Simplify Visualization and Interactive Dashboards with Super Easy and Flexible Holoviz tools including Panel and hvPlot

What you’ll learn
Understand the key concepts of data visualization and its significance in analyzing and communicating data effectively.
Develop proficiency in using Panel and hvPlot libraries to create interactive and visually appealing data visualizations.
Explore the advanced features and customization options of Panel for building interactive dashboards.
Apply data visualization techniques to real-world datasets and gain insights from data.
Learn best practices for designing visually appealing and impactful data visualizations.
Gain practical experience in creating end-to-end data visualization projects using Panel and hvPlot.

Requirements
Basic Python Knowledge: A fundamental understanding of Python programming is necessary to follow along with the course materials. Familiarity with Python syntax, data types, variables, and functions will help you grasp the concepts more effectively.
Data Analysis and Visualization Basics: Having a basic understanding of data analysis and visualization principles will be helpful. This includes concepts like data manipulation, data structures, and basic plotting techniques (e.g., Matplotlib).
Jupyter Notebooks: A basic understanding of Jupyter notebooks will be beneficial as the course may involve working with Jupyter notebooks for code demonstrations and exercises. Knowing how to execute code cells and navigate through a notebook will enhance your learning experience.

Description
Unlock the power of data visualization in Python with Panel and hvPlot! In this comprehensive Udemy course, you will dive into the world of high-level data visualization techniques using two powerful libraries: Panel and hvPlot. Whether you’re a data scientist, analyst, or developer, this course will equip you with the skills and knowledge to create stunning visualizations and interactive dashboards with ease. Join now and take your data visualization skills to new heights!By the end of this course, learners will be able to:Master the fundamentals of Panel and hvPlot: Gain a comprehensive understanding of Panel and hvPlot libraries, their key concepts, and how they fit into the Python data visualization ecosystem.Create interactive dashboards: Learn how to design and build interactive data dashboards using Panel, enabling users to explore and analyze data with ease.Enhance visualizations with hvPlot: Explore the powerful capabilities of hvPlot to create stunning and dynamic visualizations, incorporating a wide range of chart types, customizations, and interactivity.Integrate Panel and hvPlot with existing workflows: Discover how to seamlessly integrate Panel and hvPlot into your existing Python data analysis workflows, leveraging their compatibility with popular data manipulation and analysis libraries.Customize and style your visualizations: Unlock the ability to customize and style your visualizations in Panel and hvPlot, allowing you to create visually appealing and professional-looking dashboards tailored to your specific needs.Deploy and share your dashboards: Learn how to deploy and share your interactive dashboards created with Panel and hvPlot, enabling you to collaborate with others, present insights, and showcase your work effectively.Manage data visualization challenges in your real-world projects and applications: Apply your newly acquired knowledge to real-world projects and explore practical use cases across various domains, ensuring you are well-prepared to tackle data visualization challenges in your professional career.By the end of this course, you will have the skills and confidence to leverage Panel and hvPlot to create powerful, interactive, and visually compelling data visualizations and dashboards in Python.Enroll now and unlock the potential of these high-level tools for your data visualization projects.

Overview
Section 1: Introduction to the Course

Lecture 1 Anaconda Installation

Lecture 2 What are Panel and hvPlot in Holoviz?

Lecture 3 Installation and Setting up

Section 2: hvPlot Gallery

Lecture 4 hvPlot (Part1)

Lecture 5 hvPlot (Part2)

Section 3: Customization

Lecture 6 Plot Customization (Part1)

Lecture 7 Plot Customization (Part2)

Section 4: Indicators

Lecture 8 Indicators (Part1)

Lecture 9 Indicators (Part2)

Section 5: Widgets

Lecture 10 Widgets (Part1)

Lecture 11 Widgets (Part2)

Section 6: Controlling Style using CSS

Lecture 12 Controlling Style & Layout Design

Section 7: Layout Design

Lecture 13 Layout 1 (Row, Columns, Divider, and Spacer)

Lecture 14 Layout 2 (Grid Box, Widget Box, and GridSpec)

Lecture 15 Layout 3 (Tabs, Card, FloatPanel, Templates)

Lecture 16 Layout 4 (Arrange Components)

Lecture 17 Layout 5 (Applying a Design)

Section 8: Interaction with Widgets

Lecture 18 Interaction (Part1)

Lecture 19 Interaction (Part2)

Lecture 20 Interaction (Part3)

Lecture 21 Interaction (Part4)

Lecture 22 Interaction (Part5)

Lecture 23 Interaction (Part6)

Lecture 24 Interaction (Part7)

Section 9: Interaction with DataFrame

Lecture 25 Interaction with DF (Part1)

Lecture 26 Interaction with DF (Part2)

Lecture 27 Interaction with DF (Part3)

Lecture 28 Interaction with DF (Part4)

Lecture 29 Interaction with DF (Part5)

Section 10: Dashboard Design

Lecture 30 Case Study 1 (BASIC – tricks and customizations)

Lecture 31 Case Study 2 (INTERMEDIATE – tricks and customizations)

Lecture 32 Case Study 3 (ADVANCED – tricks and customizations)

This course is designed for Python developers, data analysts, data scientists, and anyone interested in harnessing the power of Panel and hvPlot libraries for high-level data visualization in Python. Whether you are a beginner looking to expand your data visualization skills or an experienced practitioner seeking to enhance your toolkit, this course provides a comprehensive introduction and in-depth exploration of Panel and hvPlot.


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