Interactive Data Visualization with Python and Bokeh

Category: Tutorial

Posted on 2021-06-25, by mitsumi.



MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 3.46 GB | Duration: 6h 46m

What you'll learn
Build advanced data visualization web apps using the Python Bokeh library.
Create interactive modern web Descriptions that represent your data impressively.
Create widgets that let users interact with your Descriptions.
Learn all the available Bokeh styling features.
Integrate and visualize data from Pandas DataFrames.
Create dynamic graphs that Description real-time data.
Description time-series data.
Integrate your data visualization apps with Flask apps.
Deploy the apps in live servers.
Learn how to troubleshoot Bokeh apps.

A working computer (Windows, Mac, or Linux)
Basic knowledge of Python

If you love Python and want to impress your clients or your employer with impressive data visualization on the browser, Bokeh is the way to go. This course is a complete guide to mastering Bokeh, a Python library for building advanced and data dashboards containing beautiful interactive visualizations. The course will guide you step by step from Descriptionting simple datasets to building rich and beautiful data visualization web apps that Description data in real-time and allow web users to interact and change the behavior of your Descriptions via the internet from their browsers.

Whether you are a data analyst, data scientist, statistician, or any other specialist who deals with data regularly, this course is perfect for you. It will give you the skills to visualize data in a way that excites your audience and eventually sells your product or your idea much easier. All you need to have to learn Bokeh is some basic prior knowledge of Python.

The course also contains exercises to help you check your skills as you progress. You will be given access to various data samples and provided with additional examples to enforce your Bokeh skills. The course is estimated to take you around four weeks to complete assuming you devote 10-20 hours/week depending on your productivity skills.

Who this course is for:
Anyone involved in the data industry
Anyone who is already familiar with Python basics



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