R Tutorial : Interactive Data Visualization with rbokeh
Skills:
Data Literacy80%
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Hi I am Omayma Said and welcome to the "interactive data visualization with rbokeh" course.
n this course, We will focus on rbokeh; a library for interactive web-based plots.
It is the R interface for the python library Bokeh.
and it is mainly written and maintained by Ryan Hafen.
But Why R bokeh?
rbokeh enables you to create different types of interactive plots.
It allows you and your audience to get more info through ineracting with the plots. The output can shared, embedded in HTML documents or used in web applications.
Since data visualization is an integral part of the data analysis process and a means of communication, the visulaizations should be:
- Self explanatory through the use of (colors, titles, labels, and other visual elements)
- Informative to deliver a certain message easily and
- Persuasive to emphasize the results of an analysis
In this course, we will start by the basics of rbokeh plots in chapter one.
In chapter two, you will learn how to customize your figures using aesthetic attributes and figure options.
In chapter three, you will learn how to put your data in the right format to fit the desired figure.
Finally, in chapter four, you will learn how to combine multiple figures in one layout using grid plots and how to create interactive maps.
In order to create the right types of visualizations to convey your message, you usually need to put your data in the desired format.
In this course we will mainly use the Tidyverse packages like dplyr and tidyr for data manipulation.
So if you are not very familiar with them, you can find introductory tidyverse courses on DataCamp.
But don't worry we'll have a quick refresher for the most important functions which we'll use throughout the course.
Let's st
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