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Introduction to Data Visualization

A beginner's guide to data visualization tools and techniques.

Microsoft Excel

You can use Excel from Microsoft Office to create a variety of visualizations and customized charts. 

You can download Microsoft Excel, and the rest of the MS Office programs, via Office 365. There's no cost to you as a Florida Tech Student! Get more information here: Office 365 @ Florida Tech

R

is a free, open source software that helps you manipulate, calculate, and visualize data. Using R requires a bit of programming knowledge. But, as it is an open source software, there is a lot of help and guidance available. 

Below is a list of widely-used R visualization libraries:

Base graphics package: The base package comes standard with R and does not need to be installed. It contains functions which can can generate simple visualizations, but the level of detail is limited. For more complex visualization capabilities, see ggplot2. 

ggplot2: Based on the grammar of graphics, the idea that every chart can be built from the same components, ggplot2 is the most comprehensive R package for data visualization. ggplot2 enables users to build a visualization from scratch and control nearly every aspect of the visuals produced. 

qplot: qplot is a condensed version of ggplot2 which allows users to quickly construct plots. While qplot is convenient, it is recommended that users learn ggplot2 before using qplot. 

 

You can also get help in the Library. Contact Rob Sippel, Geospatial & Numeric Data Librarian (rsippel@fit.edu) or Mike Dickinson, Data Librarian (mdickinson@fit.edu) for advice and assistance in using R for your project.

 

If you want some hands-on experience using R, there will be a Workshop -- "Introduction to R" -- held in the DSL on Thursday, September 13, 2018. Click this link for more details.

 

Here are a few helpful guides to visualizing data in R:

Python

Python is a free, open source programming language capable of building large-scale programming structures. Python is also a great tool for wrangling, analyzing, and visualizing data. Similar to R, Python requires some knowledge of programming semantics to be used successfully. There are many tools available on the web which can help users learn to use Python for data visualization. Below are a few of the main python libraries used to visualize data. 

matplotlib: The most widely used library for visualizing data in Python. Matplotlib is designed to resemble MATLAB. Since its creation, other libraries such as pandas and seaborn have been developed to extend it's capabilities. 

seaborn:  Built as an extension of matplotlib, seaborn was designed to make visually attractive charts with a few simple lines of code. Seaborn introduces additional color palettes and styles, allowing for greater control over aesthetic details. 

ggplot: Based on the ggplot2 package widely used to generate visualizations in R. Ggplot enables users to layer elements of a visualization to easily build complex charts. However, aesthetic details in ggplot are not as easily customized as other Python visualization libraries. 

bokeh: Similar to ggplot in that it allows users to layer elements of a visualization. Bokeh also enable users to create interactive visualizations and comes with three different levels of usability. The first level enables users to quickly generate graphics without defining the details. The middle level enables some control over the details while the third level requires users to define every detail in the plot for maximum control over the visualization. 

plotly: An online software for creating visualizations, Plotly can also be installed as a Python library. Plotly generates interactive charts that can reveal detailed information about a visualization which would be imperceptible without such functionalities. 

geoplotlib: A useful library that generates maps and plotting geographical data. Geoplotlib is an extensio nof the pyglet library, which must be installed before geoplotlib will work. 

You can also get help in the Library. Contact Rob Sippel, Geospatial & Numeric Data Librarian (rsippel@fit.edu) or Mike Dickinson, Data Librarian (mdickinson@fit.edu) for advice and assistance in using R for your project.

MatLab

MatLab is a tool that helps you analyze and visualize data. MatLab is especially appropriate for visualizing data that's a part of an equation, and is often used for data in the maths and engineering fields. MatLab is available in the Digital Scholarship Lab (DSL).

Tableau

Tableau is a versatile data analytics tool. Input your data into Tableau and it will help you create highly customizable options for visualization, including interactive displays. Tableau is available in the Digital Scholarship Lab (DSL).

 

Adobe Creative Suite

Adobe Creative Suite is the entire collection of Adobe desktop programs for creating and editing documents. From essentials like Photoshop to innovative new tools like Adobe XD (Beta). You can also access built-in templates to jump-start your designs and step-by-step tutorials to sharpen your skills and get up to speed quickly.

You can use Adobe to create and/or edit images that can later be turned into animations. Adobe Creative Suite is available on the 4 iMac stations in the Digital Scholarship Lab (DSL).

Adobe After Effects

Adobe After Effects is a user-friendly application that's a part of the Adobe Creative Suite. Adobe After Effects is used to create digital visual effects and animation. After you edit your images with Adobe Photoshop, use Adobe After Effects to animate them into something magical!

After Effects, and the rest of the Adobe Creative Suite, is installed on the 4 iMac stations in the Digital Scholarship Lab (DSL).

Blender

Blender is a free, open source software used to create 3D animations. You can model, create, and animate all with Blender. Some knowledge of 3D modeling is required. Blender is available in the Digital Scholarship Lab (DSL).

D3: Data Driven Documents

D3 is a software that allows you to create impressive graphic visualizations of data without a lot of heavy coding or proprietary framework. D3 is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS -- so, some knowledge of these languages is required. However, if you're a quick study, the D3 site has links to a lot of helpful guides and tutorials to get you started.