CS 725 Information Visualization - VI2

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CS 725 Information Visualization - VI2

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Last edited Feb 3, 2016

Created on Feb 1, 2016

This example demonstrates a bar chart for a dataset of 20 numeric values, with each bar’s height and color intensity proportional to its value. The chart is rendered as an SVG using D3.js (version 3.5.5), where `d3.select` appends an SVG element, and `selectAll("rect")` with `data()` and `enter()` creates the bars. Text labels are positioned at each bar’s top using an inverted coordinate system, where `y` is calculated from the height. The source code is a standalone HTML file, and the dataset is hardcoded as an array. The rendering uses basic D3 APIs such as `attr` for styling and `text-anchor` for label alignment.

AI-generated description

Christos Tsolakis

Tableau Charts:
- The PAC conference has the most players in the top ten and CUSA & American conference, although on the top of the list of the players, they have only 1 in the top ten.
- Most of the Rushing Attempts are rewarding by a small amount of yards. However, there is a considerable amount of backtracks.
- Oregon has the best ratio, although in average, teams in the SEC conference have better results.
List of 3 things that you learned while working through the D3 tutorial
- Using the class rect instead of simple div's for the barchart made things quite easier.
  - The coordinate system in an svg file is inverted with respect on what you expect to see.
- Configuring text position is by far more flexible than in Tableau.
List of 2 comments that you have about using Tableau
- Creating the 1st bar chart was by far easier in Tableau than it was in R.
- Tableau gives you a rapid way of visualizing and exploring your data but on the other hand if you want to customize your plot you better redo it in D3.

forked from <a href='http://bl.ocks.org/ChristosT/'>ChristosT</a>'s block: <a href='http://bl.ocks.org/ChristosT/2f93011f91b398b936be'> CS 725 Information Visualization - VI1</a>

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