Difference between revisions of "ISSS608 2016 17T3 Group6 Report"
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=Design framework= | =Design framework= | ||
| + | {| class="wikitable" | ||
| + | |- | ||
| + | |<center><b>Visualization</b></center> | ||
| + | |<center><b>Description</b></center> | ||
| + | |- | ||
| + | |[[Image:.JPG|500px]]<br/> | ||
| + | <center>Map</center> | ||
| + | | | ||
| + | World map with the package highchart shows users an intuitive distribution of happiness score across country. With yellow-blue gradient, scores from high to low can be recognized and compared straightforward.|- | ||
| + | | | ||
| + | |- | ||
| + | |[[Image:.JPG|500px]]<br/> | ||
| + | <center>Histogram </center> | ||
| + | | | ||
| + | Histogram, an accurate graphical representation of the distribution of numerical data, is used to show the distribution of world happiness scores. With the histogram, users are able to understand how the happiness score of distributed, the mean and median of the overall world happiness score from 2015 to 2017. | ||
| + | | | ||
| + | |- | ||
| + | |[[Image:.jpg|500px]]<br/> | ||
| + | <center>Tableplot </center> | ||
| + | | | ||
| + | A tableplot is used to explore the relationships between the variables for high-dimensional data. In this project, it allows users to discover countries’ happiness ranking changes patterns from 2015 to 2017 on a world or region scale. The data set is sorted according to happiness rank in 2015, each row representing corresponding country’s rankings of these three years. Outperformed countries can be observed from the tableplot obviously. Concave indicates the country ranks up in 2016 or 2017, compared with 2015, while convex means its rank dropped. | ||
| + | |- | ||
| + | |[[Image:.JPG|500px]]<br/> | ||
| + | <center>Regression Analysis</center> | ||
| + | | | ||
| + | Regression analysis applies linear regression to model the relationship between the dependent variable (Happiness Score) and each independent variables (Economy, Family, Health, Freedom, Trust, and Generosity). It is able for users to understand which independent variable will influence the happiness score the most through the regression analysis. Moreover, users are able to easily find out outliers for each independent variable and determine whether those countries are outperformed or fallen behind. | ||
| + | | | ||
| + | |- | ||
| + | |[[Image:.JPG|500px]]<br/> | ||
| + | <center>Heatmap </center> | ||
| + | | | ||
| + | Heatmap is a graphical representation of data where the individual values contained in a matrix are represented as colors. From the heatmap, users are able to understand which countries are more keen on Economy, which countries are more interested in Freedom, and so on. Countries are grouped into clusters based on their interests of each independent variable. | ||
| + | In this project, Shiny heatmap, an advanced user-friendly heatmap is used to allow users to customize the heatmap as desired. | ||
| + | | | ||
| + | |} | ||
=Demonstration= | =Demonstration= | ||
Revision as of 18:15, 4 August 2017
ISSS608 Project - Group 6
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Contents
Motivation of the application
Review and critic on past works
Design framework
| 500px |
World map with the package highchart shows users an intuitive distribution of happiness score across country. With yellow-blue gradient, scores from high to low can be recognized and compared straightforward.|- |
|
| 500px |
Histogram, an accurate graphical representation of the distribution of numerical data, is used to show the distribution of world happiness scores. With the histogram, users are able to understand how the happiness score of distributed, the mean and median of the overall world happiness score from 2015 to 2017. |
|
| 500px |
A tableplot is used to explore the relationships between the variables for high-dimensional data. In this project, it allows users to discover countries’ happiness ranking changes patterns from 2015 to 2017 on a world or region scale. The data set is sorted according to happiness rank in 2015, each row representing corresponding country’s rankings of these three years. Outperformed countries can be observed from the tableplot obviously. Concave indicates the country ranks up in 2016 or 2017, compared with 2015, while convex means its rank dropped. | |
| 500px |
Regression analysis applies linear regression to model the relationship between the dependent variable (Happiness Score) and each independent variables (Economy, Family, Health, Freedom, Trust, and Generosity). It is able for users to understand which independent variable will influence the happiness score the most through the regression analysis. Moreover, users are able to easily find out outliers for each independent variable and determine whether those countries are outperformed or fallen behind. |
|
| 500px |
Heatmap is a graphical representation of data where the individual values contained in a matrix are represented as colors. From the heatmap, users are able to understand which countries are more keen on Economy, which countries are more interested in Freedom, and so on. Countries are grouped into clusters based on their interests of each independent variable. In this project, Shiny heatmap, an advanced user-friendly heatmap is used to allow users to customize the heatmap as desired. |
