ISSS608 2016 17T3 Group11 Proposal
Performance Decomposition of China Listed Firms
|
|
|
|
|
Situation
Since initiating market reforms in 1978, China has shifted from a centrally-planned to a market-based economy and has experienced rapid economic and social development. With a population of 1.3 billion, China is the second largest economy and is increasingly playing an important and influential role in development and in the global economy. China has been the largest contributor to world growth since the global financial crisis of 2008. An increasing number of foreign investors are looking for opportunities to invest in China. Therefore, understanding the performance of China listed firms becomes very essential. This project identifies the need of developing an interactive dashboard to display the performance of China listed firms, which will be very helpful in understanding how these companies of different industries have developed over the past 12 years.
Objectives
- Currently there are quite a few statistic webs of both governments and organizations that provide data about the performance of listed companies. Yet, these data is still in table formats and the visualizations are quite basic, which stops the readers from getting any useful insights and findings. This application aims to build such an visualization that explains the data in a meaning method;
- Although off-the-shelf software , such as Tableau, provides the option of designing tree map, there are limitations to their design, such as it does not provide any interactivities among layers;
- This application framework can be easily reproduced for various statistics websites of governments and organizations;
Data Source
http://csmar.gtadata.com.libproxy.smu.edu.sg/p/sq/
Techniques to Apply:
- R Package: Shiny, ggplot2, DT, Geo_Facet, Tibble, d3Tree, d3treeR, tidyverse, sparkline, dplyr, reshape2, shinydashboard, ggthemes
- Combining data tables and sparklines
Challenges
- Data Restructure - raw data are far away from qualified to use for the application
- How to link different kinds/levels of data visualizations properly so as to give audiences a better view and understanding
