Difference between revisions of "1718t1is428T8"

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The international exports and imports of services has played an increasingly important role in Singapore over the last decade, with 70% of the nation’s GDP comprising of service industries such as finance, insurance and wholesale retail trade, up from 64% 10 years ago.
 
The international exports and imports of services has played an increasingly important role in Singapore over the last decade, with 70% of the nation’s GDP comprising of service industries such as finance, insurance and wholesale retail trade, up from 64% 10 years ago.

Revision as of 17:39, 4 November 2017

DOTA.png



Introduction

Singaporecbd.jpg



The international exports and imports of services has played an increasingly important role in Singapore over the last decade, with 70% of the nation’s GDP comprising of service industries such as finance, insurance and wholesale retail trade, up from 64% 10 years ago.

As government bodies such as the Ministry of Trade and Industry (MTI ) and Innovation and Enterprise (IE) Singapore focus more on these industries in their development plans, there comes the need to continuously view the trends and components of our services exports. This will allow us to understand the growth trends of this critical aspect of Singapore’s economy, its individual components and the countries that contribute to it and finally to monitor the effects of existing initiatives from various government agencies.


Problem and Motivation

From the existing reports prepared by MTI, we’ve identified the following areas in which we plan our visualization to value-add:

1) Interactivity and Customisability - By allowing the reader to interact with the graph to filter periods to view as well as the level of detail. This will facilitate user-led investigation and exploration of the data without any data processing tools.

2) Professional and ready to use format – This will save stakeholders such as MTI and SPH time in the preparation of graphs, especially when graph formatting is necessary before release to the public.

Exhibit 5 Growth of services exports va.png

This will provide a one stop visualization for stakeholders in the services industry in Singapore, to quickly consume the aspects of this data that is relevant to them, in an aesthetically pleasing and intuitive manner.


Data Source

We are using the following two datasets from the Singapore Department of Statistics:

Exports Of Services By Major Trading Partner And Services Category, Annual Dataset

Imports Of Services By Major Trading Partner And Services Category, Annual Dataset

The dataset consists of the following columns:

  • match_id - INTEGER, unique match id
  • match_seq_num - INTEGER, match sequence number
  • radiant_win - STRING, boolean variable than indicates if radiant won or not in the match
  • start_time - INTEGER, start time of the match
  • duration - INTEGER, duration of the match
  • tower_status_radiant - INTEGER, remaining health of the towers of the radiant side
  • tower_status_dire - INTEGER, remaining health of the towers of the dire side
  • barracks_status_radiant - INTEGER, remaining health of the barracks of the radiant side
  • barracks_status_dire - INTEGER , remaining health of the towers of the direside
  • cluster - INTEGER,
  • first_blood_time - INTEGER, time when the first blood occured in the match
  • lobby_type - INTEGER, type of the looby of the match
  • human_players - INTEGER, number of human players in the match leagueid - INTEGER, league id
  • positive_votes - INTEGER, number of positive votes
  • negative_votes - INTEGER, number of negative votes
  • game_mode - INTEGER, game mode
  • engine - INTEGER, engine
  • picks_bans - STRING, picks and bans
  • parse_status - INTEGER, parse status
  • item - STRING, a complex JSON that also include all the columns mentioned but may need more processing since the more interesting data are found here (e.g. chats, teamfights, purchase logs, etc. )


Key Technical Challenges

The following are some of the key technical challenges that we may face throughout the course of the project:

Key Technical Challenges Plans to resolve these issues
Data Cleaning & Transformation
  • Understanding the data
  • Cleaning and Transforming the data together
Unfamiliarity in Javascript, especially D3 Libraries
  • Attending D3 Programming Workshop
  • Research on different types of charts
  • Independent Learning on D3 Libraries
  • Asking questions on sites like StackOverflow to seek help


Project Timeline

The timeline for this project until its completion is as follows:

T8 Timeline.png


Tools & Technologies

The tools and technologies we will be using for this project:

  • Data Cleaning
    • Excel
    • JMP
    • R
  • Data Visualization
    • D3.js


Comments

Please give us feedbacks! Thank you!