developing-meaningful-indicators

This repository collects my work in Developing Meaningful Indicators.

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Collection of All Work

Developing Meaningful Indicators (DMI) was a module in USP taught be Dr. Charles Burke. DMI allowed us understand, use, and visualise data in a way that prioritises creating an effect on others. This is in-line with the USP’s purpose to shape independent, adaptable thinkers and doers who will make an impact in the world.

This page serves as repository of all my work created during this module. Each set of visualisation are presented in chronological order, and iterations within each set can be observed as well.

Contents

  1. Big 5
  2. Suicides
  3. Movie Ratings
  4. Sentiment Analysis
  5. 30% Rule
  6. Comparing Machine Learning
  7. Human Rights
  8. Digital Inclusion
  9. Midterm Results
  10. Resale Flats
  11. Minimum Wage
  12. Women Ministers
  13. Avengers
  14. Shootings
  15. Duolingo
  16. Netflix Originals
  17. Reorganisation

Big 5

The Big 5 is a personality test that the class took. This set of visualisations attempt to graph the collective results.

big_5_1 big_5_2 big_5_3 big_5_4 big_5_5 big_5_6 big_5_7 big_5_8 big_5_9 big_5_10

Suicides

This set of charts analysed suicide rates.

suicides_1 suicides_2 suicides_3 suicides_4 suicides_5

Movie Ratings

Being a huge movie fan, I compared my own ratings of movies I had watched against IMDB and other movie statistics.

movies_1 movies_2 movies_3 movies_4 movies_5

Sentiment Analysis

This was done in collaboration with Ling Hui and does sentiment analysis on Reddit comments.

sentiment_analysis_1 sentiment_analysis_2

30% Rule

This two gifs were inspired by the rule that states that one should only spend 30% of their salary on rent.

30%_rule_1 30%_rule_2

Comparing Machine Learning

Comparing Amazon Web Service Comprehend and Microsoft Azure Sentiment Analysis, these two graphs were created based on tweets.

comparing_ml_1 comparing_ml_2 comparing_ml_3

Human Rights

This graph was created to compare human rights score in Singapore and Malaysia.

human_rights_1 human_rights_2

Digital Inclusion

Inspired by the Roland Berger study, this set of graphs describes how digitally inclusive Singapore is.

digital_inclusion_1 digital_inclusion_2

Midterm Results

Dr. Burke had released our midterm scores and the following set of visualisations attempt to describe that dataset.

midterm_1 midterm_2 midterm_3 midterm_4

Resale Flats

This was spawned from a conversation I had with my girlfriend about buying a house.

resale_1 resale_2 resale_3 resale_4 resale_5

Minimum Wage

This was conducted in collaboration with Erika, who shared a common interest in minimum wage.

minimmum_wage_1 minimmum_wage_2 minimmum_wage_3 minimmum_wage_4 minimmum_wage_5 minimmum_wage_6 minimmum_wage_7

Women Ministers

This set was conducted in collaboration with Rhea, who was interested in women in position of power.

women_ministers_1 women_ministers_2 women_ministers_3

Avengers

These two videos attempted to develop an indicator of how popular each Avenger was.

avengers_1 avengers_2

Shootings

This set of visualisations explored the use of sunburst and radial charts using a dataset about police shootings in the US, and done in collaboration with Ling Hui.

shootings_1 shootings_2 shootings_3 shootings_4 shootings_5 shootings_6 shootings_7 shootings_8 shootings_9 shootings_10

Duolingo

This set of charts referenced Duolingo statistics, with the emphasis on the use of chord diagrams.

duolingo_1 duolingo_2 duolingo_3 duolingo_4 duolingo_5 duolingo_6

Netflix Originals

This was done in collaboration with Valerie over our shared love in Netflix.

netflix_1

Reorganisation

This set of visualisations were done during the informal hackathon conducted during the last week of lessons, and co-created with my partner Kok Lee.

reorganisation_1 reorganisation_2 reorganisation_3 reorganisation_4 reorganisation_5 reorganisation_6 reorganisation_7 reorganisation_8