Capstone Project - Data Visualization Specialization

1 Algoritma

Algoritma is a data science education center based in Jakarta. We organize workshops and training programs to help working professionals and students gain mastery in various data science sub-fields: data visualization, machine learning, data modeling, statistical inference etc. Visit our website for all upcoming workshops.

2 Libraries and Setup

We’ll set-up caching for this notebook given how computationally expensive some of the code we will write can get.

options(width=50)
knitr::opts_chunk$set(cache=TRUE,tidy=TRUE)
options(scipen = 9999)
rm(list=ls())

You will need to use install.packages() to install any packages that are not already downloaded onto your machine. You then load the package into your workspace using the library() function:

library(dplyr)
library(ggplot2)
library(plotly)
library(reshape2)

3 Data Visualization Capstone Project

After having learned and explored appropriate techniques on visualizing data, students are required to deploy an interactive dashboard web application using a shiny server which contain any plotting objects such as ggplot and/or leaflet that display useful insights.

In addition, students are given the freedom to use their own dataset or past datasets from previous classes. Below are the rubrics for assessment and grading:

• Input (reactivity) : 6 points
• Tab (paging) : 6 points
• Render plot (ggplot/leaflet) : 6 points
• Deploy : 6 points
• UI Appearence : 6 points
• Total : 30 points

3.1 References

1. Advisory

library(shiny)
# https://github.com/onlyphantom/advisory
runGitHub("advisory", "onlyphantom", subdir = "advisory")

2. Shiny Dashboard

https://rstudio.github.io/shinydashboard/

3. Shiny Rstudio

https://shiny.rstudio.com/gallery

4. Flex-dashboard

https://rmarkdown.rstudio.com/flexdashboard

3.2 Data Source

Some data source reference:

• Kaggle http://kaggle.com
• Data.gov http://data.gov The US Government pledged last year to make all government data available freely online.
• US Census Bureau http://www.census.gov/data.html A wealth of information on the lives of US citizens covering population data, geographic data and education.
• European Union Open Data Portal http://open-data.europa.eu/en/data/ As the above, but based on data from European Union institutions.
• Data.gov.uk http://data.gov.uk/ Data from the UK Government, including the British National Bibliography – metadata on all UK books and publications since 1950.
• UCI Machine Learning Repository [http://archive.ics.uci.edu/ml/index.php] is a dataset specifically pre-processed for machine learning.
• Indonesia version Government : http://data.go.id
• Jakarta open data http://data.jakarta.go.id/
• Badan Pusat Statistik : https://www.bps.go.id/

3.3 Tips

• Set your size.

By default, Shiny limits file uploads to 5MB per file. You can modify this limit by using the shiny.maxRequestSize option. For example, adding this to the top of app.R would increase the limit to 200MB.

options(shiny.maxRequestSize=200*1024^2)

• Use RDS for save your files.

saveRDS()

readRDS()