GDP vs other key indicators analysis

Amit Sahoo
Posted on Feb 4, 2017

Contributed by Amit Sahoo. He is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between January 7th to April 1st, 2017. This post is based on his 1st class project - Exploratory Data Analysis and Visualization with Shiny (due on the 4th week of the program).


Coming from a analytics background i wanted to challenge myself to see how can i visually represent something by more than 2 dimension. So I was inspired by Hans Rosling TED talk where he provides stats based on some cool visualizations.  So I started on a quest to come up with some visualization similar to his with the knowledge i had gained so far using R and Shiny. Then came the process of data gathering and data cleaning.

Getting the Data

I wanted to have a data set which has all the data for almost all the countries for last 15 years to be able to able to provide some meaningful visualization and to be able to figure out some correlation among the data. So i gathered some data from world bank like GDP, Population, Employment Ratio, CO2 emission. Since i had CO2 emission data was curious to see how the world temperature has changed over last 15 years. So was able obtain earth surface temperature data from Kaggle.

SHINY APP walkthrough

The app contains 4 sections as below in the screenshot

Screen Shot 2017-02-06 at 9.07.24 AM


Gives a brief intro to how to navigate through the app.

Correlation By Region:

This will give you a correlation plot  at the Region level and lets you choose a Region what interest you and its a multi-select field which lets you choose multiple regions. You can select the type of icon you want for your corrplot.

Correlation By Country:

This will give you a correlation plot  at the Country level and lets you choose a Country what interest you and its a multi-select field which lets you choose multiple Country. You can select the type of icon you want for your corrplot.

Time Series Dashboard :

This give you a plot and you can choose the X and Y variable. The bubble in the graph is set to "Population" by default but can be changed. The bar below lets you control the year you what interests you or you can press the arrow button to Autoplay.


SHINY Code walkthrough

The below code was defined for ui.R

server.R code as below

All the data processing steps like cleansing and merging files were done in the global.R as below

Next Steps

With additional time it would be interesting to make use of other key indicators to be included in the above dataset.

The link to the app can be found here.

About Author

Amit Sahoo

Amit Sahoo

Amit has 12 years of experience working with data, designing and implementing mission critical enterprise data solution for Retail, Healthcare, Finance and Pharmaceutical. Most recent experience involves implementing end to end data solution for Oakley from ground up....
View all posts by Amit Sahoo >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp