Swiss Fertility and Socioeconomic Indicators Data (1888) Exploration

Introduction

This is the reproducible pitch presentation for the final course porject of Coursera Data Science Specialization Course 9: Developing Data Science Tools. This document will go over the basics of developing the Shiny app. For more information, please see the following links:

1. The Swiss Fertility and Socioeconomic Indicators Data (swiss data) can be accessed with data(swiss) in R
2. The GitHub repository containing the R codes required to build the Shiny App (server.R and ui.R)can be accessed here
3. The Shiny app can be accessed here, which contains

• Exploring the distribution of each variable in a histogram
• Exploring the relationship of up to three variables in a scatter plot

The Swiss Data

• Except for fertility, all variables are expressed in the proportions (%) of the population
• Use ?swiss to read more about the study

data(swiss)
summary(swiss)

##    Fertility      Agriculture     Examination      Education    
##  Min.   :35.00   Min.   : 1.20   Min.   : 3.00   Min.   : 1.00  
##  1st Qu.:64.70   1st Qu.:35.90   1st Qu.:12.00   1st Qu.: 6.00  
##  Median :70.40   Median :54.10   Median :16.00   Median : 8.00  
##  Mean   :70.14   Mean   :50.66   Mean   :16.49   Mean   :10.98  
##  3rd Qu.:78.45   3rd Qu.:67.65   3rd Qu.:22.00   3rd Qu.:12.00  
##  Max.   :92.50   Max.   :89.70   Max.   :37.00   Max.   :53.00  
##     Catholic       Infant.Mortality
##  Min.   :  2.150   Min.   :10.80   
##  1st Qu.:  5.195   1st Qu.:18.15   
##  Median : 15.140   Median :20.00   
##  Mean   : 41.144   Mean   :19.94   
##  3rd Qu.: 93.125   3rd Qu.:21.70   
##  Max.   :100.000   Max.   :26.60

Codes for Histogram

inputVar <- 'Fertility'; inputBin <- 10; histVal <- swiss[, inputVar]
hist(histVal, breaks = seq(min(histVal), max(histVal), length.out = inputBin+1),
     xlab = inputVar, main = paste('Distribution of', inputVar),
     col = 'darkgray', border = 'white')

Codes for Scatter Plot

library(ggplot2)
scatX <- 'Fertility'; scatY <- 'Education'; scatC <- 'Examination'
ggplot(data = swiss, aes(x = Fertility, y = Education, color = Examination)) + 
      geom_point() + xlab(scatX) + ylab(scatY) + labs(colour = scatC) +
      ggtitle(paste('Scatter plot of', scatX, 'vs', scatY)) +
      theme(plot.title = element_text(hjust = 0.5))