Urban Population Growth Project Presentation

This presentation is being used used as a part of my analysis of World Bank's Climate Change Data. The analysis is a rather simple one. It allows the user to use sliders to filter the data. The app can be found here:

https://ricej2.shinyapps.io/UrbanGrowth/

The app has a tabular panel which has 2 sub panels. The first sub panel is simply the data as a table. The second panel shows the summary of the Urban Growth according to the current filters.

There are 6 slider bars which can be used to filter the data:
1. Access to electricity (% of population)
2. Agricultural land (% of land area)
3. Forest area (% of land area)
4. Population growth (annual %)
5. Urban population (% of total)
6. Urban population growth (annual %)

There is also a checkbox which can be used to select positive or negative growth.

Here is a sample of what the data looks like:

growthData <- read.csv("../ClimateIndicators.csv")
str(growthData[,2:9])

'data.frame':   238 obs. of  8 variables:
 $ Country.Name                           : Factor w/ 238 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ Access.to.electricity....of.population.: num  41 100 99.3 55.8 100 ...
 $ Agricultural.land....of.land.area.     : num  58.1 43.8 17.4 24.5 42.8 ...
 $ Forest.area....of.land.area.           : num  2.068 28.321 0.805 90 34.043 ...
 $ Population.growth..annual...           : num  2.737 -0.496 1.776 -1.055 -1.242 ...
 $ Urban.population....of.total.          : num  24.7 52.2 67.5 87.6 87.8 ...
 $ Urban.population.growth..annual...     : num  4.27 1.61 2.82 -1.17 -1.85 ...
 $ Urban.Growth                           : logi  TRUE TRUE TRUE FALSE FALSE TRUE ...

Here we can see that the data is pretty skewed.

table(growthData[,9])

FALSE  TRUE 
   27   211