R Notebook

Presentation Overview

Floods are one of the most costly natural disasters. As our planet goes through changes to its climate due to excess carbon emissions by human activity, scientists believe floods will become more common and more costly. Poor, coastal regions are at the greatest risk of floods due to the projected sea-level rise climate change will bring. The following dataset includes data on flood damage in India, a country at great risk from rising sea levels.

Data Examined

The dataset has yearly records of flood damage in India from 1953 to 2017.
This dataset is huge, so I focused on five variables to examine. There are:
-Land affected
-People affected
-Crop damage
-Damage to Houses
-Death toll

Summary of Data- Land

Summary of area of land affected by flood damage in millions of hectares.

summary(india$Area.affected.in.m.ha....India)

plot(india[,2],type="l",lwd=1,xlab="year from 1952",ylab="land area affected in mill of ha.",main="area of land affected")

Summary of Data- People

Summary of people affected by flood damage in millions.

summary(india$Population.affected.in.million...India)

plot(india[,3],type="l",lwd=1,xlab="year from 1952",ylab="people affected in millions",main="people affected")

Summary of Data- Crops

Summary of crop damage affected by flood damage in millions of hectares.

summary(india$Damage.to.Crops...Area.in.m..ha....India) 

plot(india[,4],type="l",lwd=1,xlab="year from 1952",ylab="damage to crops in millions of hectares",main="area of crop damage")

Summary of Data- Houses

Summary of damage to houses in india in crore of rupees. 1 crore of rupees is equivalent to $140,000 USD.

summary(india$Damage.to.Houses...Value.in.Rs.Crore...India)

plot(india[,7],type="l",lwd=1,xlab="year from 1952",ylab="damage to houses",main="damage to houses")

Summary of Data- Deaths

Summary of damage to number of human lives lost.

summary(india$Human.live.Lost.Nos....India)

plot(india[,9],type="l",lwd=1,xlab="year from 1952",ylab="human lives lost",main="deaths")