Our Required Library

library(ggplot2)
#install.packages("gapminder")
library(gapminder)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
library(gapminder)

We will try to visulize some graphical represantation variable in Gapminder Dataset. Now, We will see the first 6 row to generate some pre-knowledge about gapminder datatset.

head(gapminder)
## # A tibble: 6 x 6
##   country     continent  year lifeExp      pop gdpPercap
##   <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan Asia       1952    28.8  8425333      779.
## 2 Afghanistan Asia       1957    30.3  9240934      821.
## 3 Afghanistan Asia       1962    32.0 10267083      853.
## 4 Afghanistan Asia       1967    34.0 11537966      836.
## 5 Afghanistan Asia       1972    36.1 13079460      740.
## 6 Afghanistan Asia       1977    38.4 14880372      786.

Continent wise scatterplot between lifeExptation and Population

Con_exp<-gapminder %>%
  ggplot(aes(pop,lifeExp,col=continent))+geom_point()
ggplotly(Con_exp)

Continent wise scatterplot between lifeExptation and Population

Country_exp<-gapminder %>%
  ggplot(aes(pop,lifeExp,col=country))+geom_point()+labs(title = "lifeExptation vs Population")
ggplotly(Country_exp)

Year wise scatterplot between lifeExptation and Population

year_exp<-gapminder %>%
  ggplot(aes(pop,lifeExp,col=country))+geom_point()+labs(title = "lifeExptation vs Population")+facet_wrap(~year)
ggplotly(year_exp)

COntinent-wise scatterplot between Year and LifeExpectancy

year_exp<-gapminder %>%
  ggplot(aes(year,lifeExp,col=country))+geom_point()+labs(title = "lifeExptation vs Population")+facet_wrap(~continent)
ggplotly(year_exp)