library(rmarkdown)
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(ggplot2)

summarize to find the median life expectancy

gapminder%>%
  summarise(medianLifeExp=median(lifeExp))
## # A tibble: 1 × 1
##   medianLifeExp
##           <dbl>
## 1          60.7

filter for 1957 then summarize the median life expectancy

gapminder%>%
  filter(year==1957)%>%
  summarize(medianLifeExp=median(lifeExp))
## # A tibble: 1 × 1
##   medianLifeExp
##           <dbl>
## 1          48.4

filter for 1957 then summarize the median life expectancy and the maximum GDP per capita

gapminder%>%
  filter(year==1957)%>%
  summarize(medianLifeExp=median(lifeExp),
            maxGdpPercap=max(gdpPercap))
## # A tibble: 1 × 2
##   medianLifeExp maxGdpPercap
##           <dbl>        <dbl>
## 1          48.4      113523.

find median life expectancy and maximum GDP per capita in each year

gapminder%>%
  group_by(year)%>%
  summarize(medianLifeExp=median(lifeExp),
            maxGdpPercap=max(gdpPercap))
## # A tibble: 12 × 3
##     year medianLifeExp maxGdpPercap
##    <int>         <dbl>        <dbl>
##  1  1952          45.1      108382.
##  2  1957          48.4      113523.
##  3  1962          50.9       95458.
##  4  1967          53.8       80895.
##  5  1972          56.5      109348.
##  6  1977          59.7       59265.
##  7  1982          62.4       33693.
##  8  1987          65.8       31541.
##  9  1992          67.7       34933.
## 10  1997          69.4       41283.
## 11  2002          70.8       44684.
## 12  2007          71.9       49357.

find median life expectancy and maximum GDP per capita in each continent in 1957

gapminder%>%
  group_by(continent)%>%
  summarize(medianLifeExp=median(lifeExp),
            maxGdpPercap=max(gdpPercap))
## # A tibble: 5 × 3
##   continent medianLifeExp maxGdpPercap
##   <fct>             <dbl>        <dbl>
## 1 Africa             47.8       21951.
## 2 Americas           67.0       42952.
## 3 Asia               61.8      113523.
## 4 Europe             72.2       49357.
## 5 Oceania            73.7       34435.

find median life expectancy and maximum GDP per capita in each continent/year combination

gapminder%>%
  group_by(continent,year)%>%
  summarize(medianLifeExp=median(lifeExp),
            maxGdpPercap=max(gdpPercap))
## `summarise()` has grouped output by 'continent'. You can override using the
## `.groups` argument.
## # A tibble: 60 × 4
## # Groups:   continent [5]
##    continent  year medianLifeExp maxGdpPercap
##    <fct>     <int>         <dbl>        <dbl>
##  1 Africa     1952          38.8        4725.
##  2 Africa     1957          40.6        5487.
##  3 Africa     1962          42.6        6757.
##  4 Africa     1967          44.7       18773.
##  5 Africa     1972          47.0       21011.
##  6 Africa     1977          49.3       21951.
##  7 Africa     1982          50.8       17364.
##  8 Africa     1987          51.6       11864.
##  9 Africa     1992          52.4       13522.
## 10 Africa     1997          52.8       14723.
## # ℹ 50 more rows
by_year<-gapminder%>%
  group_by(year)%>%
  summarize(medianLifeExp=median(lifeExp),
            maxGdpPercap=max(gdpPercap))

create a scatter plot showing the change in medianLifeExp over time

ggplot(by_year,aes(x=year,y=medianLifeExp))+
  geom_point()+
  expand_limits(y=0)

summarise medianGdpPercap within each continent within each year: by_year_continent

by_year_continent<-gapminder%>%
  group_by(continent,year)%>%
  summarize(medianGdpPercap=median(gdpPercap))
## `summarise()` has grouped output by 'continent'. You can override using the
## `.groups` argument.

plot the change in medianGdpPercap in each continent over time

ggplot(by_year_continent,aes(x=year,y=medianGdpPercap,color=continent))+
  geom_point()+
  expand_limits(y=0)

summarise the median GDP and median life expectancy per continent in 2007

by_continent_2007<-gapminder %>%
  filter(year==2007) %>%
  group_by(continent) %>%
  summarize(medianGdpPercap=median(gdpPercap),
            medianLifeExp=median(lifeExp))
ggplot(by_continent_2007,aes(x=medianGdpPercap,y=medianLifeExp,color=continent))+
         geom_point()