Introduction section

This is my first RMarkdown document!

Here are some bullets

library(dplyr, warn.conflicts=FALSE)
library(readr)
library(ggplot2)
library(knitr)
gm <- read_csv("data/gapminder.csv")
## Parsed with column specification:
## cols(
##   country = col_character(),
##   continent = col_character(),
##   year = col_integer(),
##   lifeExp = col_double(),
##   pop = col_integer(),
##   gdpPercap = col_double()
## )
head(gm)
## # A tibble: 6 x 6
##       country continent  year lifeExp      pop gdpPercap
##         <chr>     <chr> <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan      Asia  1952  28.801  8425333  779.4453
## 2 Afghanistan      Asia  1957  30.332  9240934  820.8530
## 3 Afghanistan      Asia  1962  31.997 10267083  853.1007
## 4 Afghanistan      Asia  1967  34.020 11537966  836.1971
## 5 Afghanistan      Asia  1972  36.088 13079460  739.9811
## 6 Afghanistan      Asia  1977  38.438 14880372  786.1134

Another minor heading

gm %>% 
  filter(year==1992) %>% 
  group_by(continent) %>% 
  summarize(meanlife=mean(lifeExp)) %>% 
  kable(caption="Mean life exp by cont for 1192")
Mean life exp by cont for 1192
continent meanlife
Africa 53.62958
Americas 69.56836
Asia 66.53721
Europe 74.44010
Oceania 76.94500

this is a minor heading

ggplot(gm, aes(gdpPercap, lifeExp)) + geom_point()

head(gm) %>% kable(caption="My table")
My table
country continent year lifeExp pop gdpPercap
Afghanistan Asia 1952 28.801 8425333 779.4453
Afghanistan Asia 1957 30.332 9240934 820.8530
Afghanistan Asia 1962 31.997 10267083 853.1007
Afghanistan Asia 1967 34.020 11537966 836.1971
Afghanistan Asia 1972 36.088 13079460 739.9811
Afghanistan Asia 1977 38.438 14880372 786.1134