--- output: html_document: default word_document: default pdf_document: default --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) library(tidyverse) ``` # I am a large section ## I am a smaller section ## Let's make a table ```{r} df = data.frame(y = rnorm(1000), x = sample(letters, size = 1000, replace = TRUE), stringsAsFactors = FALSE) df$y[ sample(1:1000, size = 20)] = NA summ = df %>% group_by(x) %>% summarize(mean = mean(y, na.rm = TRUE), sd = sd(y, na.rm = TRUE), not_missing = sum(!is.na(y)), n =n()) summ = summ %>% filter(x %in% letters[1:5]) ``` ```{r} library(knitr) library(kableExtra) summ$z = "Hey I am a very long string and I want to be wrapped" knitr::kable(summ, digits = 2) ``` ```{r} library(plotly) url = "http://johnmuschelli.com/intro_to_r/data/kaggleCarAuction.csv" ## best answer - quick and simple cars = read_csv( url, col_types = cols( VehBCost = col_double() )) g = ggplot(cars, aes(x = VehYear, y = VehBCost, colour = Make)) + geom_boxplot() + guides(colour = FALSE) print(g) ``` ## Let's use plotly to get an interactive graph ```{r} ggplotly(g) ``` ```{r} ss = summ %>% as.data.frame library(pander) pander(ss, round = 2) ``` ```{r} library(DT) datatable(summ) %>% formatRound(columns = c("mean", "sd")) ``` Look at http://rmarkdown.rstudio.com/lesson-7.html and the Rmd: http://rmarkdown.rstudio.com/demos/6-tables.Rmd