hadley

.Rproj.user
.Rhistory
.RData
*.Rproj
*.html

CarlRevell

{= {NUMPAGES} - {PAGE} + 1}

StevenMMortimer

Automate Chunks of Analysis in R Markdown 
========================================================
 
```{r setup, echo=FALSE}
library(knitr)
library(DT)
```
 
```{r create-datasets, echo=FALSE}
 

rafapereirabr

This gist shows in two steps how to tilt and stack maps using ggplot2 in order to create an image like this one: [![enter image description here][1]][1]

Let's load the necessary libraries and data to use a reproducible example:

# load libraries
  library(rgeos)
  library(UScensus2000tract)
  library(ggplot2)

revodavid

---
title: "Outliers are a matter of opinion?"
author: "Antony Unwin"
date: ' '
output: html_document
---
```{r include=FALSE}
library(ggplot2)
library(ggthemes)
library(OutliersO3)

thomasp85

---
title: "PDF Animation Test"
output: pdf_document
header-includes:
   - \usepackage{animate}
---

`gganimate` now supports animations inside PDF documents. This feature is only 
viewable with Acrobat Reader, however. Remember to include 
`\usepackage{animate}` in the preamble and set `fig.show='animate'` in the chunk

batpigandme

library(tidyverse, warn.conflicts = FALSE)

# data frame
mtcars

# as tibble
as.tibble(mtcars)

# rownames_to_column()
rownames_to_column(mtcars)

andrewheiss

library(tidyverse)
library(Deriv)
library(scales)

# Formula for polynomial curve: 60x^4 + 5x + 6
#
# I invented this by using WolframAlpha to fit a polynomial linear model that
# when through a set of specific points using this command (with a maximum
# exponent of 4):

alexpghayes

library(tidyverse)

df <- mtcars %>% 
  mutate(
    # here 20, 25 are the cut points
    region = cut(mpg, c(min(mpg), 20, 25, max(mpg)))
  )

ols <- lm(hp ~ region * mpg, df)
summary(ols)

andrewheiss

#!/usr/bin/env bash

cat << EOF > ./$1.Rproj
Version: 1.0

RestoreWorkspace: No
SaveWorkspace: No
AlwaysSaveHistory: Default

EnableCodeIndexing: Yes