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RworkshopIV.Rmd
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---
title: "Hello, R!"
author: "Yue Hu's R Workshop Series III"
output:
ioslides_presentation:
self_contained: yes
incremental: yes
logo: image/logo.gif
slidy_presentation: null
transition: faster
widescreen: yes
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(message = FALSE, warning = FALSE)
```
## Tabling
There are over twenty packages for [table presentation](http://conjugateprior.org/2013/03/r-to-latex-packages-coverage/) in R. My favoriate three are `stargazer`, `xtable`, and `texreg`.
(Sorry, but all of them are for **Latex** output)
* `stargazer`: good for summary table and regular regression results
* `texreg`: when some results can't be presented by `stargazer`, try `texreg` (e.g., MLM results.)
* `xtable`: the most extensively compatible package, but need more settings to get a pretty output, most of which `stargazer` and `texreg` can automatically do for you.
## An example {.smaller .columns-2}
```{r message = F}
lm_ols <- lm(mpg ~ cyl + hp + wt, data = mtcars)
stargazer::stargazer(lm_ols, type = "text", align = T)
```
* For Word users, click [here](http://www.r-statistics.com/2010/05/exporting-r-output-to-ms-word-with-r2wd-an-example-session/).
## Print out directly in the website or the manuscript{.smaler}
```{r results='asis'}
stargazer::stargazer(lm_ols, type = "html", align = T)
```
# But...why tabulating the results if you can plot it?
## How do R plots look like
<div class="centered">
<img src="http://mkweb.bcgsc.ca/embo/img/hiveplot-02.png" height="450"/>
</div>
----
<div class="center">
<img src="http://spatial.ly/wp-content/uploads/2012/02/bike_ggplot-1024x676.png" height="600"/>
</div>
----
<div class="center">
<img src="http://i.imgur.com/ELEA9FP.gif" height="550"/>
</div>
## Too "fancy" for your research? Then...
* <div class="centered">
<img src="http://fsolt.org/blog/dotwhisker1.jpg" height="530"/>
</div>
----
<div class="centered">
<img 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" height="550" width = "500"/>
</div>
----
<div class="centered">
<img src="http://fsolt.org/blog/interplot1.png" height="450"/>
</div>
## Let's Start!
* Basic plots: `plot()`.
* Lattice plots: e.g., `ggplot()`.
* Interactive plots: `shiny()`. (save for later)
+ <div class="centered">
<img src="http://i.stack.imgur.com/qZObK.png" height="300"/>
</div>
## Basic plot
Pro:
* Embedded in R
* Good tool for <span style="color:purple">data exploration</span>.
* <span style="color:purple">Spatial</span> analysis and <span style="color:purple">3-D</span> plots.
Con:
* Not very pretty
* Not very flexible
## An example: create a histogram
```{r fig.align="center"}
hist(mtcars$mpg)
```
## Saving the plot{.build}
* Compatible format:`.jpg`, `.png`, `.wmf`, `.pdf`, `.bmp`, and `postscript`.
* Process:
1. call the graphic device
2. plot
3. close the device
```{r eval = F}
jpeg("histgraph.jpg")
hist
dev.off()
```
<span style="color:green">Tip</span>
<div class="notes">
Sometimes, RStudio may distort the graphic output. In this situation, try to <span style="color:purple">zoom</span> or use `windows()` function.
</div>
----
The device list:
| Function | Output to |
|----------------------------- |------------------ |
| pdf("mygraph.pdf") | pdf file |
| win.metafile("mygraph.wmf") | windows metafile |
| png("mygraph.png") | png file |
| jpeg("mygraph.jpg") | jpeg file |
| bmp("mygraph.bmp") | bmp file |
| postscript("mygraph.ps") | postscript file |
## `ggplot`: the most popular graphic engine in R {.build}
+ Built by Hadley Wickham based on Leland Wilkinson's *Grammar of Graphics*.
+ It breaks the plot into components as <span style="color:purple">scales</span> and <span style="color:purple">layers</span>---increase the flexibility.
+ To use `ggplot`, one needs to install the package `ggplot2` first.
```{r message=FALSE}
library(ggplot2)
```
## Histogram in `ggplot`
```{r fig.align="center", fig.height=2.7}
ggplot(mtcars, aes(x=mpg)) +
geom_histogram(aes(y=..density..), binwidth=2, colour="black")
```
## Decoration
```{r fig.align="center", fig.height=2.7}
ggplot(mtcars, aes(x=mpg)) +
geom_histogram(aes(y=..density..), binwidth=2, colour="black", fill="purple") +
geom_density(alpha=.2, fill="blue") + # Overlay with transparent density plot
theme_bw() + ggtitle("histogram with a Normal Curve") +
xlab("Miles Per Gallon") + ylab("Density")
```
## Break in Parts:{.smaller}
```{r eval=FALSE}
ggplot(data = mtcars, aes(x=mpg)) +
geom_histogram(aes(y=..density..), binwidth=2, colour="black", fill="purple") +
geom_density(alpha=.2, fill="blue") + # Overlay with transparent density plot
theme_bw() + ggtitle("histogram with a Normal Curve") +
xlab("Miles Per Gallon") + ylab("Density")
```
* `data`: The data that you want to visualise
* `aes`: Aesthetic mappings
describing how variables in the data are mapped to aesthetic attributes
+ horizontal position (`x`)
+ vertical position (`y`)
+ colour
+ size
* `geoms`: Geometric objects that represent what you actually see on
the plot
+ points
+ lines
+ polygons
+ bars
----
* `theme`, `ggtitle`, `xlab`, `ylab`: decorations.
* Other parts you may see in some developed template
+ `stats`: Statistics transformations
+ `scales`: relate the data to the aesthetic
+ `coord`: a coordinate system that describes how data coordinates are
mapped to the plane of the graphic.
+ `facet`: a faceting specification describes how to break up the data into sets.
## An advanced version:
```{r fig.height=3}
library(dplyr)
df_desc <- select(mtcars, am, carb, cyl, gear,vs) %>% # select the variables
tidyr::gather(var, value) # reshape the wide data to long data
ggplot(data = df_desc, aes(x = as.factor(value))) + geom_bar() +
facet_wrap(~ var, scales = "free", ncol = 5) + xlab("")
```
## Save `ggplot`
* `ggsave(<plot project>, "<name + type>")`:
+ When the `<plot project>` is omitted, R will save the last presented plot.
+ There are additional arguments which users can use to adjust the size, path, scale, etc.
## Plotting with packages: `dotwhisker`{.smaller}
Plot the comparable coefficients or other estimates (margins, predicted probabilities, etc.).
```{r message=FALSE}
library(dotwhisker)
library(broom)
m1 <- lm(mpg ~ wt + cyl + disp + gear, data = mtcars)
```
----
```{r}
summary(m1)
```
----
```{r}
dwplot(m1)
```
----
```{r message=F, fig.align="center", fig.height=4}
m2 <- update(m1, . ~ . + hp) # add another predictor
m3 <- update(m2, . ~ . + am) # and another
dwplot(list(m1, m2, m3))
```
----
```{r eval = F}
dwplot(list(m1, m2, m3)) +
relabel_y_axis(c("Weight", "Cylinders", "Displacement",
"Gears", "Horsepower", "Manual")) +
theme_bw() + xlab("Coefficient Estimate") + ylab("") +
geom_vline(xintercept = 0, colour = "grey60", linetype = 2) +
ggtitle("Predicting Gas Mileage") +
theme(plot.title = element_text(face="bold"),
legend.justification=c(0, 0), legend.position=c(0, 0),
legend.background = element_rect(colour="grey80"),
legend.title = element_blank())
```
----
```{r echo = F}
dwplot(list(m1, m2, m3)) +
relabel_y_axis(c("Weight", "Cylinders", "Displacement",
"Gears", "Horsepower", "Manual")) +
theme_bw() + xlab("Coefficient Estimate") + ylab("") +
geom_vline(xintercept = 0, colour = "grey60", linetype = 2) +
ggtitle("Predicting Gas Mileage") +
theme(plot.title = element_text(face="bold"),
legend.justification=c(0, 0), legend.position=c(0, 0),
legend.background = element_rect(colour="grey80"),
legend.title = element_blank())
```
## Plotting with packages: `interplot`{.smaller}
```{r message=FALSE}
library(interplot)
lm_in <- lm(mpg ~ cyl + hp * wt, data = mtcars)
```
----
```{r}
summary(lm_in)
```
----
```{r fig.align="center"}
interplot(m = lm_in, var1 = "hp", var2 = "wt", hist = TRUE) +
xlab("Automobile Weight (thousands lbs)") +
ylab("Estimated Coefficient for \nGross horsepower")
```
## Wrap Up
* R has a bunch of packages for creating publishing-like tables, e.g., `stargazer`, `xtable`, and `texreg`
* There are three ways to visualize statistics in R: basic, lattice (`ggplot`), and interactive.
+ basic: e.g., `hist(<vector>)`
+ `ggplot`: /n e.g., `ggplot(<data>, aes(x=<vector>)) + geom_histogram()`.
* Two special types of plot:
+ Estimate plot with [`dotwhisker`](https://cran.r-project.org/web/packages/interplot/vignettes/interplot-vignette.html).
+ Interaction plot with [`interplot`](https://cran.r-project.org/web/packages/dotwhisker/vignettes/dwplot-vignette.html).
## Almost the end: one topic left
<div class="centered">
[]
</div>
# Version Control
## Just a brief introduction{.columns-2 .build}
<div class = "center">
<img src= "http://www.foldertrack.com/images/Personal_Version_Mess.png" width = "400" height = "400" />
</div>
* Tried to recall the deleted codes?
* Tried to figure out what changes?
* Saved a lot of replication files?
* Version control can help you.
----
<div class = "center">
<img src="http://cdn.arstechnica.net//wp-content/uploads/2012/05/uncommitted-changes-1.png" />
</div>
## Using Git with RStudio
* RStudio has associate with the Git and SVN very well.
* Process to use git:
+ Get a user account in https://github.com.
+ Connect your account with RStudio following [this instruction](http://www.molecularecologist.com/2013/11/using-github-with-r-and-rstudio/).
+ Create a version-control project in RStudio
+ <img src="http://i0.wp.com/geraldbelton.com/wp-content/uploads/2017/01/new-project.jpg" height = "200" />
+ Commit, Pull and Push
## External Sources
* Q&A Blogs:
+ http://stackoverflow.com/questions/tagged/r
+ https://stat.ethz.ch/mailman/listinfo/r-help
* Blog for new stuffs: http://www.r-bloggers.com/
* Graph Blogs:
+ http://www.cookbook-r.com/Graphs/
+ http://shiny.stat.ubc.ca/r-graph-catalog/
* Workshops: http://ppc.uiowa.edu/node/3608
* Consulting service: http://ppc.uiowa.edu/isrc/methods-consulting
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