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---
title: "Graphical Summaries"
output:
html_document:
toc: true
toc_float: true
---
```{r, include=FALSE}
library(tidyverse)
library(plotly)
library(mosaic)
```
<script type="text/javascript">
function showhide(id) {
var e = document.getElementById(id);
e.style.display = (e.style.display == 'block') ? 'none' : 'block';
}
function openTab(evt, tabName) {
var i, tabcontent, tablinks;
tabcontent = document.getElementsByClassName("tabcontent");
for (i = 0; i < tabcontent.length; i++) {
tabcontent[i].style.display = "none";
}
tablinks = document.getElementsByClassName("tablinks");
for (i = 0; i < tablinks.length; i++) {
tablinks[i].className = tablinks[i].className.replace(" active", "");
}
document.getElementById(tabName).style.display = "block";
evt.currentTarget.className += " active";
}
</script>
----
There are many ways to display data. The fundamental idea is that the graphical depiction of data should communicate the truth the data has to offer about the situation of interest.
----
### Histograms {.tabset .tabset-fade .tabset-pills}
<div style="float:left;width:125px;">
```{r, fig.height=1, fig.width=1, echo=FALSE}
par(mai=c(0,0,0,0))
hist(cars$dist, main="", col='lightgray')
```
</div>
**1 Quantitative Variable**
#### Overview
<div style="padding-left:125px;">
Great for showing the distribution of data for a single quantitative variable when the sample size is large. Dotplots are a good alternative for smaller sample sizes. Gives a good feel for the [mean](NumericalSummaries.html#mean) and [standard deviation](NumericalSummaries.html#sd) of the data.
</div>
----
#### R Instructions
<div style="padding-left:125px;">
<div class="tab">
<button class="tablinks" onclick="openTab(event, 'BaseHistogram')">Base R</button>
<button class="tablinks" onclick="openTab(event, 'ggplot2Histogram')">ggplot2</button>
<button class="tablinks" onclick="openTab(event, 'plotlyHistogram')">plotly</button>
</div>
<div id="BaseHistogram" class="tabcontent">
<p>
To make a histogram in R use the function:
`hist(object)`
* `object` must be quantitative data. R refers to this as a "numeric vector." Usually this will be the column of a dataset accessed with the `$` sign by `hist(dataSetName$columnName)`.
Type `?hist` in your **R Console** to open the help file in R.
<br/>
**Example Code**
Hover your mouse over the example codes to learn more. Click on them to see what they create.
*Basic histogram*
<a href="javascript:showhide('hist1')">
<div class="hoverchunk">
<span class="tooltipr">
hist
<span class="tooltiprtext">An R function "hist" used to create a histogram.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
$
<span class="tooltiprtext">The $ allows us to access any variable from the airquality dataset.</span>
</span><span class="tooltipr">
Temp
<span class="tooltiprtext">"Temp" is a quantitative variable (numeric vector) from the "airquality" dataset.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the hist function.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist1" style="display:none;">
```{r, echo=FALSE}
hist(airquality$Temp)
```
</div>
<br/>
*Change Color*
<a href="javascript:showhide('hist3')">
<div class="hoverchunk">
<span class="tooltipr">
hist(airquality$Temp, <span class="tooltiprtext">This code was explained in the first example code.</span>
</span><span class="tooltipr">
col="skyblue" <span class="tooltiprtext">col= allows us to specify the color of the plot using a named color. The name of the color must be placed in quotations. Type "colors()" in R to see color options.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist3" style="display:none;">
```{r, echo=FALSE}
hist(airquality$Temp, col="skyblue")
```
</div>
<br/>
*Add Titles*
<a href="javascript:showhide('hist2')">
<div class="hoverchunk">
<span class="tooltipr">
hist(airquality$Temp
<span class="tooltiprtext">This part was explained in the first example code.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma allows us to specify optional commands to the function. The space after the comma is not required. It just looks nice.</span>
</span><span class="tooltipr">
col="skyblue"<span class="tooltiprtext">col= allows us to specify the color of the plot using a named color. The name of the color must be placed in quotations. Type "colors()" in R to see color options.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">A comma must always be used to separate additional commands.</span>
</span><span class="tooltipr">
xlab="Temperature"
<span class="tooltiprtext">xlab= stands for "x label." Use it to specify the text to print on the plot under the x-axis. The desired text must always be in quotations.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">A comma must always be used to separate additional commands.</span>
</span><span class="tooltipr">
main="La Guardia Airport Daily Mean Temperatures"
<span class="tooltiprtext">main= lets us specify the "main" title to be placed above the plot. The desired text must always be placed in quotations.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Functions must always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist2" style="display:none;">
```{r, echo=FALSE}
hist(airquality$Temp, col="skyblue", xlab="Temperature", main="La Guardia Airport Daily Mean Temperatures")
```
</div>
</p>
</div>
<div id="ggplot2Histogram" class="tabcontent">
<p>
To make a histogram in R using the ggplot approach, first ensure
`library(ggplot2)`
is loaded. Then,
`ggplot(data, aes(x=column)) + `
`geom_histogram()`
* `data` is the name of your dataset.
* `column` is a column of data from your dataset that is quantitative.
* The aesthetic helper function `aes(x= )` is how you tell the gpplot to make the x-axis become your `column` of data.
* The geometry helper function `geom_histogram()` causes the ggplot to become a histogram.
<br>
**Example Code**
Hover your mouse over the example codes to learn more. Click on them to see what they create.
*Basic Histogram*
<a href="javascript:showhide('hist1ggplot')">
<div class="hoverchunk">
<span class="tooltipr">
ggplot
<span class="tooltiprtext">An R function "ggplot" used to create a framework for a graphic that will have elements added to it with the `+` sign.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma allows us to specify optional commands to the function. The space after the comma is not required. It just looks nice.</span>
</span><span class="tooltipr">
aes(
<span class="tooltiprtext">The `aes` or "aesthetics" function allows you to tell the ggplot how it should appear. This includes things like what the x-axis or y-axis should become.</span>
</span><span class="tooltipr">
x=Temp
<span class="tooltiprtext">"x=" declares which variable will become the x-axis of the graphic.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the aes function.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the ggplot function.</span>
</span><span class="tooltipr">
+
<span class="tooltiprtext">The addition symbol `+` is used to add further elements to the ggplot.</span>
</span><br/><span class="tooltipr">
geom_histogram()
<span class="tooltiprtext">The "geom_histogram()" function causes the ggplot to become a histogram. There are many other "geom_" functions that could be used.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist1ggplot" style="display:none;">
```{r echo=FALSE, message=FALSE, warning=FALSE}
ggplot(airquality, aes(x=Temp)) +
geom_histogram()
```
</div>
<br/>
*Change Bin Width and Color*
<a href="javascript:showhide('hist2ggplot')">
<div class="hoverchunk">
<span class="tooltipr">
ggplot
<span class="tooltiprtext">An R function "ggplot" used to create a framework for a graphic that will have elements added to it with the `+` sign.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma allows us to specify optional commands to the function. The space after the comma is not required. It just looks nice.</span>
</span><span class="tooltipr">
aes(
<span class="tooltiprtext">The `aes` or "aesthetics" function allows you to tell the ggplot how it should appear. This includes things like what the x-axis or y-axis should become.</span>
</span><span class="tooltipr">
x=Temp
<span class="tooltiprtext">"x=" declares which variable will become the x-axis of the graphic.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the aes function.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the ggplot function.</span>
</span><span class="tooltipr">
+
<span class="tooltiprtext">The addition symbol `+` is used to add further elements to the ggplot.</span>
</span><br/><span class="tooltipr">
geom_histogram(
<span class="tooltiprtext">The "geom_histogram()" function causes the ggplot to become a histogram. There are many other "geom_" functions that could be used.</span>
</span><span class="tooltipr">
binwidth=5,
<span class="tooltiprtext">The "binwidth" command controls the width of the bars in the histogram.</span>
</span><span class="tooltipr">
fill="skyblue",
<span class="tooltiprtext">The "fill" command controls the color of the insides of each bar.</span>
</span><span class="tooltipr">
color="black"
<span class="tooltiprtext">The "color" command controls the color of the edges of each bar.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the geom_histogram function.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist2ggplot" style="display:none;">
```{r echo=FALSE, message=FALSE, warning=FALSE}
ggplot(airquality, aes(x=Temp)) +
geom_histogram(binwidth = 5, fill = "skyblue", color = "black")
```
</div>
<br/>
*Add Titles*
<a href="javascript:showhide('hist3ggplot')">
<div class="hoverchunk">
<span class="tooltipr">
ggplot
<span class="tooltiprtext">An R function "ggplot" used to create a framework for a graphic that will have elements added to it with the `+` sign.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma allows us to specify optional commands to the function. The space after the comma is not required. It just looks nice.</span>
</span><span class="tooltipr">
aes(
<span class="tooltiprtext">The `aes` or "aesthetics" function allows you to tell the ggplot how it should appear. This includes things like what the x-axis or y-axis should become.</span>
</span><span class="tooltipr">
x=Temp
<span class="tooltiprtext">"x=" declares which variable will become the x-axis of the graphic.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the aes function.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the ggplot function.</span>
</span><span class="tooltipr">
+
<span class="tooltiprtext">The addition symbol `+` is used to add further elements to the ggplot.</span>
</span><br/><span class="tooltipr">
geom_histogram(
<span class="tooltiprtext">The "geom_histogram()" function causes the ggplot to become a histogram. There are many other "geom_" functions that could be used.</span>
</span><span class="tooltipr">
binwidth=5,
<span class="tooltiprtext">The "binwidth" command controls the width of the bars in the histogram.</span>
</span><span class="tooltipr">
fill="skyblue",
<span class="tooltiprtext">The "fill" command controls the color of the insides of each bar.</span>
</span><span class="tooltipr">
color="black"
<span class="tooltiprtext">The "color" command controls the color of the edges of each bar.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the geom_histogram function.</span>
</span><span class="tooltipr">
+
<span class="tooltiprtext">The addition symbol `+` is used to add further elements to the ggplot.</span>
</span><br/><span class="tooltipr">
labs(
<span class="tooltiprtext">The "labs" function is used to add labels to the plot, like a main title, x-label and y-label.</span>
</span><span class="tooltipr">
title="La Guardia Airport Daily Mean Temperature",
<span class="tooltiprtext">The "title=" command allows you to control the main title at the top of the graphic.</span>
</span><span class="tooltipr">
x="Temperature",
<span class="tooltiprtext">The "x=" command allows you to control the x-label of the graphic.</span>
</span><span class="tooltipr">
y="Number of Days"
<span class="tooltiprtext">The "y=" command allows you to control the y-label of the graphic.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the labs function.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="hist3ggplot" style="display:none;">
```{r echo=FALSE, message=FALSE, warning=FALSE}
ggplot(airquality, aes(x=Temp)) +
geom_histogram(binwidth = 5, fill = "skyblue", color = "black") +
labs(title="La Guardia Airport Daily Mean Temperature", x="Temperature", y="Number of Days")
```
</div>
<br/>
**Gallery**
See some ideas from past students...
<a href="javascript:showhide('histogramgalleryggplot')">Show/Hide Gallery</a>
<div id="histogramgalleryggplot" style="display:none;">
Hover to see code. Copy the code into R. Play with it. Modify it to create your own graph.
<span class="tooltipgallery">
<img class="gallerygraphs" src="./Images/histogramggplotgallery1.png">
<span class="tooltipgallerytext">
`ggplot(airquality, aes(x = Temp)) +` <br/>
` geom_histogram(binwidth=5, fill = "skyblue", color = "black") + ` <br/>
` labs(title = "La Guardia Airport Daily Mean Temperature", ` <br/>
` x = "Temperature", y = "Number of Days") + ` <br/>
` theme_bw() + ` <br/>
` theme(plot.title = element_text(size = 14, face = "bold", hjust = .5), ` <br/>
` panel.grid.major = element_line(color = "grey80")) ` <br/>
</span>
</span>
<span class="tooltipgallery">
<img class="gallerygraphs" src="./Images/histogramggplotgallery2.png">
<span class="tooltipgallerytext">
`ggplot(airquality) + ` <br/>
` geom_histogram(aes(x = Temp, fill = Temp > median(Temp)), color = "black", binwidth = 2) + ` <br/>
` labs(title = "La Guardia Airport Daily Mean Temperature", ` <br/>
` x = "Temperature", y = "Number of Days") + ` <br/>
` theme_bw() + ` <br/>
` theme(plot.title = element_text(size = 14, face = "bold", hjust = .5),` <br/>
` panel.grid.major = element_line(color = "grey80"), ` <br/>
` legend.position = "none") + ` <br/>
` geom_vline(xintercept = 72, linetype = "dashed", size = 1.5, color = "black") + ` <br/>
` geom_vline(xintercept = 85, linetype = "dashed", size = 1.5, color = "black") + ` <br/>
` geom_text(x = 71, y = 10, label = "Q1") + ` <br/>
` geom_text(x = 86, y = 10, label = "Q3") ` <br/>
</span>
</span>
<span class="tooltipgallery">
<img class="gallerygraphs" src="./Images/histogramggplotgallery3.png">
<span class="tooltipgallerytext">
` ggplot(airquality, aes(x = Temp)) + ` <br/>
` geom_histogram(aes(fill = Temp > median(Temp)), color = "black", binwidth = 2) + ` <br/>
` labs(title = "La Guardia Airport Daily Mean Temperature", ` <br/>
` x = "Temperature", y = "Number of Days", fill = "Temperature") + ` <br/>
` theme_bw() + ` <br/>
` theme(plot.title = element_text(size = 10, face = "bold", hjust = .5),` <br/>
` panel.grid.major = element_line(color = "grey80")) + ` <br/>
` scale_fill_manual(values = c("steelblue2","brown1"),labels=c("< 79 Degrees","> 79 Degrees")) + ` <br/>
` geom_vline(xintercept = 72, linetype = "dashed", size = 1.5, color = "black") + ` <br/>
` geom_vline(xintercept = 85, linetype = "dashed", size = 1.5, color = "black") + ` <br/>
` geom_text(x = 71, y = 10, label = "Q1") + ` <br/>
` geom_text(x = 86, y = 10, label = "Q3") ` <br/>
</span>
</span>
<span class="tooltipgallery">
<img class="gallerygraphs" src="./Images/histogramggplotgallery4.png">
<span class="tooltipgallerytext">
` ggplot(airquality, aes(x = Temp)) + ` <br/>
` geom_histogram(aes(fill = Temp > median(Temp)), color = "black", binwidth = 3) + ` <br/>
` labs(title = "Temperature of La Guardia Airport by Month", ` <br/>
` x = "Temperature", y = "Number of Days", fill = "Temperature") + ` <br/>
` theme_bw() + ` <br/>
` theme(plot.title = element_text(size = 16, face = "bold", hjust = .5),` <br/>
` panel.grid.major = element_line(color = "grey80")) + ` <br/>
` scale_fill_manual(values = c("steelblue2","brown1"),labels=c("< 79 Degrees","> 79 Degrees")) + ` <br/>
` facet_grid(~Month) + ` <br/>
` geom_vline(xintercept = 77.88, linetype = "dashed", size = 1.5, color = "black") + ` <br/>
` geom_text(x = 69, y = 10, label = "Mean = \n 77.88") ` <br/>
</span>
</span>
</div>
</p>
</div>
<div id="plotlyHistogram" class="tabcontent">
<p>
To make a histogram in plotly first load
`library(plotly)`
Then, use the function:
`plot_ly(dataName, x=~columnName, type="histogram")`
* `dataName` is the name of a data set
* `columnName` must be the name of a column of quantitative data. R refers to this as a "numeric vector."
* `type="histogram"` tells the plot_ly(...) function to create a histogram.
Visit [plotly.com/r/histograms](https://plotly.com/r/histograms/) for more details.
<br/>
**Example Code**
Hover your mouse over the example codes to learn more. Click on them to see what they create.
*Basic histogram*
<a href="javascript:showhide('plotlyhist1')">
<div class="hoverchunk">
<span class="tooltipr">
plot_ly
<span class="tooltiprtext">An R function "plot_ly" from library(plotly) used to create any plotly plot.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality,
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
x=
<span class="tooltiprtext">The x= allows us to declare which column of the data set will become the x-axis of the histogram.</span>
</span><span class="tooltipr">
~Temp,
<span class="tooltiprtext">"Temp" is a quantitative variable (numeric vector) from the "airquality" dataset. The `~` is required before column names inside all plot_ly(...) commands.</span>
</span><span class="tooltipr">
type="histogram"
<span class="tooltiprtext">This option tells the plot_ly(...) function what "type" of graph to make. In this case, a histogram.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the plot_ly function.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="plotlyhist1" style="display:none;">
```{r, echo=FALSE, warning=FALSE}
plot_ly(airquality, x=~Temp, type="histogram")
```
</div>
<br/>
*Change Color*
<a href="javascript:showhide('plotlyhist3')">
<div class="hoverchunk">
<span class="tooltipr">
plot_ly(airquality, x=~Temp, type="histogram", <span class="tooltiprtext">This code was explained in the first example code.</span>
</span><span class="tooltipr">
marker=list( <span class="tooltiprtext">this "list(...)" of options that will be specified will effect the bars of the histogram.</span>
</span><span class="tooltipr">
color = "skyblue", <span class="tooltiprtext">this will change the color of the bars to skyblue.</span>
</span><span class="tooltipr">
line = list(, <span class="tooltiprtext">this opens a list of options to specify for the "lines" around the "markers."</span>
</span><span class="tooltipr">
color = "darkgray", <span class="tooltiprtext">this will change the color of the lines around the bars to darkgray.</span>
</span><span class="tooltipr">
width = 2 <span class="tooltiprtext">this will change the width of the lines around the bars to 2 pixels. Too really see what this does, change it to something crazy like 10.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="plotlyhist3" style="display:none;">
```{r, echo=FALSE}
plot_ly(airquality, x=~Temp, type="histogram", marker = list( color="skyblue", line = list(color="darkgray", width=2)))
```
</div>
<br/>
*Add Titles*
<a href="javascript:showhide('plotlyhist2')">
<div class="hoverchunk">
<span class="tooltipr">
plot_ly(airquality$Temp, type="histogram", <span class="tooltiprtext">This code was explained in the first example code.</span>
</span><span class="tooltipr">
marker=list( <span class="tooltiprtext">this "list(" of options that will be specified will effect the bars of the histogram.</span>
</span><span class="tooltipr">
color = "skyblue", <span class="tooltiprtext">this will change the color of the bars to skyblue.</span>
</span><span class="tooltipr">
line = list(, <span class="tooltiprtext">this opens a list of options to specify for the "lines" around the "markers."</span>
</span><span class="tooltipr">
color = "darkgray", <span class="tooltiprtext">this will change the color of the lines around the bars to darkgray.</span>
</span><span class="tooltipr">
width = 10 <span class="tooltiprtext">this will change the width of the lines around the bars to 10 pixels, which is rather large really. Using a width=2 is probably better.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
%>% <span class="tooltiprtext">The pipe operator passes the completed plot_ly(...) code into the layout(...) function.</span>
</span><br/><span class="tooltipr">
layout( <span class="tooltiprtext">The layout(...) function is used for specifying details about the axes and their labels.</span>
</span><span class="tooltipr">
title="La Guardia Airport Daily Mean Temperatures" <span class="tooltiprtext">This declares a main title for the top of the graph.</span>
</span><span class="tooltipr">
xaxis=list( <span class="tooltiprtext">This declares a list of options to be specified for the xaxis. The same can be done for the yaxis(...).</span>
</span><span class="tooltipr">
title="Temperature in Degrees F" <span class="tooltiprtext">This declares a title underneath the x-axis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="plotlyhist2" style="display:none;">
```{r, echo=FALSE}
plot_ly(airquality, x=~Temp, type="histogram", marker=list( color="skyblue", line=list(color="darkgray", width=10))) %>%
layout(title="La Guardia Airport Daily Mean Temperatures", xaxis=list(title="Temperature in Degrees F"))
```
</div>
</p>
</div>
</div>
----
#### Explanation
<div style="padding-left:125px;">
Histograms group data that are close to each other into "bins" (the vertical bars in the plot). The height of a bin is determined by the number of data points that are contained within the bin. For example, if we group together all the sections of the book of scripture known as the [Doctrine and Covenants](https://www.lds.org/scriptures/dc-testament/chron-order?lang=eng) that occurred in a given year (Jan. 1st - Dec. 31st) then we get the following counts.
| Year | Number of Sections |
|------|--------------------|
| 1823 | 1 |
| 1824 | 0 |
| 1825 | 0 |
| 1826 | 0 |
| 1827 | 0 |
| 1828 | 1 |
| 1829 | 16 |
| 1830 | 19 |
| 1831 | 37 |
| 1832 | 16 |
| 1833 | 12 |
| 1834 | 5 |
| 1835 | 3 |
| 1836 | 4 |
| 1837 | 1 |
| 1838 | 8 |
| 1839 | 3 |
| 1840 | 0 |
| 1841 | 3 |
| 1842 | 2 |
| 1843 | 4 |
| 1844 | 1 |
| 1845 | 0 |
| 1846 | 0 |
| 1847 | 1 |
<span style="padding-left:30px; color:#a8a8a8; font-size:.8em;">
*Note that Section 138 occurred in 1918 and is removed from this example.
</span>
In this example, each "bin" spans 365 days (Jan. 1 - Dec. 31 of each year). Since "dates" can be used as quantitative data, it makes sense to make a histogram of these data. (Remember, histograms are only for quantitative data.)
```{r, echo=FALSE}
revs <- read.csv("./Data/DCRevelationDates.csv", header=TRUE)
revs$Date <- as.Date(revs$Date, "%d %b %Y")
breaks <- c(-53692, -53327, -52961, -52596, -52231, -51866, -51500,
-51135, -50770, -50405, -50039, -49674, -49309, -48944,
-48578, -48213, -47848, -47483, -47117, -46752, -46387,
-46022, -45656, -45291, -44926, -44561)
hist(revs$Date[-length(revs$Date)], "year", las=2,
freq=TRUE, xlab="Year", main="Dates of D&C Revelations", right=FALSE,
include.lowest=FALSE, axes=FALSE)
axis(1,at=breaks,labels=1823:1848, las=2)
axis(2,at=0:19*2, las=2)
```
Notice in the bins above that the left edge of the bin is on the year the data corresponds with. The right edge of the bin lands on the following year. For example, the first bin has left edge on 1823 and right edge on 1824. Since there was one revelation in 1823, this bin has a height of 1. The bin that has 1831 on the left and 1832 on the right shows that 37 revelations occurred in 1831. It is powerful to notice the amount of revelations occurring around 1830, the year the [Church of Jesus Christ of Latter-day Saints](https://www.lds.org/?lang=eng) was organized.
</div>
----
### Boxplots {.tabset .tabset-fade .tabset-pills}
<div style="float:left;width:125px;">
```{r, fig.height=1, fig.width=1, echo=FALSE}
par(mai=c(0,0,0,0))
boxplot(uptake ~ Treatment, data=CO2, yaxt='n', col='lightgray')
```
</div>
**1 Quantitative Variable | 2+ Groups**
#### Overview
<div style="padding-left:125px;">
Graphical depiction of the [five-number summary](NumericalSummaries.html#quartiles). Great for comparing the distributions of data across several groups or categories. Provides a quick visual understanding of the location of the median as well as the range of the data. Can be useful in showing outliers. Sample size should be larger than at least five, or computing the *five*-number summary is not very meaningful. Side-by-side dotplots are a good alternative for smaller sample sizes.
</div>
----
#### R Instructions
<div style="padding-left:125px;">
<div class="tab">
<button class="tablinks" onclick="openTab(event, 'BaseBoxplot')">Base R</button>
<button class="tablinks" onclick="openTab(event, 'ggplot2Boxplot')">ggplot2</button>
<button class="tablinks" onclick="openTab(event, 'plotlyBoxplot')">plotly</button>
</div>
<div id="BaseBoxplot" class="tabcontent">
<p>
To make a boxplot in R use the function:
`boxplot(object)`
To make side-by-side boxplots:
`boxplot(object ~ group, data=NameOfYourData, ...)`
* `object` must be quantitative data. R refers to this as a "numeric vector."
* `group` must be qualitative data. R refers to this as either a "character vector" or a "factor." However, a "numeric vector" can also act as a qualitative variable.
* `NameOfYourData` is the name of the dataset containing `object` and `group`.
* `...` implies there are many other options that can be given to the `boxplot()` function. Type `?boxplot` in your **R Console** for more details.
**Example Code**
*Basic Single Boxplot*
<a href="javascript:showhide('boxplot0')">
<div class="hoverchunk">
<span class="tooltipr">
boxplot
<span class="tooltiprtext">An R function "boxplot" used to create boxplots.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
airquality
<span class="tooltiprtext">"airquality" is a dataset. Type "View(airquality)" in R to see it.</span>
</span><span class="tooltipr">
$
<span class="tooltiprtext">The $ allows us to access any variable from the airquality dataset.</span>
</span><span class="tooltipr">
Temp
<span class="tooltiprtext">"Temp" is a quantitative variable (numeric vector) from the "airquality" dataset.</span>
</span><span class="tooltipr">
)
<span class="tooltiprtext">Closing parenthsis for the function.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="boxplot0" style="display:none;">
```{r, echo=FALSE}
boxplot(airquality$Temp)
```
</div>
<br/>
*More Useful... Basic Side-by-Side Boxplot*
<a href="javascript:showhide('boxplot1')">
<div class="hoverchunk">
<span class="tooltipr">
boxplot
<span class="tooltiprtext">An R function "boxplot" used to create boxplots.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
Temp
<span class="tooltiprtext">"Temp" is a quantitative variable (numeric vector) from the "airquality" dataset.</span>
</span><span class="tooltipr">
~
<span class="tooltiprtext">The ~ is used to tell R that you want one boxplot of the quantitative variable ("Temp") for each group found in the qualitative variable ("Month").</span>
</span><span class="tooltipr">
Month
<span class="tooltiprtext">"Month" is a qualitative variable (in this case a "numeric vector" defining months by 5, 6, 7, 8, and 9) from the "airquality" dataset.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The "," is required to start specifying additional commands for the "boxplot()" function.</span>
</span><span class="tooltipr">
data=airquality
<span class="tooltiprtext">data= is used to tell R that the "Temp" and "Month" variables are located in the <span style="font-weight:bold">airquality</span> dataset. Without this, R will not know where to find "Temp" and "Month" and the command will give an error.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a><div id="boxplot1" style="display:none;">
```{r, echo=FALSE}
boxplot(Temp ~ Month, data=airquality)
```
</div>
<br/>
*Add Names under each Box*
<a href="javascript:showhide('boxplot2a')">
<div class="hoverchunk">
<span class="tooltipr">
boxplot
<span class="tooltiprtext">An R function "boxplot" used to create boxplots.</span>
</span><span class="tooltipr">
(
<span class="tooltiprtext">Parenthesis to begin the function. Must touch the last letter of the function.</span>
</span><span class="tooltipr">
Temp
<span class="tooltiprtext">"Temp" is a quantitative variable (numeric vector) from the "airquality" dataset.</span>
</span><span class="tooltipr">
~
<span class="tooltiprtext">The ~ is used to tell R that you want one boxplot of the quantitative variable ("Temp") for each group found in the qualitative variable ("Month").</span>
</span><span class="tooltipr">
Month
<span class="tooltiprtext">"Month" is a qualitative variable (in this case a "numeric vector" defining months by 5, 6, 7, 8, and 9) from the "airquality" dataset.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The "," is required to start specifying additional commands for the "boxplot()" function.</span>
</span><span class="tooltipr">
data=airquality
<span class="tooltiprtext">data= is used to tell R that the "Temp" and "Month" variables are located in the <span style="font-weight:bold">airquality</span> dataset. Without this, R will not know where to find "Temp" and "Month" and the command will give an error.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The "," is required to start specifying additional commands for the "boxplot()" function.</span>
</span><span class="tooltipr">
names=c("May","June","July","Aug","Sep")
<span class="tooltiprtext">names= is used to tell R what labels to place on the x-axis below each boxplot.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a><div id="boxplot2a" style="display:none;">
```{r, echo=FALSE}
boxplot(Temp ~ Month, data=airquality, names=c("May","June","July","Aug","Sep"))
```
</div>
<br/>
*Add Color and Labels*
<a href="javascript:showhide('boxplot2')">
<div class="hoverchunk">
<span class="tooltipr">
boxplot(Temp ~ Month, data=airquality
<span class="tooltiprtext">This code was explained in the previous example code.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma is used to separate each additional command to a function.</span>
</span><span class="tooltipr">
xlab="Month of the Year"
<span class="tooltiprtext">xlab= stands for "x label." Use it to specify the text to print on the plot under the x-axis. The desired text must always be contained in quotes.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma is used to separate each additional command to a function.</span>
</span><span class="tooltipr">
ylab="Temperature"
<span class="tooltiprtext">ylab= stands for "y label." Use it to specify the text to print on the plot next to the y-axis. The desired text must always be contained in quotes.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma is used to separate each additional command to a function.</span>
</span><span class="tooltipr">
main="La Guardia Airport Daily Temperatures"
<span class="tooltiprtext">main= stands for the "main label" of the plot, which is placed at the top center of the plot. The desired text must always be contained in quotes.</span>
</span><span class="tooltipr">
,
<span class="tooltiprtext">The comma is used to separate each additional command to a function.</span>
</span><span class="tooltipr">
col="wheat"
<span class="tooltiprtext">col= stands for the "color" of the plot. The color name "wheat" is an available color in R. Type colors() in the R Console to see more options. The color name must always be placed in quotes.</span>
</span><span class="tooltipr">
) <span class="tooltiprtext">Functions always end with a closing parenthesis.</span>
</span><span class="tooltipr">
<span class="tooltiprtext">Press Enter to run the code.</span>
</span><span class="tooltipr" style="float:right;">
...
<span class="tooltiprtext">Click to View Output.</span>
</span>
</div>
</a>
<div id="boxplot2" style="display:none;">
```{r, echo=FALSE}
boxplot(Temp ~ Month, data=airquality, xlab="Month of the Year", ylab="Temperature", main="La Guardia Airport Daily Temperatures", col="wheat")
```
</div>
</p>
</div>
<div id="ggplot2Boxplot" class="tabcontent">
<p>
To make a boxplot in R using the ggplot approach, first ensure
`library(ggplot2)`
is loaded. Then,
`ggplot(data, aes(x=groupsColumn, y=dataColumn) + `
`geom_boxplot()`