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<!DOCTYPE html>
<html>
<head>
<title>Introduction to Plotly</title>
<meta charset="utf-8">
<meta name="author" content="Kris Kindle" />
<meta name="date" content="2018-11-05" />
<link href="libs/remark-css-0.0.1/default.css" rel="stylesheet" />
<link href="libs/remark-css-0.0.1/default-fonts.css" rel="stylesheet" />
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<script src="libs/colourpicker-1.1/colourpicker.min.js"></script>
</head>
<body>
<textarea id="source">
class: center, middle, inverse, title-slide
# Introduction to Plotly
### Kris Kindle
### 2018-11-05
---
---
# What is Plotly?
--
- Graphing library built using d3.js and stack.gl with apis for many languages popular with data scientist (R, Python, Julia, and more)
--
- Open source (MIT license) with source code available on [Github](https://github.com/ropensci/plotly)
---
# Why Plotly?
--
- Allows the user to create interactive visuals
--
- Can be translated more easily to another language more easily than Base R or GGplot plots (ggplots can also be translated into plotly plots)
--
- Makes visually pleasing plots that we can use in a Shiny application
---
# Plan of Action
In this presentation we will go work through the following:
--
- How to construct some of the most common plot types
--
- How to fine tune some of the plot details
--
- How to animate a plot
--
- How to create sub-plots
--
- How to translate a ggplot to plotly
---
# How to Setup Plotly
To be able to use Plotly we must first install the Plotly library. To do this run the following command.
```r
install.packages("plotly")
```
--
Once you have done that you need to load it into the session.
```r
library(plotly)
```
(Notice to load the library by name we do not use quotes as we did in the installation step)
---
# The libraries used in this presentation
The Plotly library is great, but we will need a few other libraries for the examples that we are going to run through. (If you wish to recreate the examples you will need to install these libraries first)
```
## ── Attaching packages ──────────────────────────────────────────── tidyverse 1.2.1 ──
```
```
## ✔ ggplot2 2.2.1 ✔ purrr 0.2.4
## ✔ tibble 1.4.2 ✔ dplyr 0.7.4
## ✔ tidyr 0.8.0 ✔ stringr 1.3.0
## ✔ readr 1.1.1 ✔ forcats 0.3.0
```
```
## ── Conflicts ─────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
```
```
##
## Attaching package: 'plotly'
```
```
## The following object is masked from 'package:ggplot2':
##
## last_plot
```
```
## The following object is masked from 'package:stats':
##
## filter
```
```
## The following object is masked from 'package:graphics':
##
## layout
```
---
# A Quick Note on the Lahman Package
The Lahman package is name d after Sean Lahman who is a sports reporter that maintains a historical database for baseball data. Data for the years 1871 - 2016 are currently available. This package for R takes the relational tables and makes the data available as a function call.
```r
batting <- Batting
head(batting, n =3)
```
```
## playerID yearID stint teamID lgID G AB R H X2B X3B HR RBI SB CS BB
## 1 abercda01 1871 1 TRO NA 1 4 0 0 0 0 0 0 0 0 0
## 2 addybo01 1871 1 RC1 NA 25 118 30 32 6 0 0 13 8 1 4
## 3 allisar01 1871 1 CL1 NA 29 137 28 40 4 5 0 19 3 1 2
## SO IBB HBP SH SF GIDP
## 1 0 NA NA NA NA NA
## 2 0 NA NA NA NA NA
## 3 5 NA NA NA NA NA
```
---
# The Essentials of a Plotly Plot
```r
plot_ly(
data = ourDF,
x = ~xAxisVariable,
y = ~yAxisVariable,
type = "plotType"
)
```
* Data
+ We must first tell the function where we want to take our data from
* The variables we want to plot
+ Which variables from our data we want to plot as well as which axis we want the data on
* What Type of Plot we want it to make
---
# Our First Example
```r
plot_ly(
data=playersByLeague,
x=~lgID,
y=~TotalPlayers,
type ='bar'
)
```
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.footnote[
[1] For data for examples see the example.R script
]
---
# Example 2
```r
plot_ly(
data=playersByLeagueByYear,
x=~yearID,
y=~TotalPlayers,
type='scatter'
)
```
```
## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
```
<div id="e8429bdd236" style="width:504px;height:216px;" class="plotly html-widget"></div>
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---
# Example 3
```r
plot_ly(
data=playersByLeagueByYear,
x=~lgID,
y=~TotalPlayers,
type='box'
)
```
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---
# Sprucing up Our Plots
So far we have been using just the bare minimum to make our plots lets now add some options to our plots to bring them closer to an end product.The following options are for the plot_ly function.
--
- Color `-` Add color to your plots based on another variable
--
- Hover Info `-` Change what the user sees when they mouse over
--
- Mode `-` For the scatter type of plot we can use this to change it to different plot types
---
# Adding Color
```r
plot_ly(
data=playersByLeagueByYear,
x=~yearID,
y=~TotalPlayers,
color=~lgID,
type='scatter'
)
```
```
## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
```
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---
# Changing Hover-Info
```r
plot_ly(
data=playersByLeague,
x=~lgID,
y=~TotalPlayers,
color=~lgID,
type='bar',
hoverinfo = "text",
text=~paste("League: ", lgID,
"<br> Players: ", TotalPlayers)
)
```
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---
# Changing Scatter Modes
```r
plot_ly(
data=playersByLeagueByYear,
x=~yearID,
y=~TotalPlayers,
color=~lgID,
type='scatter',
mode ='lines'
)
```
<div id="e8457bee769" style="width:504px;height:216px;" class="plotly html-widget"></div>
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2 3 3 5 5 6 1 2 3 5 4 9 2 3 3 7 5 10 1 3 2 6 4 10 2 4 4 7 6 9 2 3 4 5 7 7 3 2 7 3 11 3 3 0 8 0 13-1l0-1c7 2 12 2 14 2l218 0c14 0 25-5 32-16 8-10 10-23 6-37l-79-259c-7-22-13-37-20-43-7-7-19-10-37-10l-248 0c-5 0-9-2-11-5-2-3-2-7 0-12 4-13 18-20 41-20l264 0c5 0 10 2 16 5 5 3 8 6 10 11l85 282c2 5 2 10 2 17 7-3 13-7 17-13z m-304 0c-1-3-1-5 0-7 1-1 3-2 6-2l174 0c2 0 4 1 7 2 2 2 4 4 5 7l6 18c0 3 0 5-1 7-1 1-3 2-6 2l-173 0c-3 0-5-1-8-2-2-2-4-4-4-7z m-24-73c-1-3-1-5 0-7 2-2 3-2 6-2l174 0c2 0 5 0 7 2 3 2 4 4 5 7l6 18c1 2 0 5-1 6-1 2-3 3-5 3l-174 0c-3 0-5-1-7-3-3-1-4-4-5-6z"},"click":"function(gd) { \n // is this being viewed in RStudio?\n if (location.search == '?viewer_pane=1') {\n alert('To learn about plotly for collaboration, visit:\\n https://cpsievert.github.io/plotly_book/plot-ly-for-collaboration.html');\n } else {\n window.open('https://cpsievert.github.io/plotly_book/plot-ly-for-collaboration.html', '_blank');\n }\n }"}],"cloud":false},"data":[{"x":[1882,1883,1884,1885,1886,1887,1888,1889,1890,1891],"y":[113,144,263,163,175,163,164,167,204,201],"mode":"lines","type":"scatter","name":"AA","line":{"fillcolor":"rgba(102,194,165,0.5)","color":"rgba(102,194,165,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1901,1902,1903,1904,1905,1906,1907,1908,1909,1910,1911,1912,1913,1914,1915,1916,1917,1918,1919,1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016],"y":[185,189,179,169,203,204,210,222,258,257,279,326,298,281,291,272,250,246,247,261,250,246,259,272,264,243,259,257,251,256,247,244,234,252,244,238,251,250,261,250,268,254,258,259,263,311,266,261,270,269,278,284,276,273,323,288,284,286,296,293,359,369,356,352,365,360,368,351,440,428,422,432,421,427,437,412,508,490,502,500,490,516,514,511,530,529,537,540,558,568,578,552,582,509,604,604,588,591,602,610,592,612,608,623,598,615,614,624,618,605,616,627,676,694,708,697],"mode":"lines","type":"scatter","name":"AL","line":{"fillcolor":"rgba(252,141,98,0.5)","color":"rgba(252,141,98,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1914,1915],"y":[216,216],"mode":"lines","type":"scatter","name":"FL","line":{"fillcolor":"rgba(141,160,203,0.5)","color":"rgba(141,160,203,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1871,1872,1873,1874,1875],"y":[115,143,122,120,190],"mode":"lines","type":"scatter","name":"NA","line":{"fillcolor":"rgba(231,138,195,0.5)","color":"rgba(231,138,195,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1876,1877,1878,1879,1880,1881,1882,1883,1884,1885,1886,1887,1888,1889,1890,1891,1892,1893,1894,1895,1896,1897,1898,1899,1900,1901,1902,1903,1904,1905,1906,1907,1908,1909,1910,1911,1912,1913,1914,1915,1916,1917,1918,1919,1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016],"y":[121,92,77,119,127,120,121,130,166,172,157,160,172,159,180,173,265,260,263,284,272,263,299,310,188,199,228,199,198,188,209,210,219,250,254,264,283,286,260,233,258,244,246,235,237,245,253,257,258,263,262,257,251,262,240,247,248,231,240,249,246,254,258,278,270,282,265,271,296,290,333,284,287,271,270,277,281,266,275,291,281,292,312,298,300,279,351,359,361,352,364,373,336,433,439,425,422,431,450,428,421,421,429,420,431,426,442,461,448,440,453,475,454,466,491,477,485,565,497,588,587,588,651,647,699,688,650,679,668,683,699,714,720,710,695,718,724,675,672,714,718],"mode":"lines","type":"scatter","name":"NL","line":{"fillcolor":"rgba(166,216,84,0.5)","color":"rgba(166,216,84,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1890],"y":[140],"mode":"lines","type":"scatter","name":"PL","line":{"fillcolor":"rgba(255,217,47,0.5)","color":"rgba(255,217,47,1)"},"xaxis":"x","yaxis":"y","frame":null},{"x":[1884],"y":[274],"mode":"lines","type":"scatter","name":"UA","line":{"fillcolor":"rgba(229,196,148,0.5)","color":"rgba(229,196,148,1)"},"xaxis":"x","yaxis":"y","frame":null}],"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.2,"selected":{"opacity":1}},"base_url":"https://plot.ly"},"evals":["config.modeBarButtonsToAdd.0.click"],"jsHooks":{"render":[{"code":"function(el, 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---
# The Layout Function
The layout function allows to even further customize the look and layout of our plots. To do this we need to pass our plot into the layout function. The following are some basic options avialable in the layout function.
--
- Title `-` Change the title of the plot
--
- showlegend `-` Setting to FALSE will allow us to drop the legend
--
- Axis Option `-` We can set the options for our axis (More on this soon)
---
# Changing Layout Options
```r
plot_ly(
data = playersByLeague,
x = ~lgID,
y = ~TotalPlayers,
color = ~lgID,
hoverinfo = "text",
text=~paste("League: ", lgID,
"<br> Players: ", TotalPlayers),
type = 'bar'
) %>%
layout(title = "Total Unique Players by League", showlegend=F)
```
<div id="e8419e0a994" style="width:504px;height:216px;" class="plotly html-widget"></div>
<script type="application/json" data-for="e8419e0a994">{"x":{"visdat":{"e8464361222":["function () ","plotlyVisDat"]},"cur_data":"e8464361222","attrs":{"e8464361222":{"x":{},"y":{},"hoverinfo":"text","text":{},"color":{},"alpha":1,"sizes":[10,100],"type":"bar"}},"layout":{"margin":{"b":40,"l":60,"t":25,"r":10},"title":"Total Unique Players by League","showlegend":false,"xaxis":{"domain":[0,1],"title":"lgID","type":"category","categoryorder":"array","categoryarray":["NL","AL","AA","NA","FL","UA","PL"]},"yaxis":{"domain":[0,1],"title":"TotalPlayers"},"hovermode":"closest"},"source":"A","config":{"modeBarButtonsToAdd":[{"name":"Collaborate","icon":{"width":1000,"ascent":500,"descent":-50,"path":"M487 375c7-10 9-23 5-36l-79-259c-3-12-11-23-22-31-11-8-22-12-35-12l-263 0c-15 0-29 5-43 15-13 10-23 23-28 37-5 13-5 25-1 37 0 0 0 3 1 7 1 5 1 8 1 11 0 2 0 4-1 6 0 3-1 5-1 6 1 2 2 4 3 6 1 2 2 4 4 6 2 3 4 5 5 7 5 7 9 16 13 26 4 10 7 19 9 26 0 2 0 5 0 9-1 4-1 6 0 8 0 2 2 5 4 8 3 3 5 5 5 7 4 6 8 15 12 26 4 11 7 19 7 26 1 1 0 4 0 9-1 4-1 7 0 8 1 2 3 5 6 8 4 4 6 6 6 7 4 5 8 13 13 24 4 11 7 20 7 28 1 1 0 4 0 7-1 3-1 6-1 7 0 2 1 4 3 6 1 1 3 4 5 6 2 3 3 5 5 6 1 2 3 5 4 9 2 3 3 7 5 10 1 3 2 6 4 10 2 4 4 7 6 9 2 3 4 5 7 7 3 2 7 3 11 3 3 0 8 0 13-1l0-1c7 2 12 2 14 2l218 0c14 0 25-5 32-16 8-10 10-23 6-37l-79-259c-7-22-13-37-20-43-7-7-19-10-37-10l-248 0c-5 0-9-2-11-5-2-3-2-7 0-12 4-13 18-20 41-20l264 0c5 0 10 2 16 5 5 3 8 6 10 11l85 282c2 5 2 10 2 17 7-3 13-7 17-13z m-304 0c-1-3-1-5 0-7 1-1 3-2 6-2l174 0c2 0 4 1 7 2 2 2 4 4 5 7l6 18c0 3 0 5-1 7-1 1-3 2-6 2l-173 0c-3 0-5-1-8-2-2-2-4-4-4-7z m-24-73c-1-3-1-5 0-7 2-2 3-2 6-2l174 0c2 0 5 0 7 2 3 2 4 4 5 7l6 18c1 2 0 5-1 6-1 2-3 3-5 3l-174 0c-3 0-5-1-7-3-3-1-4-4-5-6z"},"click":"function(gd) { \n // is this being viewed in RStudio?\n if (location.search == '?viewer_pane=1') {\n alert('To learn about plotly for collaboration, visit:\\n https://cpsievert.github.io/plotly_book/plot-ly-for-collaboration.html');\n } else {\n window.open('https://cpsievert.github.io/plotly_book/plot-ly-for-collaboration.html', '_blank');\n }\n }"}],"cloud":false},"data":[{"x":["NL"],"y":[12612],"hoverinfo":"text","text":"League: NL <br> Players: 12612","type":"bar","name":"NL","marker":{"fillcolor":"rgba(102,194,165,0.5)","color":"rgba(102,194,165,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["AL"],"y":[11504],"hoverinfo":"text","text":"League: AL <br> Players: 11504","type":"bar","name":"AL","marker":{"fillcolor":"rgba(252,141,98,0.5)","color":"rgba(252,141,98,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["AA"],"y":[875],"hoverinfo":"text","text":"League: AA <br> Players: 875","type":"bar","name":"AA","marker":{"fillcolor":"rgba(141,160,203,0.5)","color":"rgba(141,160,203,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["NA"],"y":[327],"hoverinfo":"text","text":"League: NA <br> Players: 327","type":"bar","name":"NA","marker":{"fillcolor":"rgba(231,138,195,0.5)","color":"rgba(231,138,195,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["FL"],"y":[285],"hoverinfo":"text","text":"League: FL <br> Players: 285","type":"bar","name":"FL","marker":{"fillcolor":"rgba(166,216,84,0.5)","color":"rgba(166,216,84,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["UA"],"y":[274],"hoverinfo":"text","text":"League: UA <br> Players: 274","type":"bar","name":"UA","marker":{"fillcolor":"rgba(255,217,47,0.5)","color":"rgba(255,217,47,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null},{"x":["PL"],"y":[140],"hoverinfo":"text","text":"League: PL <br> Players: 140","type":"bar","name":"PL","marker":{"fillcolor":"rgba(229,196,148,0.5)","color":"rgba(229,196,148,1)","line":{"color":"transparent"}},"xaxis":"x","yaxis":"y","frame":null}],"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.2,"selected":{"opacity":1}},"base_url":"https://plot.ly"},"evals":["config.modeBarButtonsToAdd.0.click"],"jsHooks":{"render":[{"code":"function(el, x) { var ctConfig = crosstalk.var('plotlyCrosstalkOpts').set({\"on\":\"plotly_click\",\"persistent\":false,\"dynamic\":false,\"selectize\":false,\"opacityDim\":0.2,\"selected\":{\"opacity\":1}}); }","data":null}]}}</script>
---
# Changing Axis Options
To customize the axis of our plot we use the corresponding axis argument to the layout function and pass it a list of the arguments that we want to use. Some things that we can change with options
--
- Title `-` Change the axis label
--
- Font `-` Change the font for the axis label
--
- ticks `-` Change pretty much everything about the axis ticks
--
- type `-` This can be used to change the scale among other things
---
#Example of Axis Options
```r
plot_ly(
data = playersByLeague,
x = ~lgID,
y = ~TotalPlayers,
color = ~lgID,
hoverinfo = "text",
text=~paste("League: ", lgID,
"<br> Players: ", TotalPlayers),
type = 'bar'
) %>%
layout(title = "Total Unique Players by League",
showlegend=F,
xaxis = list(title = "League"),
yaxis=list(title = "Total Players"))
```
<div id="e84370f0b7b" style="width:504px;height:144px;" class="plotly html-widget"></div>
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---
# Using Sub Plots
To place two seperate plots in the same frame you need to save the plots that you want to place in the frame as a variable. Then place these saved plots as the initial arguments of the subplot function.
```r
p1 <- plot_ly(data = shared_data,
x = ~xVariable,
y = ~yVariable,
type = "plot_type"
p2 <- plot_ly(data = shared_data,
x = ~xVariable,
y = ~yVariable,
type = "plot_type")
subplot(p1, p2)
```
---
# Sub Plot Examples
```r
p1 <- plot_ly(
data = playerMeanAtBatsYearLeague,
x= ~yearID,
y= ~MeanAtBats,
type ='scatter',
mode='lines',
name='Mean of At-Bats'
)
p2 <- plot_ly(
data = playerMeanAtBatsYearLeague,
x= ~yearID,
y= ~TotalPlayers,
type ='scatter',
mode='lines',
name = 'Total Players'
)
subplot(p1,p2, nrows = 2, shareX = T)
```
---
# Output of Subplot
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---
# Animate Your Plots
To animate a plot we will need to use three functions specific to animation as well as add an option in to our plot. The option that we need to specify is the frame that we want to capture. The three functions that we will need are :
--
- animation_opts `-` Set the specifics of the animation such as how long each frame is shown
--
- animation_button `-` Add the play button as well as specify it position in the plot
--
-animation_slider `-` Slider that will allow us to scrub through frames
---
# Animated Plot Example
```r
plot_ly(
data = playerMeanAtBatsYearLeague,
x = ~TotalPlayers,
y = ~jitter(MeanAtBats),
hoverinfo = 'text',
text = ~teamID
) %>%
add_markers(frame = ~yearID) %>%
layout(title = "Total Players vs. Mean of At-Bats",
xaxis = list(title = "Total Players"),
yaxis = list(title = "Mean of At-Bats")) %>%
animation_opts(300, easing = 'elastic', redraw = F) %>%
animation_button(
x = 1, xanchor = "right", y = 0, yanchor = "bottom"
) %>%
animation_slider(
currentvalue = list(prefix = "Year ", font = list(color="red"))
)
```
---
# Animation Example Output
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---
# Maps
Plotly comes with a function that can create goegraphic maps (plot_geo). To make use of it we need our dataset to contain a column of standard region names (For example: State Names).
```r
plot_geo(usPlayers) %>%
add_trace(
z = ~Total,
locations = ~birthState,
locationmode = 'USA-states',
text = ~paste("State: ", birthState,
"<br> Total: ", Total)
) %>%
layout(geo = list(
scope = 'usa',
projection = list(type = 'albers usa'),
lakecolor = toRGB('white')
))
```
---
# Map Output
<div id="e843bca0738" style="width:504px;height:504px;" class="plotly html-widget"></div>
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---
# Linking Plots
To link plots we need to use the crosstalk library. This will allow us to create a shared data object for the plots to use. Once we create this we can then specify which user interactions will modify the plots.
---
# Example Linked Plot
```r
sharedData <- SharedData$new(playerMeanAtBatsYearLeague, ~teamID, "Select a Team")
p1 <- plot_ly(data = sharedData) %>%
group_by(teamID) %>%
add_markers(
x = ~TotalPlayers,
y = ~teamID)
p2 <- plot_ly(data=sharedData) %>%
group_by(teamID) %>%
add_lines(
x = ~yearID,
y = ~TotalPlayers,
type= 'scatter',
mode = 'lines')
subplot(p1, p2, widths = c(0.3, 0.7)) %>%
hide_legend() %>%
highlight(dynamic = TRUE, selectize = TRUE)
```
---
# Linked Plot Output
```
## Adding more colors to the selection color palette
```
```
## Setting the `off` event (i.e., 'plotly_doubleclick') to match the `on` event (i.e., 'plotly_click'). You can change this default via the `highlight()` function.
```
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