Plotly
2025-03-18
library(plotly)
library(dplyr)
library(tibble)
library(ggplot2)## https://plotly.com/r/figure-structure/#figures-as-trees-of-attributes
# Attributes:
# Data - listed by trace ~~ geoms
# Layout - title/legend/axes/tickmarks
# Frames - for animationsAnnotate Points with mouseover labels
mtcarsdata <- mtcars %>% rownames_to_column(var="model")plotly code
plot_ly(mtcarsdata, x= ~ mpg, y= ~ disp,
text=~model)with ggplot syntax
carsplot <- mtcarsdata %>%
ggplot(aes(x=mpg, y=disp, text=model))+
geom_point(aes(fill=NA))
ggplotly(carsplot)ggplotly(carsplot, tooltip=c("model"))You can zoom in !!
library(gapminder)
p <- gapminder %>%
ggplot(aes(x=year, y=pop, group=country, color=continent, text=lifeExp))+
scale_y_continuous(transform="log")+
geom_line()
ggplotly(p)ggplotly(p, tooltip=c("country"))can’t label with a column not referenced in ggplot.
ggplotly(p, tooltip=c("gdpPercap")) #Doesn't workggplotly(p, tooltip=c("lifeExp")) #Does work because lifeExp is in ggplot as textMaps
https://plotly.com/r/#maps
library(rjson)
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
counties <- rjson::fromJSON(file=url)
url2<- "https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv"
df <- read.csv(url2, colClasses=c(fips="character"))
g <- list(
scope = 'usa',
projection = list(type = 'albers usa'),
showlakes = TRUE,
lakecolor = toRGB('white')
)
plot_ly() %>%
add_trace(
type="choropleth",
geojson=counties,
locations=df$fips,
z=df$unemp,
colorscale="Viridis",
zmin=0,
zmax=12#,
#marker=list(line=list(width=0))
) %>%
colorbar(title = "Unemployment Rate (%)") %>%
layout( title = "2016 US Unemployment by County") %>%
layout(geo = g)#Scatterplot on Maps
airtraffic <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')
# geo styling
g <- list(
scope = 'usa',
projection = list(type = 'albers usa'),
showland = TRUE,
landcolor = toRGB("gray95"),
subunitcolor = toRGB("gray85"),
countrycolor = toRGB("gray85"),
countrywidth = 0.5,
subunitwidth = 0.5
)
plot_geo(airtraffic, lat = ~lat, lon = ~long) %>%
add_markers(
text = ~paste(airport, city, state, paste("Arrivals:", cnt), sep = "<br />"),
color = ~cnt, symbol = I("square"), size = I(8), hoverinfo = "text") %>%
colorbar(title = "Incoming flights<br />February 2011") %>%
layout(title = 'Most trafficked US airports<br />(Hover for airport)',
geo = g)#Explore 3d Charts
Illustrate 3-way interaction of continuous variables
https://plotly.com/r/3d-scatter-plots/
bank <- read.csv('bankdata_emmeans.csv')
bankmod <- lm(log(currentsalary)~age*experience, data=bank)
summary(bankmod)
Call:
lm(formula = log(currentsalary) ~ age * experience, data = bank)
Residuals:
Min 1Q Median 3Q Max
-0.9759 -0.2613 -0.0775 0.2610 0.9886
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.5477898 0.0909491 126.970 < 2e-16 ***
age -0.0232583 0.0026525 -8.769 < 2e-16 ***
experience 0.0562505 0.0111394 5.050 6.34e-07 ***
age:experience -0.0006798 0.0002035 -3.341 0.000902 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3682 on 470 degrees of freedom
Multiple R-squared: 0.2385, Adjusted R-squared: 0.2337
F-statistic: 49.08 on 3 and 470 DF, p-value: < 2.2e-16anova(bankmod)Analysis of Variance Table
Response: log(currentsalary)
Df Sum Sq Mean Sq F value Pr(>F)
age 1 12.547 12.5472 92.553 < 2.2e-16 ***
experience 1 5.901 5.9012 43.529 1.128e-10 ***
age:experience 1 1.513 1.5130 11.161 0.000902 ***
Residuals 470 63.717 0.1356
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1library(emmeans)
bankmod.emm <- as.data.frame(emmeans(bankmod, ~age*experience,
at=list(age=seq(25, 65, by=5), experience=seq(0, 40, by=5))))static way to show interaction
ggplot(bankmod.emm, aes(x=age, y=emmean, color=experience, group=experience))+
geom_line()
the plotly way
plot_ly(bankmod.emm, x = ~age, y = ~experience, z = ~emmean,
text = ~paste(lower.CL, '-', upper.CL))plot_ly(bankmod.emm, x = ~age, y = ~experience, z = ~emmean, type="mesh3d",
text = ~paste(lower.CL, '-', upper.CL))gapm5yr <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv")
data_2007 <- gapm5yr[which(gapm5yr$year == 2007),]
data_2007 <- data_2007[order(data_2007$continent, data_2007$country),]
data_2007$size <- data_2007$pop
colors <- c('#4AC6B7', '#1972A4', '#965F8A', '#FF7070', '#C61951')
plot_ly(data_2007, x = ~gdpPercap, y = ~lifeExp, z = ~pop,
color = ~continent,
# size = ~size,
colors = colors,
marker = list(symbol = 'circle', sizemode = 'diameter'),
sizes = c(5, 150),
text = ~paste('Country:', country, '<br>Life Expectancy:', lifeExp, '<br>GDP:', gdpPercap,'<br>Pop.:', pop)) %>%
layout(title = 'Life Expectancy v. Per Capita GDP, 2007',
scene = list(xaxis = list(title = 'GDP per capita (2000 dollars)',
gridcolor = 'rgb(255, 255, 255)',
range = c(2.003297660701705, 5.191505530708712),
type = 'log',
zerolinewidth = 1,
ticklen = 5,
gridwidth = 2),
yaxis = list(title = 'Life Expectancy (years)',
gridcolor = 'rgb(255, 255, 255)',
range = c(36.12621671352166, 91.72921793264332),
zerolinewidth = 1,
ticklen = 5,
gridwith = 2),
zaxis = list(title = 'Population',
gridcolor = 'rgb(255, 255, 255)',
type = 'log',
zerolinewidth = 1,
ticklen = 5,
gridwith = 2)))Custom controls- wihtout shiny!
https://plotly.com/r/#controls
library(quantmod)
# Download some data
getSymbols(Symbols = c("AAPL", "MSFT"), from = '2018-01-01', to = '2019-01-01')[1] "AAPL" "MSFT"ds <- data.frame(Date = index(AAPL), AAPL[,6], MSFT[,6])
plot_ly(ds, x = ~Date) %>%
add_lines(y = ~AAPL.Adjusted, name = "Apple") %>%
add_lines(y = ~MSFT.Adjusted, name = "Microsoft")%>%
layout(title = "Stock Prices",
xaxis = list(
rangeselector = list(buttons = list(list(count = 3,
label = "3 mo",
step = "month",
stepmode = "backward"),
list(count = 6,
label = "6 mo",
step = "month",
stepmode = "backward"),
list(count = 1,
label = "1 yr",
step = "year",
stepmode = "backward"),
list(count = 1,
label = "YTD",
step = "year",
stepmode = "todate"),
list(step = "all"))),
rangeslider = list(type = "date")),
yaxis = list(title = "Price"))Animations?
https://plotly.com/r/animations/
gapminder %>%
plot_ly(x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
frame = ~year,
text = ~country,
hoverinfo = "text",
type = 'scatter',
mode = 'markers'
)%>%
layout(xaxis = list(type = "log"))