I used plotly to create a plot with multiple annotations. This is my code and it works as intended:
library(plotly)
a <- 1:10
b <- 1:10
data <- data.frame(a,b)
annotations <- list(x = a[3:4],
y = b[3:4],
text = c("p1","p2"),
showarrow = TRUE)
p <- plot_ly(data = data, x = ~a, y = ~b, type = "scatter", mode = "lines")
p <- layout(p, annotations = annotations)
p
But I can't figure out how to properly implement buttons to turn the annotations on and off. My code below implements buttons, but when I use them, only one arrow is shown, that is out of place and has no text.
library(plotly)
a <- 1:10
b <- 1:10
data <- data.frame(a,b)
annotations <- list(x = a[3:4],
y = b[3:4],
text = c("p1","p2"),
showarrow = TRUE)
updatemenus <- list(
list(
type= 'buttons',
buttons = list(
list(
label = "ON",
method = "update",
args = list(list(),
list(annotations = list(annotations)))),
list(
label = "OFF",
method = "update",
args = list(list(),
list(annotations = list(c()))))
)
)
)
p <- plot_ly(data = data, x = ~a, y = ~b, type = "scatter", mode = "lines")
p <- layout(p, updatemenus = updatemenus)
p
It would be nice if anyone could help me out here, or show me some alternative way to implement annotations that can be toggled.
You could use a for loop or lapply. For example:
library(plotly)
a <- 1:10
b <- 1:10
text <- LETTERS[seq(1,10)]
data <- data.frame(a,b,text)
annotations = list()
for (i in 1:length(data[,1])) {
annotation <- list(x = data$a[i],
y = data$b[i],
text = data$text[i],
showarrow = TRUE)
annotations[[i]] <- annotation
}
updatemenus <- list(
list(
type= 'buttons',
buttons = list(
list(
label = "ON",
method = "update",
args = list(list(),
list(annotations = annotations))),
list(
label = "OFF",
method = "update",
args = list(list(),
list(annotations = list(c()))))
)
)
)
p <- plot_ly(data = data, x = ~a, y = ~b, type = "scatter", mode = "lines")
p <- layout(p, annotations = annotations, updatemenus = updatemenus)
p
Related
Is it possible to create an interactive scatter plot between two variables (selected by user from multiple variables) in R, without using shiny. An example is here using shiny. Is it possible to make such interactive plot without using shiny?(For example using Rmarkdown)
An example is here that use one button to select a variable using a button on plotly:
library(plotly)
df <- data.frame(x = 1:5, y = 7:11, z = 10:14)
create_buttons <- function(df, y_axis_var_names) {
lapply(
y_axis_var_names,
FUN = function(var_name, df) {
button <- list(
method = 'restyle',
args = list('y'
, list(df[, var_name]))
, label = sprintf('Show %s', var_name)
)
},
df
)
}
y_axis_var_names <- colnames(df)
p <- plot_ly(df, x = ~x, y = ~y, mode = "markers", name = "A", visible = T) %>%
layout(
title = "Drop down menus - Styling",
xaxis = list(title = "x"),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = create_buttons(df, y_axis_var_names)
)
))
p
But I do not know how to add a second button to the second variable!
I am trying to use a dropdown menu to plot a subsample of a dataset using the dropdown menu from plotly in R.
This is what I have so far (based on this answer) without sucess:
library(data.table)
library(ggplot2)
library(plotly)
X <- data.table(xcoord = 1:10, ycoord = 1:10)
Z <- X[xcoord < 5]
gg <- ggplot(X, aes(x = xcoord, y = ycoord)) + geom_point()
ggplotly(gg) %>%
layout(updatemenus = list(
list(buttons = list(
list(method = "restyle",
args = list(list("x", list(X$xcoord)),
list("y", list(X$xcoord))),
label = "X"),
list(method = "restyle",
args = list(list("x", list(Z$xcoord)),
list("y", list(Z$ycoord))),
label = "Z")
))
))
Found the solution: had to use named lists instead.
ggplotly(gg) %>%
layout(updatemenus = list(
list(buttons = list(
list(method = "restyle",
args = list(list(x = list(X$xcoord)),
list(y = list(X$xcoord))),
label = "X"),
list(method = "restyle",
args = list(list(x = list(Z$xcoord)),
list(y = list(Z$ycoord))),
label = "Z")
))
))
I've created a graph that lets you pick which group's data to plot. I'd like to change the title when you pick the group, but I'm not sure how or if its possible. I'm having trouble learning which way to structure lists for certain plotly parameters. Even if I could add custom text to graph would probably work.
#Working Example so Far
library(plotly)
x <- c(1:100)
random_y <- rnorm(100, mean = 0)
random_y_prim <- rnorm(100, mean = 50)
mydata <- data.frame(x, random_y, random_y_prim, group = rep(letters[1:4], 25))
# Make Group List Button
groupList <- unique(mydata$group)
groupLoop <- list()
for (iter in 1:length(groupList)) {
groupLoop[[iter]] <- list(method = "restyle",
args = list("transforms[0].value", groupList[iter]),
label = groupList[iter])
}
# Set up Axis labeling
f <- list(
family = "Verdana",
size = 18,
color = "#7f7f7f"
)
xLab <- list(
title = "x Axis",
titlefont = f
)
yLab <- list(
title = "y Axis",
titlefont = f
)
fig <- plot_ly(mydata, x = ~x, y = ~random_y
, type = 'scatter', mode = 'lines',
transforms = list(
list(
type = 'filter',
target = ~mydata$group,
operation = '=',
value = groupList[1]
)
)
)
fig <- fig %>%
layout(
title = "Updating Practice",
xaxis = xLab,
yaxis = yLab,
updatemenus = list(
list(
type = 'dropdown',xanchor = 'center',
yanchor = "top",
active = 1,
buttons = groupLoop
)
)
)
fig
I am trying to generate multiple graphs in Plotly for 30 different sales offices. Each graph would have 3 lines: sales, COGS, and inventory. I would like to keep this on one graph with 30 buttons for the different offices. This is the closest solution I could find on SO:
## Create random data. cols holds the parameter that should be switched
l <- lapply(1:100, function(i) rnorm(100))
df <- as.data.frame(l)
cols <- paste0(letters, 1:100)
colnames(df) <- cols
df[["c"]] <- 1:100
## Add trace directly here, since plotly adds a blank trace otherwise
p <- plot_ly(df,
type = "scatter",
mode = "lines",
x = ~c,
y= ~df[[cols[[1]]]],
name = cols[[1]])
## Add arbitrary number of traces
## Ignore first col as it has already been added
for (col in cols[-1]) {
p <- p %>% add_lines(x = ~c, y = df[[col]], name = col, visible = FALSE)
}
p <- p %>%
layout(
title = "Dropdown line plot",
xaxis = list(title = "x"),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
## Add all buttons at once
buttons = lapply(cols, function(col) {
list(method="restyle",
args = list("visible", cols == col),
label = col)
})
)
)
)
print(p)
It works but only on graphs with single lines/traces. How can I modify this code to do the same thing but with graphs with 2 or more traces? or is there a better solution? Any help would be appreciated!
### EXAMPLE 2
#create fake time series data
library(plotly)
set.seed(1)
df <- data.frame(replicate(31,sample(200:500,24,rep=TRUE)))
cols <- paste0(letters, 1:31)
colnames(df) <- cols
#create time series
timeseries <- ts(df[[1]], start = c(2018,1), end = c(2019,12), frequency = 12)
fit <- auto.arima(timeseries, d=1, D=1, stepwise =FALSE, approximation = FALSE)
fore <- forecast(fit, h = 12, level = c(80, 95))
## Add trace directly here, since plotly adds a blank trace otherwise
p <- plot_ly() %>%
add_lines(x = time(timeseries), y = timeseries,
color = I("black"), name = "observed") %>%
add_ribbons(x = time(fore$mean), ymin = fore$lower[, 2], ymax = fore$upper[, 2],
color = I("gray95"), name = "95% confidence") %>%
add_ribbons(x = time(fore$mean), ymin = fore$lower[, 1], ymax = fore$upper[, 1],
color = I("gray80"), name = "80% confidence") %>%
add_lines(x = time(fore$mean), y = fore$mean, color = I("blue"), name = "prediction")
## Add arbitrary number of traces
## Ignore first col as it has already been added
for (col in cols[2:31]) {
timeseries <- ts(df[[col]], start = c(2018,1), end = c(2019,12), frequency = 12)
fit <- auto.arima(timeseries, d=1, D=1, stepwise =FALSE, approximation = FALSE)
fore <- forecast(fit, h = 12, level = c(80, 95))
p <- p %>%
add_lines(x = time(timeseries), y = timeseries,
color = I("black"), name = "observed", visible = FALSE) %>%
add_ribbons(x = time(fore$mean), ymin = fore$lower[, 2], ymax = fore$upper[, 2],
color = I("gray95"), name = "95% confidence", visible = FALSE) %>%
add_ribbons(x = time(fore$mean), ymin = fore$lower[, 1], ymax = fore$upper[, 1],
color = I("gray80"), name = "80% confidence", visible = FALSE) %>%
add_lines(x = time(fore$mean), y = fore$mean, color = I("blue"), name = "prediction", visible = FALSE)
}
p <- p %>%
layout(
title = "Dropdown line plot",
xaxis = list(title = "x"),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
## Add all buttons at once
buttons = lapply(cols, function(col) {
list(method="restyle",
args = list("visible", cols == col),
label = col)
})
)
)
)
p
You were very close!
If for example you want graphs with 3 traces,
You only need to tweak two things:
Set visible the three first traces,
Modify buttons to show traces in groups of three.
My code:
## Create random data. cols holds the parameter that should be switched
library(plotly)
l <- lapply(1:99, function(i) rnorm(100))
df <- as.data.frame(l)
cols <- paste0(letters, 1:99)
colnames(df) <- cols
df[["c"]] <- 1:100
## Add trace directly here, since plotly adds a blank trace otherwise
p <- plot_ly(df,
type = "scatter",
mode = "lines",
x = ~c,
y= ~df[[cols[[1]]]],
name = cols[[1]])
p <- p %>% add_lines(x = ~c, y = df[[2]], name = cols[[2]], visible = T)
p <- p %>% add_lines(x = ~c, y = df[[3]], name = cols[[3]], visible = T)
## Add arbitrary number of traces
## Ignore first col as it has already been added
for (col in cols[4:99]) {
print(col)
p <- p %>% add_lines(x = ~c, y = df[[col]], name = col, visible = F)
}
p <- p %>%
layout(
title = "Dropdown line plot",
xaxis = list(title = "x"),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
## Add all buttons at once
buttons = lapply(0:32, function(col) {
list(method="restyle",
args = list("visible", cols == c(cols[col*3+1],cols[col*3+2],cols[col*3+3])),
label = paste0(cols[col*3+1], " ",cols[col*3+2], " ",cols[col*3+3] ))
})
)
)
)
print(p)
PD: I only use 99 cols because I want 33 groups of 3 graphs
I am not sure if this is possible, but here is what I would like to do. I would like to update the data in a plotly plot by selecting from a dropdown menu.
As a simple example, let's assume I have a data frame
df <- data.frame(x = runif(200), y = runif(200), z = runif(200))
from which I use df$x and df$y in a scatter plot. Two scenarios of data manipulation I would like to achieve using a dropdown:
Replace df$y with df$z
Plot only the first n values of df$x and df$y
I looked at the following two examples, which I can easily reproduce:
https://plot.ly/r/dropdowns/
However, I have no idea how to pass the information regarding the data to be plotted based on the dropdown selection. For scenario 2 e.g. I have tried it with args = list("data", df[1:n,]) which did not work.
For scenario 1 the (only?) way to go (according to the examples) seems to be hiding/showing the traces respectively. Is that the only way for scenario 2 as well?
Any alternative ideas?
Update 1: Add reproducible example
So here is an example which achieve what I would like in scenario 1.
require(plotly)
df <- data.frame(x = runif(200), y = runif(200), z = runif(200))
Sys.setenv("plotly_username"="xxx") #actual credentials replaced
Sys.setenv("plotly_api_key"="xxx") #actual credentials replaced
p <- plot_ly(df, x = df$x, y = df$y, mode = "markers", name = "A", visible = T) %>%
add_trace(mode = "markers", y = df$z, name = "B", visible = T) %>%
layout(
title = "Drop down menus - Styling",
xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = list(
list(method = "restyle",
args = list("visible", list(TRUE, TRUE)),
label = "Show All"),
list(method = "restyle",
args = list("visible", list(TRUE, FALSE)),
label = "Show A"),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = "Show B")))
))
plotly_POST(p)
Result here: https://plot.ly/~spietrzyk/96/drop-down-menus-styling/
This is based on the example from https://plot.ly/r/dropdowns/
However, I am wondering if one could pass the data to be plotted instead of triggering changes to the visible property of individual traces.
The one thing I tried was the following:
p <- plot_ly(df, x = df$x, y = df$y, mode = "markers", name = "A", visible = T) %>%
layout(
title = "Drop down menus - Styling",
xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = list(
list(method = "restyle",
args = list("y", df$y),
label = "Show A"),
list(method = "restyle",
args = list("y", df$z),
label = "Show B")))
))
Result here: https://plot.ly/~spietrzyk/98/drop-down-menus-styling/
This approach cannot work, as the data from df$z is not posted to the grid (https://plot.ly/~spietrzyk/99/).
So I was wondering is there anyway to manipulate the data to be plotted based on dropdown selection, beyond plotting all traces and than switching the visible property by dropdown selections.
Is this what you were after?
require(plotly)
df <- data.frame(x = runif(200), y = runif(200), z = runif(200))
p <- plot_ly(df, x = ~x, y = ~y, mode = "markers", name = "A", visible = T) %>%
layout(
title = "Drop down menus - Styling",
xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = list(
list(method = "restyle",
args = list("y", list(df$y)), # put it in a list
label = "Show A"),
list(method = "restyle",
args = list("y", list(df$z)), # put it in a list
label = "Show B")))
))
p
On the top of #jimmy G's answer.
You can automatically create the buttons so that you don't have to manually specify every single variable you want in the plot.
library(plotly)
df <- data.frame(x = runif(200), y = runif(200), z = runif(200), j = runif(200), k = rep(0.7, 200), i = rnorm(200,0.6,0.05))
create_buttons <- function(df, y_axis_var_names) {
lapply(
y_axis_var_names,
FUN = function(var_name, df) {
button <- list(
method = 'restyle',
args = list('y', list(df[, var_name])),
label = sprintf('Show %s', var_name)
)
},
df
)
}
y_axis_var_names <- c('y', 'z', 'j', 'k', 'i')
p <- plot_ly(df, x = ~x, y = ~y, mode = "markers", name = "A", visible = T) %>%
layout(
title = "Drop down menus - Styling",
xaxis = list(domain = c(0.1, 1)),
yaxis = list(title = "y"),
updatemenus = list(
list(
y = 0.7,
buttons = create_buttons(df, y_axis_var_names)
)
))
p
Hope you find it useful.