I wish to add scatterplots to an existing 3D scatterplot in R using plot_ly.
I am generating data from Normal distribution of length 219. Then I want to plot and add scatter plots corresponding to the indices 80, 150 and 195 of the variables on the same graph with a different color (red in my case).
I used the following codes -
library(plotly)
index <- c(80, 150, 195)
set.seed(4991)
data1 <- rnorm(219,9,1.5)
data2 <- rnorm(219,2,1)
timeline <- 1:length(data1)
plot_ly(x=data1, y=data2, z=timeline, type="scatter3d", mode="markers")%>%
layout(scene = list(xaxis = list(title = 'cases per day'),
yaxis = list(title = 'deaths per day'),
zaxis = list(title = 'observation #')))%>%
add_trace(x=data1[index],y=data2[index],z=timeline[index], type="scatter3d", mode = "markers", marker = list(size = 5, color = "red", symbol = 104))
Snapshot of the output looks like this -
However if I use the color=timeline option in the plot_ly section,
plot_ly(x=data1, y=data2, z=timeline, type="scatter3d", mode="markers",color=timeline)%>%
layout(scene = list(xaxis = list(title = 'cases per day'),
yaxis = list(title = 'deaths per day'),
zaxis = list(title = 'observation #')))%>%
add_trace(x=data1[index],y=data2[index],z=timeline[index], type="scatter3d", mode = "markers", marker = list(size = 5, color = "red", symbol = 104))
I get the following error
Error:
! Tibble columns must have compatible sizes.
• Size 3: Columns `x`, `y`, and `z`.
• Size 219: Column `color`.
ℹ Only values of size one are recycled.
Run `rlang::last_error()` to see where the error occurred.
I want to plot the 3D scatterplot with color=timeline option and then add the scatterplot in red.
Any help is appreciated.
The variable timeline is all unique values, which doesn't align with your desire to have the three values colored. What you need is a grouping variable (i.e., yes or no, a or b, etc.)
I made a control.
timeline1 <- rep("A", length(data1))
timeline1[index] <- "B"
summary(timeline1 %>% as.factor())
# A B
# 216 3
Then I made my graph. One trace- with specific colors designated. I used Plotly's blue to keep it consistent with your question.
# '#1f77b4' is the Plotly blue (muted blue)
plot_ly(x = data1, y = data2, z = timeline, type = "scatter3d", mode = "markers",
color = timeline1, colors = setNames(c('#1f77b4', "red"), nm = c("A", "B"))) %>%
layout(scene = list(xaxis = list(title = 'cases per day'),
yaxis = list(title = 'deaths per day'),
zaxis = list(title = 'observation #')))
Related
I try to plot a 3d scatterplot with plotly in R with overall 12 groups and cannot find out how to use 12 different symbols and colours.
palette <- distinctColorPalette(12)
pie(rep(1, 12), col=palette)
library(plotly)
fig <- plot_ly(data, x = ~Length..mm., y = ~Width..mm., z = ~Height..mm.,
color = ~spec, colors = palette, symbol =~spec, symbols = ~spec)
fig <- fig %>% layout(scene = list(xaxis = list(title = 'Seed length (mm)'),
yaxis = list(title = 'Seed width (mm)'),
zaxis = list(title = 'Seed heigth (mm)'))
I really appreciate any help you can provide.
this is the output
I have a data.frame of regression coefficients with the associated p-values:
library(dplyr)
set.seed(1)
effects.df <- data.frame(contrast = paste0("C",1:5), effect = rnorm(5), stringsAsFactors = F) %>%
dplyr::mutate(effect.error = abs(effect)/sqrt(5)) %>%
dplyr::mutate(p.value = pnorm(effect/effect.error)) %>%
dplyr::arrange(p.value)
effects.df$contrast <- factor(effects.df$contrast,levels = effects.df$contrast)
Which I want to display as a forest plot (X-axis are the effect size and Y-axis are the 'contrast's), where the points and their associated error bars (effect.error) are color coded by 1-p.value, using R's plotly.
Here's what I'm trying:
library(plotly)
effects.plot <- plot_ly(x = effects.df$effect, y = effects.df$contrast, type = 'scatter', mode = "markers", marker = list(size = 8, colorbar = "Hot", color = 1-effects.df$p.value)) %>%
layout(xaxis=list(title = "Effect size",zerolinewidth = 2, zerolinecolor = plotly::toRGB('black'), showgrid = F), yaxis = list(showgrid = F)) %>%
add_trace(error_x = list(array = effects.df$effect.error, width = 5),marker = list(size = 8,colorbar = "Hot", color = 1-effects.df$p.value))
It's close because it's color-coding the points how I want them to but not the error bars.
Any idea how to:
Color the error bars similar to the points?
Get the color-bar to show?
I'm not sure that it will allow you to color the error bars separately without some (a lot) of creativity. If you created separate traces for each color, you might be able to force it to comply.
There are many ways you could show the color bar. Here's one way:
(effects.plot <- plot_ly(data = effects.df,
x = ~effect,
y = ~contrast,
error_x = list(array = ~effect.error,
width = 5,
color = "black"),
type = 'scatter',
mode = "markers",
marker = list(colorscale = "Hot",
colorbar = list(size = 8),
color = 1 - effects.df$p.value)) %>%
layout(xaxis=list(title = "Effect size",
zerolinewidth = 2,
zerolinecolor = plotly::toRGB('black'),
showgrid = F),
yaxis = list(showgrid = F)) # set the joined color axis
)
By the way, I noticed that the colors you have are gray and red, not black and white, as shown in my image. You're getting a different color scale than you were expecting.
You can see what I mean by plotting this a different way:
(effects.plot <- plot_ly(data = effects.df,
x = ~effect,
y = ~contrast,
error_x = list(array = ~effect.error,
width = 5,
color = "black"),
type = 'scatter',
mode = "markers",
marker = list(coloraxis = "coloraxis",
color = 1 - effects.df$p.value)) %>%
layout(xaxis=list(title = "Effect size",
zerolinewidth = 2,
zerolinecolor = plotly::toRGB('black'),
showgrid = F),
yaxis = list(showgrid = F),
coloraxis = list(colorbar = "Hot", size = 8))
)
This plot is not using the "Hot" color scale. That scale is shown in the first image.
The easiest way to solve this is to use ggplot2 and then to convert it to a plotly object:
Libraries and data:
library(dplyr)
library(plotly)
library(ggplot2)
set.seed(1)
effects.df <- data.frame(contrast = paste0("C",1:5), effect = rnorm(5), stringsAsFactors = F) %>%
dplyr::mutate(effect.error = abs(effect)/sqrt(5)) %>%
dplyr::mutate(p.value = pnorm(effect/effect.error)) %>%
dplyr::arrange(p.value)
Here I also add a horizontal dashed y-line to mark the p-value = 0.05 cutoff:
effects.df$contrast <- factor(effects.df$contrast,levels=effects.df$contrast)
y.intercept <- min(which(effects.df$p.value > 0.05))-0.5
pp <- ggplot(effects.df)+geom_vline(xintercept=0,color="black")+geom_point(aes(y=contrast,x=effect,color=p.value))+
geom_errorbarh(aes(y=contrast,xmin=effect-effect.error,xmax=effect+effect.error,x=effect,color=p.value,height=0.1))+
scale_color_continuous(low="darkred",high="gray")+theme_minimal()+xlab("Effect Size")+
geom_hline(yintercept=y.intercept,linetype="dashed",color="black",size=0.25)
Which gives:
And the plotly object:
ggplotly(pp)
This question already has answers here:
Horizontal/Vertical Line in plotly
(4 answers)
Closed 2 years ago.
I would like to add a vertical line on a special date to my plot. I am using the plot_ly() function from the plotly package in R.
p <- plot_ly(dt.allDataFvsS, x = dt.allDataFvsS$date, y = dt.allDataFvsS$meanDifference, mode = 'lines',
type = "scatter", line = list(color = " #007d3c")) %>%
layout(title = "Average Price Difference Forward vs. Spot", xaxis = list(title = "Date"),
yaxis = list(title = "EUR / MWh"))
The date has the following form: e.g. "2018-10-01" ("Y-M-D")
My plot looks like this:
PLOT
So, my question is how do I get a black vertical line at date "2018-10-01" ?
Is it also possible to have vertical lines at the beginning of each year? Or of every quarter (Jan - Apr - Jul - Oct) of each year?
I would be very happy if someone could help me? Unfortunately, after a day of browsing the internet, I couldn't find anything that worked.
As no data is provided to reproduce your issue, I would suggest next approach using add_trace() function where you define the coordinates for the line:
p <- plot_ly(dt.allDataFvsS, x = dt.allDataFvsS$date, y = dt.allDataFvsS$meanDifference, mode = 'lines',
type = "scatter", line = list(color = " #007d3c")) %>%
add_trace(x =as.Date("2018-10-01"),type = 'scatter', mode = 'lines',
line = list(color = 'black'),name = '') %>%
layout(title = "Average Price Difference Forward vs. Spot", xaxis = list(title = "Date"),
yaxis = list(title = "EUR / MWh"))
Let me know if that works!
Here is another approach based on shapes rather than adding another trace (you can see the difference when zooming out + there is no legend item for the vertical line):
library(plotly)
dates <- seq(from = as.Date("2018-08-01"), to = as.Date("2018-12-31"), by = 1)
dt.allDataFvsS <- data.frame(date = dates, meanDifference = sin(seq_along(dates)*0.1))
vline <- function(x = 0, color = "red") {
list(
type = "line",
y0 = 0,
y1 = 1,
yref = "paper",
x0 = x,
x1 = x,
line = list(color = color)
)
}
p <- plot_ly(dt.allDataFvsS, x = dt.allDataFvsS$date, y = dt.allDataFvsS$meanDifference, mode = 'lines',
type = "scatter", line = list(color = " #007d3c")) %>%
layout(title = "Average Price Difference Forward vs. Spot", xaxis = list(title = "Date"),
yaxis = list(title = "EUR / MWh"))
p %>% layout(shapes = list(vline(as.Date("2018-10-01"))))
Based on this answer.
I have some data like this:
data <- data.frame(x=runif(500), y=runif(500), z=runif(500))
I want a scatterplot with points colored independently/discretely in each dimension (X, Y, and Z) using RGB values.
This is what I have tried:
Code:
library(dplyr)
library(plotly)
xyz_colors <- rgb(data$x, data$y, data$z)
plot_ly(data = data,
x = ~x, y = ~y, z = ~z,
color= xyz_colors,
type = 'scatter3d',
mode='markers') %>%
layout(scene = list(xaxis = list(title = 'X'),
yaxis = list(title = 'Y'),
zaxis = list(title = 'Z')))
Plot:
RColorBrewer thinks I'm trying to create a continuous scale from 500 intermediate colors:
Warning messages:
1: In RColorBrewer::brewer.pal(N, "Set2") :
n too large, allowed maximum for palette Set2 is 8
Returning the palette you asked for with that many colors
2: In RColorBrewer::brewer.pal(N, "Set2") :
n too large, allowed maximum for palette Set2 is 8
Returning the palette you asked for with that many colors
What are some correct ways to color the points like this in R with Plotly?
Also, how can one generally assign colors to data points in R with Plotly, individually?
To clarify, I am trying to color each point where the color is of the format "#XXYYZZ" where 'XX' a value between 00 and FF linearly mapped to the value of data$x from 0 to 1. That is, the X dimension determines the amount of red, the Y dimension determines the amount of green, and the Z dimension determines the amount of blue. At 0,0,0 the point should be black and at 1,1,1 the point should be white. The reason for this is to make as easy to visualize the 3D position of the points as possible.
Updated answer after comments:
So, is there no way to color every point separately?
Yes, there is through the power and flexibility of add_traces(). And it's a lot less cumbersome than I first thought.
Just set up an empty plotly figure with some required 3D features:
p <-plot_ly(data = data, type = 'scatter3d', mode='markers')
And apply add_traces() in a loop over each defined color:
for (i in seq_along(xyz_colors)){
p <- p %>% add_trace(x=data$x[i], y=data$y[i], z=data$z[i],
marker = list(color = xyz_colors[i], opacity=0.6, size = 5),
name = xyz_colors[i])
}
And you can easily define single points with a color of your choice like this:
p <- p %>% add_trace(x=0, y=0, z=0,
marker = list(color = rgb(0, 0, 0), opacity=0.8, size = 20),
name = xyz_colors[i])
Plot:
Complete code:
library(dplyr)
library(plotly)
# data and colors
data <- data.frame(x=runif(500), y=runif(500), z=runif(500))
xyz_colors <- rgb(data$x, data$y, data$z)
# empty 3D plot
p <-plot_ly(data = data, type = 'scatter3d', mode='markers') %>%
layout(scene = list(xaxis = list(title = 'X'),
yaxis = list(title = 'Y'),
zaxis = list(title = 'Z')))
# one trace per color
for (i in seq_along(xyz_colors)){
p <- p %>% add_trace(x=data$x[i], y=data$y[i], z=data$z[i],
marker = list(color = xyz_colors[i], opacity=0.6, size = 5),
name = xyz_colors[i])
}
# Your favorite data point with your favorite color
p <- p %>% add_trace(x=0, y=0, z=0,
marker = list(color = rgb(0, 0, 0), opacity=0.8, size = 20),
name = xyz_colors[i])
p
Original answer:
In 3D plots you can use the same color for all of the points, discern different clusters or categories from each other using different colors, or you use individual colors for each point to illustrate a fourth value (or fourth dimension if you like, as described here) in your dataset. All these approaches are, as you put it, examples of '[...] correct ways to color the points [...]'. Have a look below and see if this suits your needs. I've included fourthVal <- data$x+data$y+data$z as an example for an extra dimension. What you end up using will depend entirely on your dataset and what you'd like to illustrate.
Code:
library(dplyr)
library(plotly)
data <- data.frame(x=runif(500), y=runif(500), z=runif(500))
xyz_colors <- rgb(data$x, data$y, data$z)
fourthVal <- data$x+data$y+data$z
plot_ly(data = data,
x = ~x, y = ~y, z = ~z,
color= fourthVal,
type = 'scatter3d',
mode='markers') %>%
layout(scene = list(xaxis = list(title = 'X'),
yaxis = list(title = 'Y'),
zaxis = list(title = 'Z')))
Plot:
I'm trying to overlay a line chart and bar chart in plotly (with a vertical line designating an important date) and I'm encountering this issue where the two zero lines are offset instead of on the same line. I've tried messing around with the overlaying = 'y' option within layout and tried changing the order of the three trace components but nothing seems to help. Any ideas how to fix? Below is my code with dummy data:
(Also, bonus points if you can fix my legend-overlapping-y2axis issue)
date <- seq(as.Date("2015/6/1"), by = "month", length.out = 19)
wires_mnth <- c(rep(0,8),100000,750000,1200000,2500000,3100000,5500000,7500000,8000000,9900000,11300000,11000000)
wires_cnt <- c(rep(0,8),100,200,250,325,475,600,750,800,1000,1150,1200)
data <- data.frame(date, wires_mnth)
plot_ly(data) %>%
add_trace(x = ~date, y = ~wires_cnt, type = 'bar', name = 'Wires Count',
yaxis = 'y2', opacity = .5) %>%
add_trace(x = ~date, y = ~wires_mnth, type = 'scatter', mode = 'lines', name
= 'Monthly Wires') %>%
add_trace(x = c(2016,2016), y = c(0, 12000000), type = 'scatter', mode =
"lines", name = 'Sanctions Removed') %>%
layout(title = 'Monthly Aggregate Wire Transfers to Iran',
xaxis = list(title = ''),
yaxis = list(side = 'left', title = 'Wire Amounts (USD)', showgrid =
FALSE, zeroline = FALSE),
yaxis2 = list(side = 'right', overlaying = 'y', title = 'Wires Count',
showgrid = FALSE, zeroline = FALSE)
)
You could add rangemode='nonnegative' to your layout or specify the range manually via range=list(0, max(wires_mnth).
For your bonus question, you can set the x-position of the legend, e.g.
legend = list(x = 1.2)