df <- data.frame(X1 = rep(1:5,1), X2 = rep(4:8,1), var1 = sample(1:10,5), row.names = c(1:5))
library("ggvis")
graph <- df %>%
ggvis(~X1) %>%
layer_lines(y = ~ var1) %>%
add_axis("y", orient = "left", title = "var1") %>%
add_axis("x", orient = "bottom", title = "X1") %>%
add_axis("x", orient = "top", title = "X2" )
graph
Obviously, the top x-axis (X2) is not correct here since it refers to the same variable as X1. I know how to create a scaled dual-y axis in ggvis. But how can I create a similar dual axis on different X? Those two X-axis should refer to different variables (X1 and X2 in this example).
I know this could be a really BAD idea to make dual X-axis. But one of my working dataset may need me to do so. Any comments and suggestions are appreciated!
The second axis needs to have a 'name' in order for the axis to know which variable to reflect. See below:
df <- data.frame(X1 = rep(1:5,1),
X2 = rep(4:8,1),
var1 = sample(1:10,5),
row.names = c(1:5))
library("ggvis")
df %>%
ggvis(~X1) %>%
#this is the line plotted
layer_lines(y = ~ var1) %>%
#and this is the bottom axis as plotted normally
add_axis("x", orient = "bottom", title = "X1") %>%
#now we add a second axis and we name it 'x2'. The name is given
#at the scale argument
add_axis("x", scale = 'x2', orient = "top", title = "X2" ) %>%
#and now we plot the second x-axis using the name created above
#i.e. scale='x2'
layer_lines(prop('x' , ~X2, scale='x2'))
And as you can see the top x-axis reflects your X2 variable and ranges between 4 and 8.
Also, as a side note: You don't need rep(4:8,1) to create a vector from 4 to 8. Just use 4:8 which returns the same vector.
Related
I am trying to plot two series at different scales on same plot with dygraph lib in r.
dygraph(data.frame(x = 1:10, y = runif(10),y2=runif(10)*100)) %>%
dyAxis("y", valueRange = c(0, 1.5)) %>%
dyAxis(runif(10)*100,name="y2", valueRange = c(0, 100)) %>%
dyEvent(2, label = "test") %>%
dyAnnotation(5, text = "A")
however, The plot does not fit the data with larger scale, I cannot figure out how to align the two axises. I suspect the option independentTicks in dyAxis() function does the trick but I cannot find how to use it in the documentation. Please help out with this. Best
One way could be:
We pass the named vector of the column with higher values to dySeries function:
See here https://rstudio.github.io/dygraphs/gallery-axis-options.html
library(dygraphs)
library(dplyr)
df = data.frame(x = 1:10, y = runif(10),y2=runif(10)*100)
y2 <- df %>%
pull(y2)
names(y2) <- df$x
dygraph(df) %>%
dySeries("y2", axis = 'y2')
I would like to declutter a plot created with plotly and remove the repetitions of the year on the x-axis. The year should be shown only for the first month. For the rest of the labels the month (without the year) is enough.
I have tried to achieve this result with the ifelse function - without success (see reproducible example below). Is there any way to use ifelse or if_else to set the axis labels in plotly? I think it works that way in ggplot.
library(tidyverse)
library(plotly)
set.seed(42)
df <-
data.frame(date = seq(ymd('2021-01-01'), ymd('2021-12-12'), by = 'weeks'),
value = cumsum(sample(-10:20, length(seq(ymd('2021-01-01'), ymd('2021-12-12'), by = 'weeks')), replace = TRUE)))
df %>%
plot_ly(x = ~date, y = ~value) %>%
add_lines() %>%
layout(xaxis = list(dtick = "M1", tickformat = ~ifelse(date <= "2021-01-31", "%b\n%Y", "%b")))
i have this small dataset that i need to plot with plotly. Im struggling with it :/
Im looking to have 3 colored lines (each line for each of the rows (1,2,3). The x axis needs to be the column names and the Y axis represents each one of the numeric values.
My code so far looks wrong
plot_ly (x = colnames(a), y = a[1], type = "scatter" ,mode = "lines" )
I'm not sure that this is your desired plot, but it sounded closest to your description. I adapted a few columns of your data to describe.
The plot will be easier if data is in longer form with pivot_longer. Also easier if you add row numbers to your data so you can plot one line for each row number.
Since plotly will plot your xaxis categories alphabetically, you will want to relevel your name factor (name is your column names) to order of your columns.
In your plot_ly statement, use split to plot by row number.
library(plotly)
library(tidyverse)
a %>%
mutate(rn = row_number()) %>%
pivot_longer(cols = -rn, names_to = "name", values_to = "value") %>%
mutate(name = factor(name, levels = colnames(a))) %>%
plot_ly(x = ~name, y = ~value, split = ~rn, type = "scatter", mode = "lines")
Output
Data
a <- data.frame(
N_of_Brands = c(-.4, .8, -.4),
Brand_Runs = c(-.26, .70, -.75),
Total_Volume = c(-.69, .15, -.015),
No_of_Trans = c(-.81, .45, -.35)
)
I am looking to add a dropdown feature to a plotly graph which will highlight a chosen id variable and will make the selected id's line change to a different color. An example of a code to produce the type of chart I'm considering is
library(tidyverse)
library(plotly)
set.seed(2001)
## make 10 random data series
data <- data.frame(
t = rep(1:50, 10),
id = sort(rep(1:10, 50)),
y = rnorm(500)
)
## cumulate the random variates by group
data <- data %>%
group_by(id) %>%
mutate(y2 = cumsum(y))
## plot
plot <- data %>%
plot_ly(x = ~ t, y = ~y2, text = ~id) %>%
add_lines(split = ~id, color = I('gray'), alpha = 0.5) %>%
hide_legend()
plot
What I'm looking to do is create a drop down selection choice so that I can select say id = 3, and change that line corresponding to id = 3 to blue, keeping all others as gray. I found how to change overall styles with dropdowns, but couldn't find this specific question. Thanks in advance.
Andrew
EDIT: Sample code updated with more complex example
I have a data frame with (x, y) values and a name for each pair, and I'm plotting it in a ggvis scatterplot. SO users already pointed me to this post (How do I label plot tick marks using ggvis) and I updated my code to reflect what I saw there by using factor() to create the list of custom y-axis labels ylabels_ which is fed to values = under the add_axis() statement. Here is the new code:
library(stringi)
require(ggvis)
set.seed(13)
df <- data.frame(x = 1:15,
y = c(rep.int(1, 15),
rep.int(4, 15),
rep.int(7, 15)))
ylabels_ <- factor(c(1,4,7), labels = stri_rand_strings(3, 7))
df %>%
ggvis(~x, ~y) %>%
add_axis("y", values = ylabels_)
My axis labels are still coming back with NaN instead of the factors. Am I missing something?
SOLUTION EDIT: Here is my code that I finally got to work. Note I changed the x values to be staggered so I could distinguish between the three lines.
library(stringi)
require(ggvis)
set.seed(13)
df <- data.frame(x = c(seq(1, length.out = 15, by = 3),
seq(2, length.out = 15, by = 3),
seq(3, length.out = 15, by = 3)),
y = factor(c(rep.int(1, 15),
rep.int(4, 15),
rep.int(7, 15)), labels = c("one", "four", "seven"),
ordered = T))
df %>%
ggvis(~x, ~y) %>%
layer_points() %>%
scale_ordinal("y", domain = c("seven", "four", "one")
I don't understand why in the domain = portion I had to reverse the order of the factors for them to show in the correct order. If anyone has any insight on that, it would be very helpful!
Notice that in the linked answer, the new factor variable is used as the y variable. You can use it for your values, as well, but it's not necessarily needed.
Making the new factor based on y but using name as the labels is to get the name variable in the correct order for plotting.
df$ylabels_ <- factor(df$y, labels = stri_rand_strings(3, 7))
Because you are now working with a factor variable on the y axis, layer_points needs to be used explicitly.
df %>%
ggvis(~x, ~ylabels_) %>%
layer_points()
Note that this whole approach will only work if the original y data are integers.
Call me a fool, but I'm calling this a bug (which, BTW, is not answering your question):
## set up data
lab <- factor(1:15, labels=stri_rand_strings(15, 7))
val <- 1:15
## all works according to expectations on the "x" axis
data.frame(xx=lab, yy=val) %>%
ggvis(~xx, ~yy) %>%
layer_points() %>%
add_axis("x", values=lab,
properties=axis_props(labels=list(angle=90, fontSize = 10)))
## nothing works according to expectations on the "y" axis
## attempt 1
data.frame(xx=val, yy=lab) %>%
ggvis(~xx, ~yy) %>%
layer_points() %>%
add_axis("y", values=lab,
properties=axis_props(labels=list(angle= 0, fontSize = 10)))
## attempt 2
data.frame(xx=val, yy=as.numeric(val)) %>%
ggvis(~xx, ~yy) %>%
layer_points() %>%
add_axis("y", values=lab,
properties=axis_props(labels=list(angle= 0, fontSize = 10)))