I made this pie chart in R:
# https://plotly.com/r/text-and-annotations/
df <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv", stringsAsFactors = FALSE)
df <- df[which(df$year==2007 & df$continent=='Asia'),]
fig <- plot_ly(df, type='pie', labels = ~country, values = ~pop, textposition = 'inside')
fig1 <- fig %>% layout(uniformtext=list(minsize=12, mode='hide'))
fig1 <- fig1 %>% add_annotations(
y=1.05,
x=0.5,
text="Countries of the World",
showarrow=F,
font=list(size=15)
)
Everything works fine here, but I notice that when I am working with my real data, the title of the pie chart and the actual pie chart always come very close to intersecting with each other - I would like to try and change this.
I was thinking if there might be a way to avoid this problem. I thought that perhaps I could add more space between the title and the actual pie chart to avoid this problem from happening. I found this post here (how to adjust title space and plot plotly in r) and tried to apply the advice that was suggested in the answer:
mrg <- list(l = 50, r = 50,
b = 50, t = 50,
pad = 20)
fig1 %>% layout(margin = mrg)
However, this has not seemed to add any space between the pie chart and the title of the pie chart.
Can someone please show me how to do this correctly?
Thank you!
Here is one option making use of layout for the title and adjusting the spacing. Then, you can just adjust the margins to get the desired spacing.
library(plotly)
plot_ly(df, type='pie', labels = ~country, values = ~pop, textposition = 'inside') %>%
layout(uniformtext=list(minsize=12, mode='hide')) %>%
layout(title = list(text = 'Countries of the World',
y=1.25,
x=0.43, font=list(size = 30)),
autosize = T,
margin=list( l = 50, r = 50, b = 100, t = 100, pad = 4))
Output
Related
I am outputting a scatterplot in R using plotly with the code below:
library(tidyverse)
library(plotly)
set.seed(1)
data.frame(state = c(rep(state.name, 2)),
value = sample(1:100, 100)) %>%
plot_ly(x = ~value,
y = ~state,
type = "scatter",
mode = "markers") %>%
layout(title = list(text = "State Information"))
The issue that I am running into is that the code above renders a plot with an excessive amount of space between the y-axis and the plot title and x-axis ticks respectively:
Can anyone tell me how I can shrink this space so that the plot margins are tighter?
Edit: I know that a similar question was asked here, but this relates to a numeric y-axis, not a categorical one:
R Plotly - Large unused space on top and bottom of graph when setting height
We can use the same procedure for a categorical axis.
Please run schema() and navigate: object ► layout ► layoutAttributes ► yaxis ► range:
[...] If the axis type is category, it should be numbers, using
the scale where each category is assigned a serial number from zero in
the order it appears.
library(plotly)
library(datasets)
set.seed(1)
DF <- data.frame(state = c(rep(state.name, 2)),
value = sample(1:100, 100))
plot_ly(
data = DF,
x = ~ value,
y = ~ state,
type = "scatter",
mode = "markers"
) %>%
layout(
title = list(text = "State Information"),
xaxis = list(
range = ~ c(-1, length(unique(value)) + 1)
),
yaxis = list(
range = ~ c(-1, length(unique(state))),
title = list(text = "state", standoff = 0L)) # maybe needed? sets distance between title and labels
)
I am using plot_ly in R to create a line chart. By default, the line runs right up to the left and right edges of the plot area. I would like to add some space here, as is done by default in ggplot. Does anyone know how to do this with plot_ly?
Reproducible example:
df <- data.frame(date = seq(as.Date('2021-01-01'), length=50, by='day'),
value = rnorm(50))
plot_ly(df, x=~date, y=~value) %>%
add_lines(color=I('black')) %>%
layout(title = 'plot_ly', plot_bgcolor = 'E9E9E9')
ggplot(df, aes(x=date, y=value)) +
geom_line() +
ggtitle('ggplot')
I would like to add the space shown below with red arrows:
You can set the range in xaxis :
library(plotly)
plot_ly(df, x=~date, y=~value) %>%
add_lines(color=I('black')) %>%
layout(title = 'plot_ly', plot_bgcolor = 'E9E9E9',
xaxis = list(range = c(min(df$date) - 3, max(df$date) + 3)))
I'm looking to see if there's a way to change the order of the hoverlabels when using hovermode = "x unified" in the newest version of the R package of plotly (4.9.3). Alternatively, is it possible to revert back to the way the old version of plotly displayed the hoverlabels while still using the current version of the plotly package? From a data visualization perspective, the old way is much clearer in my opinion.
I've included a minimum reproducible example below. When I run this using plotly v4.9.2.1, I get the result shown in Figure A and when I run it in plotly v4.9.3, I get the result shown in Figure B. The benefits to Figure A over Figure B are:
Figure A labels are in descending order relative to the data on each line at the time specified. Also this is reactive to the time period, so if one line moves above another at a different time period, the relative positioning of the label also moves to reflect the ordering of the data. You can see in Figure B that the dark green (y1) line has the lowest value (66) yet it is shown at the top of the hoverlabel box. In figure B, the y1 label is at the bottom.
Figure A labels are attached to the individual lines, so its easier to see the hovertext as it applies to the line in question
Figure A:
Figure B:
Code:
library(plotly)
library(tidyr)
df <- data.frame(Date = seq(as.Date("2018-01-01"),
as.Date("2021-01-01"),
by = "months"),
stringsAsFactors = F)
df$y1 <- seq(0, 100, length.out = nrow(df))
df$y2 <- seq(0, 600, length.out = nrow(df))
df$y3 <- seq(0, 300, length.out = nrow(df))
df$y4 <- seq(0, 200, length.out = nrow(df))
df <- df %>%
pivot_longer(cols = -Date,
names_to = "yname",
values_to = ) %>%
arrange(yname, Date)
mycols <- c("#006633", "#70AD47", "#1F4E78", "#2F75B5", "#C65911", "#EF8C4F",
"#C00000", "#FF8B8B", "#7030A0", "#9966FF")
mycols <- mycols[1:length(unique(df$yname))]
p <- plot_ly()
p <- p %>%
add_trace(data = df,
x = ~Date,
y = ~value,
text = ~yname,
hovertemplate = paste('<b>%{text}</b>',
'<br>%{x}',
'<br>%{y}',
'<extra></extra>'),
color = ~yname, colors = mycols,
name = ~yname, yaxis = "y",
type = "scatter", mode = "lines",
showlegend = T)
p <- p %>%
layout(hovermode = "x unified",
legend = list(x = 1.12, y = .5, xanchor = "left"),
yaxis = list(fixedrange = T),
xaxis = list(title = "",
fixedrange = T,
hoverformat = "%b %d, %Y"),
showlegend = T)
p
Two answers:
the ordering of traces in the unified hoverlabel is always the same, regardless of the relative Y values of the traces. The order is the same as in the legend, so it will follow the ordering of the colors.
You can revert to the previous behavior with hovermode = "x" rather than hovermode = "x unified"
Probably an easy one.
I have an xy dataset I'd like to plot using R's plotly. Here are the data:
set.seed(1)
df <- data.frame(x=1:10,y=runif(10,1,10),group=c(rep("A",9),"B"),group.size=as.integer(runif(10,1,10)))
I'd like to color the data by df$group and have the size of the points follow df$group.size (i.e., a bubble plot). In addition, I'd like to have both legends added.
This is my naive attempt:
require(plotly)
require(dplyr)
main.plot <-
plot_ly(type='scatter',mode="markers",color=~df$group,x=~df$x,y=~df$y,size=~df$group.size,marker=list(sizeref=0.1,sizemode="area",opacity=0.5),data=df,showlegend=T) %>%
layout(title="Title",xaxis=list(title="X",zeroline=F),yaxis=list(title="Y",zeroline=F))
which comes out as:
and unfortunately messes up the legend, at least how I want it to be: a point for each group having the same size but different colors.
Then to add a legend for the group.size I followed this, also helped by aocall's answer:
legend.plot <- plot_ly() %>% add_markers(x = 1, y = unique(df$group.size),
size = unique(df$group.size),
showlegend = T,
marker = list(sizeref=0.1,sizemode="area")) %>%
layout(title="TITLE",xaxis = list(zeroline=F,showline=F,showticklabels=F,showgrid=F),
yaxis=list(showgrid=F))
which comes out as:
Here my problem is that the legend is including values that do not exist in my data.
then I combine them using subplot:
subplot(legend.plot, main.plot, widths = c(0.1, 0.9))
I get this:
where the legend title is eliminated
So I'd be helpful for some help.
Based on the updated request:
Note the changes in legend.plot (mapping values to a sequence of integers, then manually changing the axis tick text), and the use of annotations to get a legend title. As explained in this answer, only one title may be used, regardless of how many subplots are used.
The circle on the plot legend seems to correspond to the minimum point size of each trace. Thus, I've added a point at (12, 12), and restricted the range of the axes to ensure it isn't shown.
titleX and titleY control the display of axis labels, as explained here.
set.seed(1)
df <- data.frame(x=1:10,y=runif(10,1,10),group=c(rep("A",9),"B"),group.size=as.integer(runif(10,1,10)))
require(plotly)
require(dplyr)
## Take unique values before adding dummy value
unique_vals <- unique(df$group.size)
df <- rbind(c(12, 12, "B", 1), df)
df[c(1, 2, 4)] <- lapply(df[c(1, 2, 4)], as.numeric)
main.plot <-
plot_ly(type='scatter',
mode="markers",
color=~df$group,
x=~df$x,
y=~df$y,
size=~df$group.size,
marker=list(
sizeref=0.1,
sizemode="area",
opacity=0.5),
data=df,
showlegend=T) %>%
layout(title="Title",
xaxis=list(title="X",zeroline=F, range=c(0, 11)),
yaxis=list(title="Y",zeroline=F, range=c(0, 11)))
legend.plot <- plot_ly() %>%
add_markers(x = 1,
y = seq_len(length(unique_vals)),
size = sort(unique_vals),
showlegend = F,
marker = list(sizeref=0.1,sizemode="area")) %>%
layout(
annotations = list(
list(x = 0.2,
y = 1,
text = "LEGEND TITLE",
showarrow = F,
xref='paper',
yref='paper')),
xaxis = list(
zeroline=F,
showline=F,
showticklabels=F,
showgrid=F),
yaxis=list(
showgrid=F,
tickmode = "array",
tickvals = seq_len(length(unique_vals)),
ticktext = sort(unique_vals)))
subplot(legend.plot, main.plot, widths = c(0.1, 0.9),
titleX=TRUE, titleY=TRUE)
Firstly, you are only passing in the unique values to the legend. If you pass in all possible values (ie, seq(min(x), max(x), by=1), or in this case seq_len(max(x))) the legend will show the full range.
Secondly, sizeref and sizemode in the marker argument alter the way that point size is calculated. The following example should produce a more consistent plot:
set.seed(1)
df <- data.frame(x=1:10,y=runif(10,1,10),group=c(rep("A",9),"B"),group.size=as.integer(runif(10,1,10)))
require(plotly)
require(dplyr)
a <- plot_ly(type='scatter',mode="markers",
color=~df$group,
x=~df$x,
y=~df$y,
size=df$group.size,
marker = list(sizeref=0.1, sizemode="area"),
data=df,
showlegend=F) %>%
layout(title="Title",
xaxis=list(title="X",zeroline=F),
yaxis=list(title="Y",zeroline=F))
b <- plot_ly() %>% add_markers(x = 1, y = seq_len(max(df$group.size)),
size = seq_len(max(df$group.size)),
showlegend = F,
marker = list(sizeref=0.1, sizemode="area")) %>%
layout(
xaxis = list(zeroline=F,showline=F,showticklabels=F,showgrid=F),
yaxis=list(showgrid=F))
subplot(b, a, widths = c(0.1, 0.9))
I am new to plotly and want to make my own bullet chart (a bit like http://bl.ocks.org/mbostock/4061961) that has markers/traces to show the values of the relevant values when comparing actual vs expected.
Below is my attempt:
q <- ggplot(data.frame(measure='',actual=25),aes(x=measure,y=actual))+
geom_bar(stat='identity')+
ylim(c(0,35))+
geom_hline(yintercept = 30,color='red')+
geom_text(y=30,label='Expected',angle=270,vjust=0)+
coord_flip()+
ylab('Num. of carrots')
q
q1 <- ggplotly(q) %>% add_markers()
q1
When converting it to plotly using ggplotly, the text looks like it has not rotated correctly, and the markers/traces do not show for the bar chart...Any help here would be much appreciated.
Kindest regards,
HLM
I do not think that plotly supports rotating text for type="scatter" (which is how ggplotly is interpreting your geom_text). You can delete the geom_text line from the ggplot graph, then add text to the plotly one using annotations:
q1 <- ggplotly(q) %>% add_markers() %>%
layout(annotations = list(x = 30, y = 1, text = "Expected", textangle=270))
q1
update
The 2nd part of your question (how to also get hover info on the bar) is slightly trickier. To get the hover info, we can create the bars using the plotly API directly like this
p.bars = plot_ly(data = data.frame(measure='', actual=25)) %>%
add_bars(y=~measure, x=~actual, orientation="h")
we can add the text annotation to it like this
p.bars.text = p.bars %>%
layout(annotations = list(x = 30, y = 0, text = "Expected", textangle=270,
showarrow=F, xanchor="center"))
But the problem is that adding a line also to this plot by
p.bars.text %>% add_segments(x=30, xend=30, y=-0.5, yend=0.5)
gives an error
Error in populate_categorical_axes(p) : Can't display both discrete & non-discrete data on same axis
I.e. we can only specify the y values of the line with respect to categorical values of y. So, for example we can do
dat1 = data.frame(measure=letters[1:2], actual=c(25,20))
plot_ly(data = dat1) %>%
add_bars(y=~measure, x=~actual, orientation="h") %>%
layout(annotations = list(x = 29, y = 0, text = "Expected", textangle=270,
showarrow=F, xanchor="center")) %>%
add_segments(x=30, xend=30, y='a', yend='b')
which gives the following in which the line is aligned with the category labels rather than with the width of the bars
The only solution I have to this at the moment is to use a numeric axis for the categories, and then set the axis labels using ticktext:
plot_ly(data = data.frame(measure=c(0,1), actual=c(25,20))) %>%
add_bars(y=~measure, x=~actual, orientation="h", showlegend=F) %>%
add_segments(x=30, xend=30, y=-0.4, yend=0.4, showlegend=F) %>%
layout(annotations = list(x = 29.5, y = 0, text = "Expected", textangle=270, showarrow=F, xanchor="center"),
yaxis = list(tickmode="array", tickvals=c(0,1), ticktext=c("", "") ))