ggradar | radar charts with ggplot2 | Data Visualization library
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kandi X-RAY | ggradar Summary
radar charts with ggplot2
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QUESTION
I want to create a radar chart with ggradar package. The problem is that I have long labels and they are clipped (as shown in the figure below inside two red rectangles).
...ANSWER
Answered 2022-Apr-08 at 04:40You could increase the plot.margin
and add coord_cartesian(clip = "off")
. However, this distorts the dimensions of your radar chart. I played around with the plot pane to account for that. However, I'm sure there are cleverer solutions to your problem.
QUESTION
Given a sample data as follows:
...ANSWER
Answered 2022-Apr-07 at 13:21I think you need to scale your data so that, say, the values 45 - 55 map to the range 0 - 1. Then just label the plot appropriately:
QUESTION
I am using ggradar to create radar plots. I have a case like this:
...ANSWER
Answered 2021-Jun-21 at 10:07This could be achieved by setting the argument grid.max
and grid.mid
You could also set the labels via values.radar
:
QUESTION
I want to create a radar chart with ggirahExtra::ggRadar
. The problem is that I have long labels and they are clipped. I thought I could create more space between label and plot by adding margin = margin(0,0,2,0, "cm")
to element_text
in axis.text
, but its not working.
Any ideas how to increase the label space are welcome (apart from making the font smaller).
Add: As @tjebo suggests in the comments, it might be easier, or maybe the only way to make it work, to change the underlying functions in ggRadar
especially coord_radar
. Any suggestions of how to do this are welcome.
ANSWER
Answered 2021-Apr-30 at 13:05You can use the labelled
package to create labels with line breaks and then set label = TRUE
in ggRadar()
. You can add more than one break for super long labels.
QUESTION
I'm hoping to calculate the area of a polygon using ggradar.
From the research I've done so far, I think the goal is to calculate the area of each triangle and add them all together. Since we know the distance from the centroid to each point and the angle between the two sides of each triangle, we can calculate the area for each wedge using side1 x side2 x sin(pi/n)/2 (where n = number of variables, in this case 4) and adding all the wedges together.
Using mtcars data as an example:
...ANSWER
Answered 2020-Oct-26 at 19:10While I question the utility, it certainly is possible to do this in R. Here's such a function
QUESTION
I am trying to add title for all my plot in a loop, here is what I have done:
first I split the data with the split()
fuction:
ANSWER
Answered 2020-Oct-24 at 14:46No data to test this but in such situations when you want to access the names of the list you can use imap
from purrr
:
QUESTION
Hi everyone I am making a a radar plot and I want to highlight the two highest values in the factors or levels. Highlight in this case is to make the text of the top tree values bold
...ANSWER
Answered 2020-Jun-20 at 00:37My suggestion would be to identify the highest values you wish to highlight, and put them in a dataframe. Then use geom_richtext()
to highlight.
QUESTION
This issue is so strange to me. So I tried to create a radar chart using ggRadar from the interactive ggplot2 package ggiraphExtra, and for some reason it can't identify my particular data.frame. Emphasise "particular", other data.frames work fine with this plot statement but my particular data.frame won't.
Here's an example using the iris dataset, this example works fine.
...ANSWER
Answered 2020-Apr-19 at 11:08The following runs without issue on my computer. Can you share sessionInfo()
and try with a new R session.
QUESTION
Here's my code:
...ANSWER
Answered 2020-Mar-27 at 14:04All,
A lot of you have been getting this error with #3/ ggradar:
Error in data.frame(group = i, x = pathData[,j] * sin(angles[j-1]), : arguments imply differing number of rows: 1, 0
If you are getting this, it's likely because your dataframe isn't coverting to a tibble correctly.
To resolve it, try to read in the files with the command read_csv() instead of read.csv
read_csv reads it in as a tibble, which prevents conversion issues later. read.csv reads it in as a dataframe.
Of note, you need to call library(readr) before using read_csv
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