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Q-Q plot is a useful graphical device used to check for example normality of residuals. Q-Q plot is constructed by putting theoretical quantiles on x-axis and observed quantiles on the y-axis. In ggplot, this can be easily done using geom_qq and stat_qq. I would like to produce a wormplot, which is like a Q-Q plot, but on the y-axis, it has a difference between theoretical and observed quantiles (see the figure).

Is there a way to do this in ggplot? For example, is there a simple way to change the y-axis of the geom_qq to show the difference between theoretical and observed quantiles? I know it should be possible to calculate observed quantiles manually, but this would not work well if I would like to create plots of multiple groups or using facets, since then I would also need to calculate the observed quantiles manually for each group separately.

I'm working with house price indices and I have a question on how to add another geom to a ggplot. This is an example data that I made for this question. I have housing data from a census and from online postings. rooms a variable for a housing characteristic (many or few rooms), and value is the percentage of homes for each source that has that characteristic. Then, houses and apts show the percentage of houses and apts that the city has for that data source. So for example, city 1 has 40% houses and 60% apartments in the census data and 45% houses and 55% apartments in the zillow data. I made a geom_bar faceting by rooms and filling by source so I have two plots, one for rooms=1 and another for rooms=2, each one of them with two bars for each city (one for each source). Now, I want to fill those same bars with the percentage of houses and apartments for each city and source.

I'd be very grateful if someone can help me with this.

The code I'm currently using for the plot is the following:

The plot code below makes the segment line congverge at the center of the descrete x variable for all colours. What can be done so that the segment line is vertical for each x variable respective of colour?

I have made a plot displaying multiple facets of my data. The colour bar created by scale_colour_gradientn is confusing because it shows percentage breakdowns. Could I get rid of these percentage breakdowns and add my own. I have tried using values and breaks parameters but with no luck. I think maybe ggplot is confused because most of the values are either very small or close to 1. I have added a toy dataset, code and image output below.

dput(df)

I need to get the email address from this 'facets' table I created from my firehose logs (JSON).

Now, I am using Athena to get particular information.

I need to get the email addresses from this:

This is my out of 'facets' when I pass-

I have stucked with an issue using refinement list widget of algolia. First of all my resulting data structure is like that:

I've created a new SOLR Indexed property that must act as category a facet:

Im currently getting back into using R, but its been a while so im a little rusty.

I have the following code for making plots using ggplot2:

I'm trying to put a mean in a boxplot with facets but the mean points does not end up on top of the boxplot but next to them. Any suggestions as how to fix this so that the mean points end up on top of the boxplots?

Here's the code for the ggplot2