aesthetic | ＭＯＳＴ ＥＦＦＩＣＩＥＮＴ ＡＥＳＴＨＥＴＩＣ | Computer Vision library

Adding a fill variable to geom_dotplot introduces an unwanted grouping to the geom. Here's the behavior when you don't add a fill variable:

I am trying to present some data

Background:

I have a little dataframe composed of percentage estimates across two characteristics. One is "political party", the other is "sex". As it stands, these specific names are unmentioned in the df even if the categories that comprise them are. Here it is:

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 have a dataframe which has two different sample types (A and B). I would like to differentiate these by using different shape options. Here is a dataframe and my current attempt at performing this.

output of dput(head(df))

I am using Jenkins and Nginx both in Docker,

From Jenkins docker documentation, it seems that jenkins need 2 ports, 50000 and 8080, Reference : https://github.com/jenkinsci/docker/blob/master/README.md

Nginx acting as reverse proxy has this configuration right now

I have the dataframe below:

I am having difficulties customising the aesthetics of an interactive line plot in Plotly Python, and would appreciate some assistance from members of the community here.

Here is a picture of the plot I would like to amend, a working example of which is supplied further down the page:

In particular, I want to know how or what can be modified so that I can

1. Remove 'step-#' in 'Sample size n = step-#', and replace with 'Sample size n = #', where # is a number. Currently the value of # is also out of sync with the title. So in this figure # should be displayed as 300.

2. Remove the 'step-#' annotating the slider, and replace it with something else.

3. Adjust number of 'ticks' on the slider line.

Ideally, I would appreciate if someone could tell me definitively what keywords or parameters I need to be amending in Plotly.

Having read the documentation, it is not clear to me what parameters/keyword arguments I need to be tweaking in order to customise the aesthetics to be closer to what I desire. And I don't know if the customisation I'm looking for can be achieved with these parameter/keyword argument tweaks, or if it would require a rewriting of the code I have reproduced below.

Essentially, I want the slider looking something more like the one in this example:

Minimal working code example.

I adapted this code from the example from the Plotly documentation on sliders here

Let's say I have a class with many static methods. My goal is to wrap each static method with a function. Specifically, I want to catch async errors by applying .catch to each static method like so: