data-visualisation

As a follow-up to #11540, we would like to add metadata to as many examples as possible. This will not only make the examples more usable as they are right now, but it will also open up new possibilities to search for and crosslink examples.

For the purpose of this issue, 'standalone examples' are all .py files in these folders in this repository:

• examples/plotting/file
• `examples/mode

In many node editor, the connections between nodes are mostly curves rather than straight lines
Visually, this can achieve better results. Can you consider using Bezier curves, etc. instead of the current straight line connection?

There are some examples:

• Github workflow preview:
  
• [

My comment is specifically about the example code showing how to add points to a ggplot boxplot. It's possible this is something that was fixed in an update to R or the ggplot2 package, but I know historically there have been issues with using geom_jitter and geom_boxplot together and these combined functions causing outlier points to duplicate.

I realize the code in the episode takes care of

Hello, I would like to know if there is already any method developed to match the flight_ids obtained from So6 to ADS-B files. I’m trying to use the assign_id method for both files but it seems to be assigned differnent new flight-ids for SO6 and ADS-B same flights.

Thank you.

The Introduction to R and RStudio of R for Reproducible Scientific Analysis introduces arithmetic calculations as the simplest way to use R. I think the section [Using R as a Calculator](https://swcarpentry.github.io/r-novice-gapminder/01-rstudio-intro/index.html#usi

• I felt like nunique was arbitrarily (re)introduced when it was necessary. It wouldn't be top-of-mind for students solving problems.
• The lesson answers need to be adjacent to the exercises.
• I like the pre-introduction of masks and then circling back around to explain them.
• I feel like Part 4 needs to be broken up and integrated across other lessons: it felt thin on its own.
• Horizo

Dear Community,

There is a typo in the section titled "The StringsAsFactors argument" after the second block of code that demonstrates the use of the str() function. Right after the code boxes is written "We can see that the $Color and $State columns are factors and $Speed is a numeric column", but the box shows that the $Color column is a vector of strings.

Regards,

Rodolfo

In the second episode I believe that it would be more usefull to have the sections "Python is case-sensitive" and "Use meaningful variable names" right after "Use variables to store values". It would keep all the information and instructions for using and allocating variables in one place before going into printing and slicing.

In episode _episodes_rmd/12-time-series-raster.Rmd

There is a big chunk of code that can probably be made to look nicer via dplyr:

# Plot RGB data for Julian day 133
 RGB_133 <- stack("data/NEON-DS-Landsat-NDVI/HARV/2011/RGB/133_HARV_landRGB.tif")
 RGB_133_df <- raster::as.data.frame(RGB_133, xy = TRUE)
 quantiles = c(0.02, 0.98)
 r <- quantile(RGB_133_df$X133_HARV_landRGB.1, q