data-wrangling

On Windows, creating a project from a URL that contains the colon ":" character in the URL path throws an error related to the naming of a temporary directory/file.

To Reproduce

Steps to reproduce the behavior:

1. Create a new project from a URL as protocol://domain/foo/:bar/foo
2. Click on the Next button
3. An error message is displayed that states "Error uploading data illegal char

Starting at line 135 the lesson uses view() to open the data in RStudio's Data Viewer.
I suggest adding to the note on line 141 that tibble::view() and utils::View() have similar functionality but are part of different packages which is why the function does not seem to be case sensitive.

The space between Work and flow in the title of the Work flow within RStudio chunk should be removed as workflow is a single word.

Also, in this same section, reference to a .R file occurs without explanation that this is reflective of the R scripts described above. This could potentially b

• 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

https://swcarpentry.github.io/python-novice-gapminder/01-run-quit/index.html
Update in wording

I would like to suggest improvement to the below opening paragraph, found at https://swcarpentry.github.io/python-novice-gapminder/01-run-quit/index.html

"Many software developers will often use an integrated development environment (IDE) or a text editor to create and edit their Python programs

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

As datacarpentry is aimed at researchers, citations are an important part of their job.
Therefore a page on Rmarkdown should mention citations.

Maybe just one sentence about it including a link that is a more up-to-date version of
https://www.rstudio.com/blog/rstudio-1-4-preview-citations/