lesson

I'm preparing to teach this for the first time, and I keep "coming up with great ideas for a challenge" only to find that they're clumped at the end (that I've done this more than once is shame on me ;) of course). I don't know if this is deliberately following a different model of teach-test or if it's the result of a migrations?

The challenges already there are smart, and appear tailored to c

The first line of output for git log --oneline is
005937f (HEAD -> main) Discuss concerns about Mars' climate for Mummy
In in the callout, Episode 5, "Limit Log Size," the output is missing (HEAD -> main).

Hi all,

This is nitpicking given that so much awesome work has been done in this repository, but here are some notes on grammar, as well as some suggestions on style:

In Manipulating, analyzing and exporting data with tidyverse:

Grammar

NB: Good first issue label (cannot be added because not in contributor list)

Exercise Reading error Messages - Lesson "Error and Exceptions"
(http://swcarpentry.github.io/python-novice-inflammation/09-errors/index.html)

• As dictionaries are not introduced previously in lesson (maybe a consequence of reducing the lesson) I suggest the following:

1. Moving this exercise at the end of th

In Section 8, Creating Publication-Quality Graphics with ggplot2, the two charts after the alpha argument is introduced should also have the alpha value set on them.

I.e. after this example

ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
  geom_point(alpha = 0.5) + scale_x_log10()

Admittedly, I'm not a pythonista, but I wonder whether there would be value in using bash versions of the three python scripts. For whatever reason, I'm running into problems with getting python installed correctly on my Mac. Once I got it pointed in the right direct, I ran into problems with installing numpy. It's quickly becoming a tutorial on installing python rather than make :)

I suspect the

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

• 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

I have helped in a few courses run based on the Gapminder material, and in common with Issue #528, getting to the correct directory and accessing the files is a common source of grief. My suggestion would be:

1. put in material in Episode 1 covering working directories in Python, and
2. remove the

Help Wanted to Fix:

• "Utilize" could be "use" throughout. (#353)
• Sometimes we emphasize terms with italics, sometimes with boldface. "The cloud" on 11-hpc-intro is bold, and "The cloud" on 12-cluster is italics. Any significance to the difference? Any preference on just using one?
• Should images be linked as "../fig/" instead of "fig/" ?
• Consistent use of "log in to

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

The discussion of data types and data structures in "Vectors and data types" could be clarified. Perhaps even defining these terms before using them would help. Also note that the first sentence of the section reads "A vector is the most common and basic data type in R, and is pretty much the workhorse of R." perhaps this should be changed to "basic data structure"

The Survey table has a field called quant that holds what type of reading was taken. The values in this column are rad, sal, and temp. There is no legend that explains what these mean on the page where the data is introduced (the selecting data chapter). Much later in the course it's mentioned that these mean 'radiation', 'salinity' and 'temperature', but I think it would also be helpful