Run aeolus on non-episode files

Author: Bisaloo

instructors/instructor-notes.md

@@ -19,70 +19,61 @@ and may not be relevant to this redesigned version.**
 ## Dataset
 
 The data used for this lesson are in the figshare repository at:
-[https://doi.org/10.6084/m9.figshare.1314459](https://doi.org/10.6084/m9.figshare.1314459)
-
-This lesson uses mostly `combined.csv`. The 3 other csv files: `plots.csv`,
-`species.csv` and `surveys.csv` are only needed for the lesson on databases.
-
-`combined.csv` is downloaded directly in the episode "Starting with Data" and
-does not need to be downloaded before hand. It however requires that there is a
-decent internet connection in the room where the workshop is being taught. To
-facilitate the download process, the chunk of code that includes the URL where
-the csv file lives, and where the file should go and be named is included in the
-code handout (see next paragraph). Using this approach ensures that the file
-will be where the lesson expects it to be, and teaches good/reproducible
-practice of automating the download. If the learners haven't created the `data/`
-directory and/or are not in the correct working directory, the `download.file`
-command will produce an error. Therefore, it is important to use the stickies at
-this point.
+<https://doi.org/10.6084/m9.figshare.1314459>
+
+This lesson uses mostly `combined.csv`.
+The 3 other csv files: `plots.csv`, `species.csv` and `surveys.csv` are only needed for the lesson on databases.
+
+`combined.csv` is downloaded directly in the episode "Starting with Data" and does not need to be downloaded before hand.
+It however requires that there is a decent internet connection in the room where the workshop is being taught.
+To facilitate the download process, the chunk of code that includes the URL where the csv file lives, and where the file should go and be named is included in the code handout (see next paragraph).
+Using this approach ensures that the file will be where the lesson expects it to be, and teaches good/reproducible practice of automating the download.
+If the learners haven't created the `data/` directory and/or are not in the correct working directory, the `download.file` command will produce an error.
+Therefore, it is important to use the stickies at this point.
 
 ## The handout
 
-The [code handout](files/code-handout.R)
-(a link to download it is also available on the top bar of the lesson website)
-is useful for Data Carpentry workshops. It includes an outline of the lesson
-content, the text for the challenges, the links for the files that need to be
-downloaded for the lesson, and pieces of code that may be difficult to type for
-learners with no programming experience/who are unfamiliar with R's syntax. We
-encourage you to distribute it to the learners at the beginning of the
-lesson. As an instructor, we encourage you to do the live coding directly in
-this file, so the participants can follow along.
+The [code handout](files/code-handout.R) (a link to download it is also available on the top bar of the lesson website) is useful for Data Carpentry workshops.
+It includes an outline of the lesson content, the text for the challenges, the links for the files that need to be downloaded for the lesson, and pieces of code that may be difficult to type for learners with no programming experience/who are unfamiliar with R's syntax.
+We encourage you to distribute it to the learners at the beginning of the lesson.
+As an instructor, we encourage you to do the live coding directly in this file, so the participants can follow along.
 
 ## R Version
 
-With the release of R 4.0.0 in early 2020, an important change has been made
-to R: The default for `stringsAsFactors` is now `FALSE` instead of `TRUE`.
-As a result, the `read.csv()` and `data.frame()` functions do not automatically
-convert character columns to factors anymore (you can read more about it
-[in this post on the R developer blog](https://developer.r-project.org/Blog/public/2020/02/16/stringsasfactors/index.html)).
+With the release of R 4.
+0\.
+0 in early 2020, an important change has been made to R: The default for `stringsAsFactors` is now `FALSE` instead of `TRUE`.
+As a result, the `read.csv()` and `data.frame()` functions do not automatically convert character columns to factors anymore (you can read more about it [in this post on the R developer blog](https://developer.r-project.org/Blog/public/2020/02/16/stringsasfactors/index.html)).
 
-This change should not cause any problems with this lesson, independent of
-whether R >4.0 is used or not, because it uses
-`read_csv()` from the **`tidyverse`** package throughout. Other than
-`read.csv()` from base R, `read_csv()` never converts character columns to
-factors, regardless of the R version.
+This change should not cause any problems with this lesson, independent of whether R >4.
+0 is used or not, because it uses `read_csv()` from the **`tidyverse`** package throughout.
+Other than `read.csv()` from base R, `read_csv()` never converts character columns to factors, regardless of the R version.
 
-Nevertheless, it is recommended that learners install a version of R ≥4.0.0,
-and instructors and helpers should be aware of this potential source of error.
+Nevertheless, it is recommended that learners install a version of R ≥4.
+0\.
+0, and instructors and helpers should be aware of this potential source of error.
 
 ## RStudio and Multiple R Installs
 
-Some learners may have previous R installations. On Mac, if a new install
-is performed, the learner's system will create a symbolic link, pointing to the
-new install as 'Current.' Sometimes this process does not occur, and, even
-though a new R is installed and can be accessed via the R console, RStudio does
-not find it. The net result of this is that the learner's RStudio will be
-running an older R install. This will cause package installations to fail. This
-can be fixed at the terminal. First, check for the appropriate R installation in
-the library;
+Some learners may have previous R installations.
+On Mac, if a new install is performed, the learner's system will create a symbolic link, pointing to the new install as 'Current.
+' Sometimes this process does not occur, and, even though a new R is installed and can be accessed via the R console, RStudio does not find it.
+The net result of this is that the learner's RStudio will be running an older R install.
+This will cause package installations to fail.
+This can be fixed at the terminal.
+First, check for the appropriate R installation in the library;
 
 ```
 ls -l /Library/Frameworks/R.framework/Versions/
 ```
 
-We are currently using R 4.0.x. If it isn't there, they will need to install it.
-If it is present, you will need to set the symbolic link to Current to point to
-the 4.0.x directory:
+We are currently using R 4.
+0\.
+x.
+If it isn't there, they will need to install it.
+If it is present, you will need to set the symbolic link to Current to point to the 4.
+0\.
+x directory:
 
 ```
 ln -s /Library/Frameworks/R.framework/Versions/3.6.x /Library/Frameworks/R.framework/Version/Current
@@ -92,26 +83,22 @@ Then restart RStudio.
 
 ## Issues with Fonts on MacOS
 
-On older versions of MacOS, it may happen that axis labels do not show up when calling `plot()`
-(section "renaming factors" in "Starting with Data"). This issue might be due to the default font
-Arial being deactivated, so that R cannot find it. To resolve this issue, go to Finder,
-Search for Font Book and open it. Look for the Arial font and, if it is greyed out, turn it on.
+On older versions of MacOS, it may happen that axis labels do not show up when calling `plot()` (section "renaming factors" in "Starting with Data").
+This issue might be due to the default font Arial being deactivated, so that R cannot find it.
+To resolve this issue, go to Finder, Search for Font Book and open it.
+Look for the Arial font and, if it is greyed out, turn it on.
 
-If the problem occurs with `ggplot2` plots, an alternative workaround is to change the default
-theme for the R session, so that ggplot uses a *serif* font. Since Arial is a *sans-serif*
-font, R will try to load a different font. This can be done with
-`theme_update(text = element_text(family = "serif"))`.
+If the problem occurs with `ggplot2` plots, an alternative workaround is to change the default theme for the R session, so that ggplot uses a *serif* font.
+Since Arial is a *sans-serif* font, R will try to load a different font.
+This can be done with `theme_update(text = element_text(family = "serif"))`.
 
 ## Required packages
 
-Save yourself some aggrevation, and have everyone check and see if they can
-install all these packages before you start the first day.
-See the "Install required R packages" section on the homepage of the course
-website for package installation instructions.
+Save yourself some aggrevation, and have everyone check and see if they can install all these packages before you start the first day.
+See the "Install required R packages" section on the homepage of the course website for package installation instructions.
 
 Sometimes learners are unable to install the **`tidyverse`** package.
-In that case, they can try to install the individual packages that are actually
-needed:
+In that case, they can try to install the individual packages that are actually needed:
 
 ```
 install.packages(c("readr", "lubridate", "dplyr", "tidyr", "ggplot2", "dbplyr"))
@@ -194,7 +181,7 @@ The two main goals for this lessons are:
 - This lesson is a broad overview of ggplot2 and focuses on (1) getting familiar
   with the layering system of ggplot2, (2) using the argument `group` in the
   `aes()` function, (3) basic customization of the plots.
-- It maybe worthwhile to mention that we can also specify colors by color HEX code ([http://colorbrewer2.org](https://colorbrewer2.org))
+- It maybe worthwhile to mention that we can also specify colors by color HEX code ( [http://colorbrewer2.org](https://colorbrewer2.org))
   ```
   ggplot(data = surveys_complete, mapping = aes(x = weight, y = hindfoot_length)) +
       geom_point(alpha = 0.1, color = "#FF0000")
@@ -214,44 +201,33 @@ The two main goals for this lessons are:
 
 ## Potential issues \& solutions
 
-As it stands, the solutions to all the challenges are commented out in the Rmd
-files. If you want to double check your answer, you can look at the source code
-of the Rmd files on GitHub.
+As it stands, the solutions to all the challenges are commented out in the Rmd files.
+If you want to double check your answer, you can look at the source code of the Rmd files on GitHub.
 
 ## Technical Tips and Tricks
 
-Show how to use the 'zoom' button to blow up graphs without constantly resizing
-windows
+Show how to use the 'zoom' button to blow up graphs without constantly resizing windows
 
 Sometimes a package will not install, try a different CRAN mirror
 
 - Tools > Global Options > Packages > CRAN Mirror
 
-Alternatively you can go to CRAN and download the package and install from ZIP
-file
+Alternatively you can go to CRAN and download the package and install from ZIP file
 
 - Tools > Install Packages > set to 'from Zip/TAR'
 
-It is important that R, and the R packages be installed locally, not on a
-network drive. If a learner is using a machine with multiple users where their
-account is not based locally this can create a variety of issues (This often
-happens on university computers). Hopefully the learner will realize these
-issues before hand, but depending on the machine and how the IT folks that
-service the computer have things set up, it may be very difficult to impossible
-to make R work without their help.
+It is important that R, and the R packages be installed locally, not on a network drive.
+If a learner is using a machine with multiple users where their account is not based locally this can create a variety of issues (This often happens on university computers).
+Hopefully the learner will realize these issues before hand, but depending on the machine and how the IT folks that service the computer have things set up, it may be very difficult to impossible to make R work without their help.
 
-If learners are having issues with one package, they may have issues with
-another. It is often easier to [make sure they have all the necessary packages installed](#required-packages)
-at one time, rather then deal with these issues over and over.
+If learners are having issues with one package, they may have issues with another.
+It is often easier to [make sure they have all the necessary packages installed](#required-packages) at one time, rather then deal with these issues over and over.
 
-In lesson 2 starting with data, one might not have the appropriate folder "data\_raw" in their working directory causing an error. This is a good time to go over reading an error, and a brief introduction of how to identify your working directory `getwd()` as well as setting your working directory `setwd("/somedirectory")` and if needed creating a directory within your script `dir.create("/some_new_directory")`, or simply creating it within a file explorer works if short on time.
+In lesson 2 starting with data, one might not have the appropriate folder "data\_raw" in their working directory causing an error.
+This is a good time to go over reading an error, and a brief introduction of how to identify your working directory `getwd()` as well as setting your working directory `setwd("/somedirectory")` and if needed creating a directory within your script `dir.create("/some_new_directory")`, or simply creating it within a file explorer works if short on time.
 
 ## Other Resources
 
-If you encounter a problem during a workshop, feel free to contact the
-maintainers by email or
-[open an issue](https://github.com/fishtree-attempt/R-ecology-lesson/issues/new).
+If you encounter a problem during a workshop, feel free to contact the maintainers by email or [open an issue](https://github.com/fishtree-attempt/R-ecology-lesson/issues/new).
 
-For a more in-depth coverage of topics of the workshops, you may want to read
-"[R for Data Science](https://r4ds.had.co.nz/)" by Hadley Wickham and Garrett
-Grolemund.
+For a more in-depth coverage of topics of the workshops, you may want to read " [R for Data Science](https://r4ds.had.co.nz/)" by Hadley Wickham and Garrett Grolemund.

learners/extra-challenges.Rmd

@@ -4,7 +4,6 @@ teaching: 45
 exercises: 3
 ---
 
-
 ```{r setup, include=FALSE}
 knitr::opts_chunk$set(dpi = 200, out.height = 600, out.width = 600, R.options = list(max.print = 100))
 ```
@@ -14,22 +13,24 @@ library(tidyverse)
 surveys <- read_csv("data/cleaned/surveys_complete_77_89.csv")
 ```
 
-::::::::::::::::::::::::::::::::::::: challenge 
+::::::::::::::::::::::::::::::::::::: challenge
 
 ## Challenge: `ggplot2` syntax
 
-There are some issues with these `ggplot2` examples. Can you figure out what is wrong with each one?
+There are some issues with these `ggplot2` examples.
+Can you figure out what is wrong with each one?
 
 ```{r, eval=FALSE}
 ggplot(data = surveys, 
        mapping = aes(x = weight, y = hindfoot_length, color = "blue")) +
   geom_point()
 ```
 
+:::::::::::::::::::::::: solution
 
-:::::::::::::::::::::::: solution 
-
-Our points don't actually turn out blue, because we defined the color inside of `aes()`. `aes()` is used for translating variables from the data into plot elements, like color. There is no variable in the data called "blue".
+Our points don't actually turn out blue, because we defined the color inside of `aes()`.
+`aes()` is used for translating variables from the data into plot elements, like color.
+There is no variable in the data called "blue".
 
 ::::::::::::::::::::::::
 
@@ -39,7 +40,7 @@ ggplot(data = surveys,
   geom_point()
 ```
 
-:::::::::::::::::::::::: solution 
+:::::::::::::::::::::::: solution
 
 Variable names inside `aes()` should not be wrapped in quotes.
 
@@ -51,7 +52,7 @@ ggplot(data = surveys,
   + geom_point()
 ```
 
-:::::::::::::::::::::::: solution 
+:::::::::::::::::::::::: solution
 
 When adding things like `geom_` or `scale_` functions to a `ggplot()`, you have to end a line with `+`, not begin a line with it.
 
@@ -62,7 +63,7 @@ ggplot(data = surveys, x = weight, y = hindfoot_length) +
   geom_point()
 ```
 
-:::::::::::::::::::::::: solution 
+:::::::::::::::::::::::: solution
 
 When translating variables from the data, like `weight` and `hindfoot_length`, to elements of the plot, like `x` and `y`, you must put them inside `aes()`.
 
@@ -75,9 +76,10 @@ ggplot(data = surveys,
   scale_color_continuous(type = "viridis")
 ```
 
-:::::::::::::::::::::::: solution 
+:::::::::::::::::::::::: solution
 
-`species_id` is a categorical variable, but `scale_color_continuous()` supplies a continuous color scale. `scale_color_discrete()` would give a discrete/categorical scale.
+`species_id` is a categorical variable, but `scale_color_continuous()` supplies a continuous color scale.
+`scale_color_discrete()` would give a discrete/categorical scale.
 
 ::::::::::::::::::::::::
 ::::::::::::::::::::::::::::::::::::::::::::::::