Move data download instructions to project directory setup

episodes/introduction-r-rstudio.Rmd

@@ -174,6 +174,8 @@ Let's start making our new folders. Go to the **Files** pane (bottom right), and
 
 Next, click the **New Folder** button, and type in `scripts` to generate your `scripts` folder. It should appear in the Files list now. Repeat the process to make your `data`, `images`, and `documents` folders. Then, click on the `data` folder in the Files pane. This will take you into the `data` folder, which will be empty. Use the **New Folder** button to create `raw` and `cleaned` folders. To return to the `R-Ecology-Workshop` folder, click on it in the file path, which is highlighted in yellow in the previous image. It's worth noting that the **Files** pane helps you create, find, and open files, but moving through your files won't change where the **working directory** of your project is.
 
+We have prepared a cleaned dataset that you will use towards the end of the workshop. Since you're setting up your project directory now, it's a good time to download it and add it to your directory. Click this link to download the file:  <https://datacarpentry.org/R-ecology-lesson/data/cleaned/surveys_complete_77_89.csv>. You may be prompted to save the file on your computer somewhere, or it might download automatically to a Downloads folder. If you are prompted, save it inside the `cleaned` data folder, which is in the `data` folder you just created. If you are not prompted choose a location, wait until it has downloaded and then move it from its current location to the `cleaned` folder using whatever method you would normally use to move files.
+
 ## Working in R and RStudio
 
 The basis of programming is that we write down instructions for the computer to follow, and then we tell the computer to follow those instructions. We write these instructions in the form of *code*, which is a common language that is understood by the computer and humans (after some practice). We call these instructions *commands*, and we tell the computer to follow the instructions by *running* (also called *executing*) the commands.

episodes/working-with-data.Rmd

@@ -71,11 +71,8 @@ library(tidyverse)
 
 ## Importing data
 
-Up until this point, we have been working with the `complete_old` dataframe contained in the `ratdat` package. However, you typically won't access data from an R package; it is much more common to access data files stored somewhere on your computer. We are going to download a CSV file containing the surveys data to our computer, which we will then read into R.
+Up until this point, we have been working with the `complete_old` dataframe contained in the `ratdat` package. However, you typically won't access data from an R package; it is much more common to access data files stored somewhere on your computer. We are now going to start using the data in our `cleaned` directory inside the `data` directory that you downloaded at the beginning of the lesson. This file is called `surveys_complete_77_89.csv`.
 
-Click this link to download the file: <https://datacarpentry.org/R-ecology-lesson/data/cleaned/surveys_complete_77_89.csv>.
-
-You will be prompted to save the file on your computer somewhere. Save it inside the `cleaned` data folder, which is in the `data` folder in your `R-Ecology-Workshop` folder. Once it's inside our project, we will be able to point R towards it.
 
 #### File paths
 

learners/setup.md

@@ -118,9 +118,9 @@ Sometimes, package updates introduce changes that break your old code, which can
 
 ### Download the data
 
-We will download the data directly from R during the lessons. However, if you are expecting problems with the network, it may be better to download the data beforehand and store it on your machine.
+We will download the data we need during the lessons. However, if you are expecting problems with the network, it may be better to download the data beforehand and store it on your machine.
 
-The data files for the lesson can be downloaded manually:
+The data files for the lesson can be downloaded from:
 
  - [cleaned data](../episodes/data/cleaned/surveys_complete_77_89.csv) and 
  - [zip file of raw data](../episodes/data/new_data.zip).