diff --git a/index.Rmd b/index.Rmd
index a4eefe73..b8ab3768 100644
--- a/index.Rmd
+++ b/index.Rmd
@@ -37,7 +37,7 @@ knitr::include_graphics("images/class.jpg")
#### Online course
-_`r config::get("online_dates")`_
+_`r config::get("online_dates")`_
_`r config::get("online_times")`_
Two-week online course in R programming foundations.
@@ -46,7 +46,7 @@ Two-week online course in R programming foundations.
#### Code-a-thon
-_`r config::get("codeathon_dates")`_
+_`r config::get("codeathon_dates")`_
_`r config::get("codeathon_times")`_
Three-day in-person intensive “Code-a-thon”. Here, we'll work on authentic environmental health projects. We'll also practice data ethics skills in peer code review, reproducibility, and transparency in a supportive environment.
diff --git a/modules/Data_Input/Data_Input.Rmd b/modules/Data_Input/Data_Input.Rmd
index 899c1cfd..3aa82206 100644
--- a/modules/Data_Input/Data_Input.Rmd
+++ b/modules/Data_Input/Data_Input.Rmd
@@ -36,6 +36,12 @@ R Projects are a super helpful feature of RStudio. They help you:
- **Be more reproducible.** You can share the entire project directory with others, and they can replicate your environment and analysis without much hassle.
+## Why projects?
+
+"The chance of the `setwd()` command having the desired effect – making the file paths work – for anyone besides its author is 0%. It’s also unlikely to work for the author one or two years or computers from now. The project is not self-contained and portable."
+
+- [Jenny Bryan](https://www.tidyverse.org/blog/2017/12/workflow-vs-script/)
+
**Let's go over how to create and use an R Project!**
## New R Project
@@ -99,6 +105,10 @@ knitr::include_graphics("images/Data_Input_new_project_topright.png")
* We are going to focus on simple delimited files first
* comma separated (e.g. '.csv')
* tab delimited (e.g. '.txt')
+
+
+
+**delimiters** are symbols that separate cells in a simple-text file.
## Data Input
@@ -293,15 +303,6 @@ These functions have slightly different syntax for reading in data (e.g. `header
However, while many online resources use the base R tools, the latest version of RStudio switched to use these new `readr` data import tools, so we will use them in the class for slides. They are also up to two times faster for reading in large datasets, and have a progress bar which is nice.
-
-## TROUBLESHOOTING: Setting the working directory
-
-If you are trying to knit your work, it might help to set the knit directory to the "Current Working Directory":
-
-```{r, fig.alt="Screenshot of the Knit menu, with Knit directory open, and Current Working Directory selected.", out.width = "60%", echo = FALSE, align = "center"}
-knitr::include_graphics("images/Data_Input_knit_directory.png")
-```
-
## Other Useful Functions
- The `str()` function can tell you about data/objects.
diff --git a/modules/Data_Input/lab/Data_Input_Lab_Key.Rmd b/modules/Data_Input/lab/Data_Input_Lab_Key.Rmd
index d3f2c137..201a2e9d 100644
--- a/modules/Data_Input/lab/Data_Input_Lab_Key.Rmd
+++ b/modules/Data_Input/lab/Data_Input_Lab_Key.Rmd
@@ -65,7 +65,7 @@ Preview the data by examining the Environment. How many observations and variabl
### P.1
-Download the data and move the file to your project folder. Import the data by browsing for the file on your computer.
+Download the data from https://daseh.org/data/CalEnviroScreen_data.csv and move the file to your project folder. Import the data by browsing for the file on your computer.
> *Download the data*
> *Put data in the project folder*