Organizing and struturing practice session 2.

materials/sections/exercise-intro-programming-socialsci.qmd

@@ -28,15 +28,15 @@ by clicking the "more info" link next to the file name at the top of the
 page.**
 
 ::: callout-note
-## Session's Goal
+## Big Idea
 
 The goal for this session is to practice downloading data, reading it
 into R in a Quarto document, using base R commands to summarize a
 variable within the dataset, and practice formatting a Quarto document
 using Markdown syntax.
 :::
 
-## Exercise I
+## Exercise 1
 
 ::: callout-tip
 ## Set up
@@ -133,7 +133,7 @@ Calculate the mean of the answers to Question 3 and save this value into
 an object in your Global Environment.
 
 **Tip:** Look at the help page if your answer isn't what you expect,
-`?mean()`. Does Q3 column contan `NA` values?
+`?mean()`. Does Q3 column have `NA` values?
 :::
 
 

materials/sections/exercise-tidyverse-socialsci.qmd

@@ -1,23 +1,85 @@
 ## Learning Objectives {.unnumbered}
 
--   practice tidyverse R skills
+-   Practice cleaning and wrangling data
+-   Practice using `dplyr` and `tidyr` functions
+-   Learn how to use the `tibble::tibble()` function to create a data frame
 
-### Introduction
+## Introduction
 
 In this session of R practice, we will continue working with the dataset: [Tobias Schwoerer, Kevin Berry, and Jorene Joe. 2022. A household survey documenting experiences with coastal hazards in a western Alaska community (2021-2022). Arctic Data Center. doi:10.18739/A29Z90D3V.](https://doi.org/10.18739/A29Z90D3V)
 
-In this practice session, we will build upon the previous session by using `dplyr`, `tidyr`, and other packages form the tidyverse to create more summarizations of the survey answers.
+::: callout-tip
+## Big Idea
 
-### High level steps
+In this practice session, we will build upon the previous session by using `dplyr`, `tidyr`, and other packages form the tidyverse to summarize answers of the survey.
+:::
 
--   work in the same Rmd you did during R practice I
--   add necessary headers and text to describe what you are doing during this practice
--   using `group_by` and `summarize`, calculate how many responses there were to each unique answer for question 3
--   create a `data.frame` containing the definitions to the answer codes in question 3
-    -   use the metadata to get code-definition pairs
-    -   create your `data.frame` either by writing a new file and reading it in, or by exploring the function `tribble` (see the examples)
--   use a `left_join` to join your definitions table to the summarized answers
+## Exercise 2
 
-#### Bonus {.unnumbered}
+::: callout-tip
+## Set up
 
+-   Work in the same Qmd you did during R practice 1.
+-   Add necessary headers and text to describe what you are doing during this practice.
+    -   Using Split-Apply-Combine strategy
+    -   Creating a Data Frame
+    -   Joining Data Frames
+
+-   At the top of your document, one line below the three dashed line from the YAML, add a level 2 header called Setup followed by a new code chunk to load the necessary libraries.
+
+```{r}
+library(readr)
+library(dplyr)
+library(tidyr)
+library(tibble)
+```
+
+
+:::
+
+### Using Split-Apply-Combine strategy
+
+::: callout-note
+## Step 1
+
+Use `group_by` and `summarize` to calculate how many responses there were to each unique answer for question 3.
+:::
+
+
+::: {.callout-note appearance="minimal" collapse="true"}
+## Example Code
+
+
+```{r}
+
+#q3_summary <- 
+
+```
+
+:::
+
+### Creating a Data Frame
+
+::: callout-note
+## Step 2
+Create a `data.frame` containing the definitions to the answer codes in Question 3. Use the [metadata](https://arcticdata.io/catalog/view/doi%3A10.18739%2FA29Z90D3V#urn%3Auuid%3Aab696e67-8ed0-4900-b568-4ee576bc87bd) to get code-definition pairs.
+
+One way of creating a new data frame is by using the  `tribble()` or `tibble()` functions from the [`tibble` package](https://tibble.tidyverse.org/index.html).
+
+**Tip:** Search either in the help page or on the web for information about `tribble()` or `tibble()`. Then decide which on to use to create a new data frame.
+
+:::
+
+### Joining Data Frames
+
+::: callout-note
+## Step 3
+Use a `left_join` to join your definitions table to the summarized answers
+:::
+
+## Bonus
+
+::: callout-note
+## Go Further
 Explore how you might summarize other questions in these survey results.
+:::

materials/session_07.qmd

@@ -14,5 +14,4 @@ execute:
 
 
 
-
 {{< include /sections/exercise-intro-programming-socialsci.qmd >}}

materials/session_12.qmd

@@ -1,7 +1,10 @@
-
 ---
-title: "Practice Session II"
+title: "R Practice: Cleaning and Wrangling"
 title-block-banner: true
+execute:
+  eval: false
 ---
 
+
+
 {{< include /sections/exercise-tidyverse-socialsci.qmd >}}