00_import_data.qmd

---
title: "Exercise 0"

date-modified: 'today'
date-format: long

format: 
  html:
    footer: "CC BY 4.0 John R Little"

license: CC BY    
---

Goals:

-   Create a R Notebook
-   Import a dataset using `reader::read_csv()`

> ANSWER can be found in exercise_00_answers.Rmd file

## Exercise: Data Structures & Vector Types

1.  Load the tidyverse libary package

```{r}
#| message: false
#| warning: false
library(tidyverse)
```

2.  Fill in the blanks. Using what you've seen in class, if `data/brodhead_center.csv` is a CSV (comma separated values) file, how would you load the file into a new object called `brodhead`?
    -   Often people find using the {here} package is helpful . e.g. `read_csv(here::here("data", "file")`

```{r}
_____  <- read_csv(________)
```

3.  Display your new `brodhead` data frame?

```{r}

```

4.  `starwars` is an on-board dataset that comes with the tidyverse. Insert a new code chunk and display that data.

5.  Copy and paste the following code into a new code chunk in your new file.

```{r}
starwars %>% 
  ggplot(aes(fct_infreq(hair_color))) + 
  geom_bar() + 
  ggtitle("Hair color frequency for Star Wars Characters")
```

### BONUS 1

6.  Take a look at the structure of the `brodhead` object.

    -   How many observations (rows) are there?
    -   How many variables (columns) are there?
    -   How many of the variables are numeric data?

    HINT: You can use the `glimpse()` function

> ANSWER can be found in exercise_00_answers.Rmd file

### BONUS 2

1.  Import SPSS data containing labeled vectors: `data/student_satisfaction_test_data_from_qualtrics.sav`

2.  Convert the labeled vector field `Q2` to its labeled values with `haven::as_factor()` and `mutate()`

Hints:

-   The {`here`} package is helpful for navigating to the data directory

-   Notice the data-types of the variables. Using `glimpse()` or simply displaying the data frame, notice the data type: `<S3: haven_labelled>` used for some columns.

```{r}
library(haven)
library(here)

my_labeled_vectors_df <- 
  read_sav(here("data", "student_satisfaction_test-data_from_qualtrics.sav"))
```

```{r}
my_labeled_vectors_df

my_labeled_vectors_df |> 
  select(Q2) |> 
  mutate(Q2_labels = _________(Q2))
```