01-intro-to-vroom.Rmd

```{r intro-to-vroom, include = FALSE}
eval_vroom <- FALSE
if(Sys.getenv("GLOBAL_EVAL") != "") eval_vroom <- Sys.getenv("GLOBAL_EVAL")
```


```{r, include = FALSE, eval = eval_vroom}
library(vroom)
library(fs)
library(purrr)
library(dplyr)
```

# Introduction to `vroom`

## `vroom` basics
*Load data into R using `vroom`*

1. Load the `vroom()` library
    ```{r, eval = eval_vroom}
    library(vroom)
    ```

2. Use the `vroom()` function to read the **transactions_1.csv** file from the **/usr/share/class/files** folder
    ```{r, eval = eval_vroom}
    vroom("/usr/share/class/files/transactions_1.csv")
    ```

3. Use the `id` argument to add the file name to the data frame.  Use **file_name** as the argument's value
    ```{r, eval = eval_vroom}
    
    ```

4. Load the prior command into a variable called `vr_transactions`
    ```{r, eval = eval_vroom}
    
    ```

5. Load the file spec into a variable called `vr_spec`, using the `spec()` command
    ```{r, eval = eval_vroom}
    vr_spec <- spec(vr_transactions)
    
    vr_spec
    ```

## Load multiple files

1. Load the `fs` and `dplyr` libraries
    ```{r, eval = eval_vroom}
    library(fs)
    library(dplyr)
    ```

2. List files in the **/usr/share/class/files** folder using the `dir_ls()` function
    ```{r, eval = eval_vroom}
    dir_ls("/usr/share/class/files")
    ```

3. In the `dir_ls()` function, use the `glob` argument to pass a wildcard to list CSV files only. Load to a variable named `files`
    ```{r, eval = eval_vroom}
    
    ```

4. Pass the `files` variable to `vroom`. Set the `n_max` argument to 1,000 to limit the data load for now
    ```{r, eval = eval_vroom}
    
    ```

5. Add a `col_types` argument with `vr_specs` as its value
    ```{r, eval = eval_vroom}
    
    ```

6. Use the `col_select` argument to pass a `list` object containing the following variables: order_id, date, customer_name, and price
    ```{r, eval = eval_vroom}
    
    ```

## Load and modify multiple files
*For files that are too large to have in memory, keep a summarization*

1. Use a `for()` loop to print the content of each vector inside `files`
    ```{r, eval = eval_vroom}
    for(i in seq_along(files)) {
      print(files[i])
    }
    ```

2. Switch the `print()` command with the `vroom` command, using the same arguments, except the file name.  Use the `files` variable.  Load the results into a variable called `transactions`. 
    ```{r, eval = eval_vroom}
    for(i in seq_along(files)) {

    }
    ```

3. Group `transactions` by `order_id` and get the total of `price` and the number of records. Name them `total_sales` and `no_items` respectively. Name the new variable `orders`
    ```{r, eval = eval_vroom}
    for(i in seq_along(files)) {
      
    }
    ```

4. Define the `orders` variable as `NULL` prior to the for loop and add a `bind_rows()` step to `orders` to preserve each summarized view.
    ```{r, eval = eval_vroom}
    orders <- NULL
    for(i in seq_along(files)) {
      
    }
    ```
    
5. Remove the `transactions` variable at the end of each cycle    
    ```{r, eval = eval_vroom}
    orders <- NULL
    for(i in seq_along(files)) {
      
    }
    ```
    
6. Preview the `orders` variable
    ```{r, eval = eval_vroom}
    orders
    ```