Diagnosing Coding Errors with ChatGPT

Introduction

In this assignment, you will learn how to diagnose and resolve coding errors using ChatGPT. As a data analyst, it’s essential to develop the skill of identifying and fixing issues in your code. By using AI-assistants (e.g., ChatGPT) you can find solutions to common coding problems.

Instructions

1. Create a new quarto blog post for this assignment

2. Load the tidyverse package and read in supermarket data set in

```{r}
library(tidyverse)
supermarket_sales <- read_csv("https://bus320-quarto.netlify.app/data/supermarket_sales.csv")
```

The dataset was created using ChatGPT and has the following variables:

  • invoice_id: Unique identifier for each invoice
  • branch: Branch location of the supermarket
  • city: City where the supermarket is located
  • customer_type: Type of customer (Member or Normal)
  • gender: Gender of the customer
  • product_line: Category of the product purchased
  • unit_price: Price per unit of the product
  • quantity: Number of units purchased
  • tax: Tax applied to the purchase
  • total: Total amount of the purchase (includes tax)
  • date: Date of the purchase
  • time: Time of the purchase
  • payment: Payment method used (Cash or Credit card)
  • cogs: Cost of goods sold
  • gross_margin_percentage: Gross margin percentage
  • gross_income: Gross income
  • rating: Customer rating of the purchase

3. Use glimpse to examine the data

  • Insert a code chunk and glimpse the data
```{r}

glimpse(supermarket_sales)

```

4. Calculate total sales by city including tax

  • Chunk with error
  • Note: you need #| eval: false in the chunks with errors so when you render the post it will not evaluate that chunk
```{r}
#| eval: false
supermarket_sales |>
  group_by(city) |>
  summarise(total_sales = sum(total_price))
```
  • The error you receive when running the code is:

Use ChatGPT to identify the error in the code

  • The response from ChatGPT is (put in your own words):

  • Did the response explain the error:

Put the corrected version of the code in a chunk and re-run it.

```{r}

```

5. Count the number of sales by product_line and arrange counts in descending order

  • Chuck with error
```{r}
#| eval: false
supermarket_sales |>
  group_by(product_line) |>
  count() 
  arrange(desc(n))
```
  • The error you receive when running the code is (put in your own words):

Use ChatGPT to identify the error in the code

  • The response from ChatGPT is

  • Did the response explain the error

Put the corrected version of the code in a chunk and re-run it.

```{r}

```

6. Create a horizontal barplot to display the average rating by product line.

```{r}
#| eval: false
supermarket_sales |>
  group_by(product_line) |>
  summarise(mean_rating = mean(rating)) |>
  ggplot(aes(x = mean_rating, y = reorder(product_line, mean_rating))) |>
  geom_col() |>
  labs(y = NULL, x = NULL, title = "Average product rating by product line")

```
  • The error you receive when running the code is:

Use ChatGPT to identify the error in the code

  • The response from ChatGPT is (put in your own words):

  • Did the response explain the error:

Put the corrected version of the code in a chunk and re-run it.

```{r}

```

  1. Did you find the response from ChatGPT was more helpful than the error message? Explain.

  2. How likely are you to use ChatGPT to assist you with programming? (1 = not likely… 5 = very likely) Explain.

Submit the link to your published quarto blog post on Camvas.