Need help with Q3

### Allowable packages

The only allowable package is `tidyverse`. You should not use any other packages as CodeGrade is not set up to accept them on this assignment.

### Data Set

The data set for this assignment is called **`avocados`**. The data was collected by the Hass Avocado Board to track the proce and sales volume of Hass avocados from 2015 to 2023. More information is available on Kaggle [here](https://www.kaggle.com/datasets/vakhariapujan/avocado-prices-and-sales-volume-2015-2023?resource=download).

You are expected to use pipe notation

Before we run our correlations and regressions, we need to clean our data and prepare it for different types of regressions. All of the changes should be made in and saved as the `avocados` dataframe. First, remove all rows for regions at the city and state level and the entire United States. Hint: look at the `region` column for values that do not indicate a region related to city or state; there are eight regions that should remain.

### Next, create a new variable called `type_bin` to convert values in the `type` columns into binary values. Organic avocados should be labeled as `1`. The updated dataframe should include only the following six columns: `Year`, `Month`, `AveragePrice`, `plu4225`, `type_bin`, and `region` (you will use `plu4225` later).

### Finally, save the first five rows of the updated dataframe as Q1

Before moving on, we will check for and remove any outliers in the AveragePrice column. Use the 3SD method to identify and remove outliers from this column; `avocados` should now reflect the data with the outliers removed.

### Save the number of rows in the updated `avocados` dataset (after outlier removal) to Q2.

- Assign the number of rows remaining in the dataframe to Q2

Q3 Create a correlation matrix of the relationships between Year, Month, AveragePrice, and type_bin for the Northeast region.

- Assign the matrix to Q3. It should look something like this:

```

Year Month AveragePrice type_bin

Year [value] [value] [value] [value]

Month [value] [value] [value] [value]

AveragePrice [value] [value] [value] [value]

type_bin [value] [value] [value] [value]