---
title: "161.324 Data Mining"
subtitle: "Assignment 1, 2025"
author: "YOUR NAME GOES HERE"
output: html_document
---

```{r setup, echo=TRUE, warning=FALSE, message=FALSE}
# Add any other packages you need to load here.
library(tidyverse)

# Read in the data
uksun <- read_csv("https://www.massey.ac.nz/~jcmarsha/161324/assessment/data/uksun.csv")
woops <- read_csv("https://www.massey.ac.nz/~jcmarsha/161324/assessment/data/woops2025.csv")
```

## Exercise 1: Exploratory analysis of UK weather records

### 1.1. Missing values

```{r}

```

### 1.2. Mean sunshine hours

```{r}

```

### 1.3. Mean rainfall per month

```{r}

```

### 1.4. Reproduce the graphic

```{r}

```


## Exercise 2: Imputation of UK weather records

### 2.1. Histogram of mean imputed July sunshine hours in Durham city

```{r}

```

### 2.2. Standard deviation before and after mean imputation

```{r}

```

### 2.3. k-Nearest neighbour imputation scatterplots

```{r}

```


## Exercise 3: Woops!

```{r}

```

## Exercise 4: Reflection

WRITE DOWN WHICH SOURCES OF INFORMATION YOU USED, AND REFLECT ON HOW IT WAS USED