---
title: "Week 3 Assignment"
author: Kathy Qi
date: "2025-04-18"
output: 
  html_document:
      css: splendor.css
      toc: true
      toc_float: true
      number_sections: true
      code_folding: show
---

```{r setup, include=FALSE}
# uses CSS file downloaded from https://github.com/nwstephens/rmdcss/tree/master
knitr::opts_chunk$set(echo = TRUE, warning= FALSE, message = FALSE)
```

## Introduction

This is a practice markdown file for my **project**. It will contain the following:

1.  Code
2.  Plots
3.  Analysis
4.  Interpretations

## Load packages
```{r}
library("stringr")
library("dplyr")
library("maps")
library("readr")
library("ggplot2")
```

## Code to read in sample metadata
```{r}
## read in metadata and only grab data from diel study
metadata <- read.csv('../project/metadata/sample_metadata.csv')
diel <- metadata[str_detect(metadata$SampleID, "DIEL"), ]
```
Surface samples (15 m) are taken every ~3-4 hours across 3 days. 


## Plot map
```{r map}
# Calculate average latitude and longitude
avg_coords <- diel %>%
  summarise(
    avg_lat = mean(Latitude, na.rm = TRUE),
    avg_lon = mean(Longitude, na.rm = TRUE)
  )

# Get world map data (for a simple ocean/land basemap)
world_map <- map_data("world")

# Set plot limits to focus on your study region
lon_buffer <- 20
lat_buffer <- 20
lon_min <- min(diel$Longitude) - lon_buffer
lon_max <- max(diel$Longitude) + lon_buffer
lat_min <- min(diel$Latitude) - lat_buffer - 5
lat_max <- max(diel$Latitude) + lat_buffer

# Plot
ggplot() +
  geom_polygon(data = world_map, aes(x = long, y = lat, group = group),
               fill = "grey90", color = "grey70", size = 0.3) +
  coord_fixed(xlim = c(lon_min, lon_max), ylim = c(lat_min, lat_max)) +
  geom_point(data = avg_coords, aes(x = avg_lon, y = avg_lat),
             color = "red", size = 5, shape = 21, fill = "red", alpha = 0.8) +
  labs(
    title = "G3 Diel Study",
    x = "Longitude",
    y = "Latitude"
  ) +
  theme_minimal(base_size = 14)
```

Study site is located in the North Pacific Transition Zone.