storms_Ghamedi.Rmd

---
title: "storms_Ghamedi"
author: "OGhamedi"
date: "2023-10-27"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r}
source("Setup.R")
```

# Answrering the question: "How have storms changed over time?"

*download .csv of storms*

```{r}
storms_raw <- read_csv("data/storms.csv")
```

# Explore data

```{r}
glimpse(storms_raw)
```

# Organizes data in by Year and Catagory -- all storms in bar plot

```{r}

# Filter out rows with NA in the "category" column
storms_filt <- storms_raw %>%
  filter(!is.na(category))

# Create a bar plot
ggplot(storms_filt, aes(x = factor(year), fill = factor(category))) +
  geom_bar() +
  labs(x = "Year", y = "Count") +
  ggtitle("Bar Plot of Category Count by Year (Excluding NA Values)") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

```

# Visualizing storm status by year in bar plot

```{r}

# Create a bar plot of "status" by year
ggplot(storms_raw, aes(x = factor(year), fill = factor(status))) +
  geom_bar() +
  labs(x = "Year", y = "Count") +
  ggtitle("Bar Plot of Status by Year") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

```

# Re-visulaizing the year vs. status as a line plot

```{r}

# Create a line chart of "status" over time
ggplot(storms_raw, aes(x = year, group = status, color = status)) +
  geom_line(stat = "count") +
  labs(x = "Year", y = "Count") +
  ggtitle("Trend of Storm Status Over Time") +
  scale_color_discrete(name = "Status") +
  theme(legend.position = "top")

```

# Looking at mean wind values by year

```{r}
storm_wind <- storms_raw %>%
      group_by(year) %>%
      summarise(mean_wind = mean(wind, na.rm = TRUE))
```

# Visualise the relationship 

```{r}
storm_wind %>%
  ggplot(aes(x = year, y = mean_wind)) + 
  geom_line()
```

# Histogram of all hurricanes over time w/ density plot 
```{r}
# Filter out rows with NA in the "category" column
hurr_filt <- storms_raw %>%
  filter(status == "hurricane") %>%
  group_by(year)

ggplot(hurr_filt, aes(x=year)) + 
 geom_histogram(aes(y=..density..), colour="black", fill="white")+
 geom_density(alpha=.2, fill="#FF6666") 
```