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week_04/case_study04.Rmd

@@ -0,0 +1,49 @@
+---
+title: "Case Study 04"
+author: Eleanor M. Byrne 
+output: html_document
+---
+
+## Packages/Lib
+
+Comments
+
+```{r}
+# This is for library/packages
+# install/load packages 
+library(tidyverse)
+# install.packages('nycflights13')
+library(nycflights13)
+library(dplyr)
+```
+
+## Opening/Data/information
+
+```{r}
+# Open and access the nyc flights 
+airports <- nycflights13::airports
+flights <- nycflights13::flights
+```
+
+```{r}
+# Find the maximum distance and the corresponding destination airport code
+highest <- flights %>%
+  arrange(desc(distance)) %>%
+  slice(1) %>% 
+  select(dest, distance)
+# It would be HNL (dest)
+```
+
+```{r}
+# Join with airports data to get the full name of the airport
+farthest_airport_data <- highest %>%
+  left_join(airports, by = c("dest" = "faa")) %>%
+  select(name) # select the the destName column only 
+```
+
+```{r}
+# Convert the data.frame to a single character value with as.character()
+farthest_airport <- as.character(farthest_airport_data$name)
+# Print the farthest airport name
+farthest_airport
+```

week_05/case_study05.Rmd

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+---
+title: "Case Study 05"
+author: Eleanor M. Byrne 
+date: August 1, 2020
+output: github_document
+---
+
+## Packages/Libraries
+
+```{r}
+# Step 1 
+  # download the libraries/packages 
+#install.packages("spData")
+#install.packages("sf")  
+#install.packages("tidyverse")
+#install.packages("units")
+
+library(spData)
+library(sf)
+library(tidyverse)
+library(units)
+```
+
+### Download the data/Read
+```{r}
+# download the data 
+data(world) # this is the data from the spData package 
+  # load the lad 
+data(us_states)
+
+# Step 2
+albers="+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs"
+  # transform to the albers equal area projection 
+  # # Transform world dataset to Albers Equal Area projection
+world_albers <- st_transform(world, crs = albers)
+  # Canada
+  # Filter the world dataset to include only Canada
+canada <- world_albers %>% 
+  filter(name_long == "Canada") # filter the world dataset for Canada 
+  # Set to 10km (10000m)
+# Buffer Canada by 10 km (10000 meters)
+canada_buffer <- st_buffer(canada, dist = 10000)
+  # plot using ggplot 
+ggplot() +
+  geom_sf(data = canada_buffer, fill = "lightblue", color = "black") +
+  ggtitle("Buffered Area of Canada (10 km)") +
+  theme_minimal()
+```
+### New York setup
+```{r}
+# Step 3
+  # Create one for New York 
+# transform us_states dataset to the same Albers projection
+us_states_albers <- st_transform(us_states, crs = albers)
+
+  # filter for NY
+new_york <- us_states_albers %>% 
+  filter(NAME == "New York") # New York and use the us_states_albers 
+  # Create border object by intersecting Canada buffer with New York
+
+border <- st_intersection(canada_buffer, new_york)
+```
+### Plotting 
+```{r}
+# Step 4
+  # Plot using ggplot and geom_sf()
+# Plot the border area using ggplot2
+ggplot() +
+  geom_sf(data = new_york, fill = 'blue', color = "red") +  # New York outline
+  geom_sf(data = border, fill = "yellow", color = "black") +  # Intersection area
+  ggtitle("Border Area Between Canada and New York") +
+  theme_minimal()
+
+# Step 5
+  # Calculate the area of the intersected polygon
+area_sq_m <- st_area(border) # Area in square meters
+  # Convert to km^2
+area_sq_km <- set_units(area_sq_m, km^2)
+  # Print the area in square kilometers
+print(area_sq_km)
+```
+

week_06/case_study06.Rmd

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+---
+title: "Case Study 06"
+author: Eleanor M. Byrne 
+date: August 1, 2020
+output: html_document
+---
+
+ ### Packages/Libraries 
+```{r}
+library(terra)
+library(spData)
+library(tidyverse)
+library(sf)
+library(ncdf4)
+```
+
+ ### Data
+```{r}
+download.file("https://crudata.uea.ac.uk/cru/data/temperature/absolute.nc","crudata.nc", method="curl") # add the curl if there are issues
+
+# read in the data using the rast() function from the terra package
+tmean=rast("crudata.nc")
+
+# Inspect the tmean object
+print(tmean)
+plot(tmean)
+```
+### Calculate the Maximum Temperature Observed:
+```{r}
+# Step 2: Calculate the maximum value
+tmean_max <- max(tmean)
+
+# Plot the maximum temperature to visualize the new raster layer
+plot(tmean_max, main = "Maximum Temperature")
+
+# Step 3: Extract the maximum temperature observed in each country
+# Use terra::extract() to get the maximum temperature for each country
+max_temp_per_country <- terra::extract(tmean_max, world, fun = max, na.rm = TRUE, small = TRUE)
+
+# Bind the original world dataset with the new summary of the temperature data
+world_clim <- bind_cols(world, max_temp_per_country)
+
+# Rename the column for clarity
+colnames(world_clim)[ncol(world_clim)] <- "max_temp"
+```
+### Communicate your results 
+```{r}
+# Plot the maximum temperature in each country polygon
+ggplot(world_clim) +
+  geom_sf(aes(fill = max_temp), color = "black") +
+  scale_fill_viridis_c(name = "Maximum\nTemperature (C)") +
+  theme_minimal() +
+  theme(legend.position = 'bottom') +
+  ggtitle("Maximum Temperature in Each Country")
+
+# Find the hottest country in each continent
+hottest_continents <- world_clim %>%
+  group_by(continent) %>%
+  slice_max(order_by = max_temp, n = 1) %>%
+  select(name_long, continent, max_temp) %>%
+  arrange(desc(max_temp)) %>%
+  st_set_geometry(NULL)
+
+# Print the hottest country in each continent
+print(hottest_continents)
+```

week_07/case_study07.Rmd

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+---
+title: "Case Study 07"
+author: Eleanor M. Byrne 
+format: html
+editor: visual
+---
+ ### Library/Packages
+```{r}
+# library and packages 
+library(tidyverse)
+library(reprex)
+library(sf)
+
+library(spData)
+data(world)
+```
+ ### Practice plot
+```{r}
+ggplot(world,aes(x=gdpPercap, y=continent, color=continent))+
+   geom_density(alpha=0.5,color=F)
+```
+ ### The Corrected Plot 
+```{r}
+# Corrected code to achieve the desired figure
+ggplot(world, aes(x = gdpPercap, fill = continent)) +
+  geom_density(alpha = 0.5) +
+  labs(title = "Distribution of GDP per Capita by Continent",
+       x = "GDP per Capita",
+       y = "Density") +
+  theme_minimal()
+```
+ ### Copy the Code to Your Clipboard
+```{r}
+reprex({
+  # Load necessary libraries
+  library(tidyverse)
+  library(sf)
+  library(spData)
+  
+  # Load the world data
+  data(world)
+  
+  # Your initial code with corrections
+  ggplot(world, aes(x = gdpPercap, fill = continent)) +
+    geom_density(alpha = 0.5) +
+    labs(title = "Distribution of GDP per Capita by Continent",
+         x = "GDP per Capita",
+         y = "Density") +
+    theme_minimal()
+}, venue = "gh")
+
+```
+ ### Post as an ‘issue’ in github 
+```{r}
+
+```
+
+

week_08/case_study08.Rmd

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+---
+title: "Case Study 08"
+author: Eleanor M. Byrne 
+output: html_document
+---
+
+# The website
+
+The website was created and the link is https://github.com/AdamWilsonLabEDU/final-project-embyrne0

week_09/Case_Study9.Rmd

@@ -1,7 +1,7 @@
 ---
-title: "Case_Study9"
+title: "Case Study 09"
+author: Eleanor M. Byrne 
 output: html_document
-date: "2024-10-29"
 ---
 
 ```{r setup, include=FALSE}
@@ -59,6 +59,7 @@ sf_stormdata <- storm_data %>%
 region <- st_bbox(sf_stormdata)
 print(region) # this is the bbox, the boundary/shapefile 
 ```
+
 ```{r}
 # This is for the ggplot 
   # use the world plot 
@@ -109,8 +110,6 @@ states_5 <- storm_counts %>%
 print(states_5)
 ```
 
-
-
 ## Including Plots
 
 You can also embed plots, for example: