BLCC

knitr::opts_chunk$set(echo = TRUE)

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Note that the echo = TRUE parameter was added to the code chunk to prevent printing of the R code that generated the plot. install.packages(‘dplyr’) install.packages(“kableExtra”) install.packages(“readr”) install.packages(“tidyverse”) install.packages(“tidyr”) install.packages(“ggplot2”) install.packages(“ggmap”) install.packages(“data.table”) install.packages(“vtable”) install.packages(“magrittr”) install.packages(“girafe”) library(dplyr) library(kableExtra) library(vtable) vtable(zip_info, lush = TRUE) library(magrittr) library(readr) library(tidyverse) library(tidyr) library(ggplot2) library(ggmap) library(data.table) library(girafe)

this data shows that those that are less represented feel less safe.

relevant_data <- data[, c(“Do you feel safe at SU? Rate on a scale of 1-5 (1 being you DON’T feel safe, 5 being you feel safe)”, “What has your experience at Albers/SU been like?”)]

Rename the columns for easier reference

colnames(relevant_data) <- c(“Safety_Rating”, “Experience”)

Convert the “Experience” column to lowercase

relevant_data\(Experience <- tolower(relevant_data\)Experience)

Calculate correlation

correlation <- cor.test(relevant_data\(Safety_Rating, as.numeric(factor(relevant_data\)Experience)))

Print correlation coefficient and p-value

print(correlation) filtered_data <- data[data$Race %in% c(“Black”, “Latinx”, “White”), ]

Calculate the average safety rating for each race group

average_safety <- aggregate(data\(`Do you feel safe at SU? Rate on a scale of 1-5 (1 being you DON'T feel safe, 5 being you feel safe)`, by = list(Race = data\)Race), FUN = mean)

Print the average safety ratings for each race group

print(average_safety)

ggplot(average_safety, aes(x = Race, y = x)) + geom_bar(stat = “identity”, fill = “skyblue”) + labs(x = “Race”, y = “Average Safety Rating”, title = “Average Safety Rating by Race”) + theme_minimal()

#An interactive plot graph that shows the answers given in the column “What has your experience at Albers/SU been like?” when hovering over it. but make the x axis the rating/column name “Do you feel safe at SU? Rate on a scale of 1-5 (1 being you DON’T feel safe, 5 being you feel safe)” and the y axis “Race” that uses all the responses given # Load necessary libraries library(plotly) library(readxl)

Load the dataset from Excel

data <- read_excel(“Open Discussion for BLCC (Responses).xlsx”)

Create an interactive scatter plot

plot <- plot_ly(data = data, x = data\(`Do you feel safe at SU? Rate on a scale of 1-5 (1 being you DON'T feel safe, 5 being you feel safe)`, y = data\)Race, text = data$What has your experience at Albers/SU been like?, type = ‘scatter’, mode = ‘markers’, marker = list(size = 10))

Customize layout

plot <- plot %>% layout(title = “Relationship between Feeling of Safety, Race, and Experience at Albers/SU”, xaxis = list(title = “Feeling of Safety at SU”), yaxis = list(title = “Race”))

Show plot

plot

#rows 20-34

Load necessary libraries

library(plotly) library(readxl)

Load the dataset from Excel

data <- read_excel(“Open Discussion for BLCC (Responses).xlsx”)

Specify the range of rows to display (e.g., rows 20 to 34)

selected_data <- data[20:34,]

Create an interactive scatter plot

plot <- plot_ly(data = selected_data, x = ~Do you feel safe at SU? Rate on a scale of 1-5 (1 being you DON'T feel safe, 5 being you feel safe), y = ~Race, text = ~What has your experience at Albers/SU been like?, type = ‘scatter’, mode = ‘markers’, marker = list(size = 10))

Customize layout

plot <- plot %>% layout(title = “Relationship between Feeling of Safety, Race, and Experience at Albers/SU”, xaxis = list(title = “Feeling of Safety at SU”), yaxis = list(title = “Race”))

Show plot with the selected data points

plot