Unemployment

---

title: "Unemployment and Crime Rates Dashboard"
format: dashboard
editor: visual
--------------

## Overview

This dashboard presents unemployment trends and crime rate patterns using sample data. Replace the sample datasets with your actual data for real insights.

## Unemployment Rate


::: {.cell}

```{.r .cell-code}
library(ggplot2)

Warning: package 'ggplot2' was built under R version 4.4.3

data_unemployment <- data.frame(
  year = 2015:2024,
  unemployment_rate = c(24.3, 25.0, 26.5, 27.1, 28.0, 29.2, 30.1, 32.5, 33.0, 32.1)
)

ggplot(data_unemployment, aes(x = year, y = unemployment_rate)) +
  geom_line(size = 1) +
  geom_point(size = 2) +
  labs(title = "Unemployment Rate Over Time", x = "Year", y = "Unemployment Rate (%)")

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

:::

Crime Rates

data_crime <- data.frame(
  year = 2015:2024,
  crime_rate = c(3200, 3300, 3500, 3700, 3900, 4200, 4500, 4700, 4900, 5100)
)

ggplot(data_crime, aes(x = year, y = crime_rate)) +
  geom_line(size = 1, color = "red") +
  geom_point(size = 2, color = "red") +
  labs(title = "Crime Rate Over Time", x = "Year", y = "Crime Rate per 100,000 population")

Relationship Between Unemployment and Crime

combined_data <- merge(data_unemployment, data_crime, by = "year")

ggplot(combined_data, aes(x = unemployment_rate, y = crime_rate)) +
  geom_point(size = 3) +
  geom_smooth(method = "lm", se = FALSE) +
  labs(title = "Relationship Between Unemployment and Crime", x = "Unemployment Rate (%)", y = "Crime Rate")

`geom_smooth()` using formula = 'y ~ x'