WorkShop

The data set selected for this work shop was the population of electric vehicles in Washington State

EVP <- read.csv("C:/Users/Ozili Nwokobia/Downloads/Electric_Vehicle_Population_Data.csv", header=FALSE, stringsAsFactors=TRUE)
View(EVP)

Question 1: Will battery electric vehicles be more popular compared to hybrid plug-in because fully electric cars have the reputation of being more eco-friendly?

library(ggplot2)
ev_type_counts <- as.data.frame(table(EVP$V9))

View(ev_type_counts)

colnames(ev_type_counts) <- c("Type", "Count")

pie_chart <- ggplot(ev_type_counts, aes(x = "", y = Count, fill = Type)) +
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y", start = 0) +
  theme_void() +
  labs(title = "Distribution of Electric Vehicle Types") +
  scale_fill_brewer(palette = "Set3")

print(pie_chart)

Question 2: Will Tesla have the most electric cars on the road since their entire vehicle line up is only electric vehicles and they’re the most popular brand of electric cars?

library(viridis)

## Warning: package 'viridis' was built under R version 4.3.3

## Loading required package: viridisLite

make_counts <- as.data.frame(table(EVP$V7))

colnames(make_counts) <- c("Make", "Count")

pie_chart_make <- ggplot(make_counts, aes(x = "", y = Count, fill = Make)) +
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y", start = 0) +
  theme_void() +
  labs(title = "Distribution of Electric Vehicle Makes") +
  scale_fill_viridis(discrete = TRUE, option = "D")
print(pie_chart_make)

line_graph <- ggplot(make_counts, aes(x = Make, y = Count, group = 1)) +
  geom_line(aes(color = Make)) +
  geom_point(aes(color = Make)) +
  theme_minimal() +
  labs(title = "Count of Electric Vehicles by Make",
       x = "Vehicle Make",
       y = "Count") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  scale_color_viridis_d(option = "D", guide = FALSE)
print(line_graph)

## Warning: The `guide` argument in `scale_*()` cannot be `FALSE`. This was deprecated in
## ggplot2 3.3.4.
## ℹ Please use "none" instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Question 3: Will Seattle have the most electric Vehicles because they have the largest population in Washington State?

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

city_counts <- as.data.frame(table(EVP$V3))

colnames(city_counts) <- c("City", "Count")

top_cities <- city_counts %>% 
  arrange(desc(Count)) %>% 
  head(10)
bar_graph_city <- ggplot(top_cities, aes(x = reorder(City, -Count), y = Count, fill = City)) +
  geom_bar(stat = "identity") +
  theme_minimal() +
  labs(title = "Top 10 Cities with Electric Cars",
       x = "City",
       y = "Count") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  scale_fill_viridis_d(option = "D", guide = FALSE)

print(bar_graph_city)