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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

data <- read.csv("death-rates-from-air-pollution-2.csv")
data

data2 <- read.csv("owid-co2-data.csv")
data2

library(dplyr)
library(ggplot2)

data_table <- data %>% 
  filter(Country %in% c("United States"))
data_table

data_table2 <- data2 %>% 
  filter(country %in% c("United States"))
data_table2

NA

library(ggthemes)

ggplot(data_table, aes(x = Year, y = Air.pollution..total...deaths.per.100.000., group = Country, color = Country)) +
  labs(y = "Air Pollution (Total Deaths Per 100,000)", x = "Year", 
       title = "Change in Death Rate of Air Pollution Over Time in the United States",
       color = "Country")+
  geom_line(size = 1.5) +
  
  theme_minimal()

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

ggplot(data_table2) +
  geom_line(aes(y = co2_per_capita, x = year, color = "Carbon Dioxide Emissions (Overall)")) +
  geom_line(aes(y = gas_co2_per_capita, x = year, color = "Carbon Dioxide Emissions (Gas)")) +
  labs(y = "Carbon Dioxide Emissions Per Capita", x = "Year", 
       title = "Change in Carbon Dioxide Emissions Per Capita Over Time in the United States",
       color = "Emissions") +
  scale_color_manual(labels = c("Carbon Dioxide Emissions (Overall)", "Carbon Dioxide Emissions (Gas)"), values = c("red", "blue")) +
  
  theme_classic()

data_table3 <- data_table2
data_table3[data_table3$year >= 1990 & data_table2$year <= 2020,]

ggplot(data_table3[data_table3$year >= 1990 & data_table2$year <= 2020,], aes(x = year, y = nitrous_oxide_per_capita, group = country, color = country)) +
  labs(y = "Nitrous Oxide Emissions Per Capita", x = "Year", 
       title = "Change in Nitrous Oxide Emissions Per Capita Over Time in the United States",
       color = "Country")+
  geom_line(size = 1.5) +
  
  theme_light()

data_table4 <- data_table3
data_table4[data_table4$year %in% c('1800', '1850', '1900', '1950', '2000'), ]

year <- c("1850", "1850", "1900", "1900", "1950", "1950", "2000", "2000")
co2 <- c("Overall","Gas",
            "Overall","Gas", "Overall","Gas", "Overall","Gas")
amount <- c(19.793, 0.000, 662.738, 11.542, 2541.485, 319.219, 6010.136, 1251.263)

circle <- data.frame(amount,year,co2)

ggplot(circle, aes(year, amount, fill = co2)) +
  geom_bar(stat="identity", position = "dodge") +
  labs(y = "Amount in Million Metric Tons", x = "Year", 
       title = "Amount of Carbon Dioxide Released in the United States From 1850 to 2000",
       color = "Carbon Dioxide", fill = "Carbon Dioxide")

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