AirQualityAssignment4

Air Quality Assignment

Daniel Johnson

library(tidyverse)
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✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.0.4     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Load in the airquality dataset

data("airquality")

Show the beginning of the data to make sure it’s there

head(airquality)
  Ozone Solar.R Wind Temp Month Day
1    41     190  7.4   67     5   1
2    36     118  8.0   72     5   2
3    12     149 12.6   74     5   3
4    18     313 11.5   62     5   4
5    NA      NA 14.3   56     5   5
6    28      NA 14.9   66     5   6

Example on how to do basic statistics on the dataset

mean(airquality$Temp)
[1] 77.88235
mean(airquality[,4]) 
[1] 77.88235
median(airquality$Temp)
[1] 79
sd(airquality$Wind)
[1] 3.523001
var(airquality$Wind)
[1] 12.41154
airquality$Month[airquality$Month == 5]<- "May"
airquality$Month[airquality$Month == 6]<- "June"
airquality$Month[airquality$Month == 7]<- "July"
airquality$Month[airquality$Month == 8]<- "August"
airquality$Month[airquality$Month == 9]<- "September"
summary(airquality$Month)
   Length     Class      Mode 
      153 character character 
airquality$Month<-factor(airquality$Month, 
                         levels=c("May", "June","July", "August",
                                  "September"))
p1 <- airquality |>
  ggplot(aes(x=Temp, fill=Month)) +
  geom_histogram(position="identity")+
  scale_fill_discrete(name = "Month", 
                      labels = c("May", "June","July", "August", "September")) +
  labs(x = "Monthly Temperatures from May - Sept", 
       y = "Frequency of Temps",
       title = "Histogram of Monthly Temperatures from May - Sept, 1973",
       caption = "New York State Department of Conservation and the National Weather Service")  #provide the data source
p1
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

p2 <- airquality |>
  ggplot(aes(x=Temp, fill=Month)) +
  geom_histogram(position="identity", alpha=0.5, binwidth = 5, color = "white")+
  scale_fill_discrete(name = "Month", labels = c("May", "June","July", "August", "September")) +
  labs(x = "Monthly Temperatures from May - Sept", 
       y = "Frequency of Temps",
       title = "Histogram of Monthly Temperatures from May - Sept, 1973",
       caption = "New York State Department of Conservation and the National Weather Service")
p2

p3 <- airquality |>
  ggplot(aes(Month, Temp, fill = Month)) + 
  labs(x = "Months from May through September", y = "Temperatures", 
       title = "Side-by-Side Boxplot of Monthly Temperatures",
       caption = "New York State Department of Conservation and the National Weather Service") +
  geom_boxplot() +
  scale_fill_discrete(name = "Month", labels = c("May", "June","July", "August", "September"))
p3

p4 <- airquality |>
ggplot(aes(Month, Temp, fill = Month)) + 
  labs(x = "Monthly Temperatures", y = "Temperatures", 
       title = "Side-by-Side Boxplot of Monthly Temperatures",
       caption = "New York State Department of Conservation and the National Weather Service") +
  geom_boxplot()+
  scale_fill_grey(name = "Month", labels = c("May", "June","July", "August", "September"))
p4

p5 <- airquality |> 
  ggplot(aes(Month, Wind, fill = Month)) + 
  labs(x = "Monthly Wind Speed", y = "Wind Speed", 
       title = "Comparison of Wind Speed Data By Month", 
       capiton = "New York State Department of Conservation and the National Weather Service") + 
  geom_boxplot() + 
  scale_fill_discrete(name = "Month", labels = c("May", "June", "July", "August", "September"))
p5

This plot is similar to plot 3, in that it is a boxplot by month, but instead of temperature it shows wind by month. I wanted to combine this with the previous p3 to see if temperature affected wind, but I couldn’t figure out how to do so. Instead, if you look at both you can see that as the temperature goes up the wind speed tends to go down. In terms of special code, there isn’t really any, I changed p3 to be about wind instead of temperature. I had a lot of trouble making this (if you looked at discord you probably saw) and this was about all I could manage, and even then this ended up being the 4th version of the file because at different points along the way I managed to mess stuff up and I had to restart.