# install.packages("tidyverse")
library(tidyverse)
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v tibble 3.1.6 v dplyr 1.0.7
v tidyr 1.1.4 v stringr 1.4.0
v readr 2.1.1 v forcats 0.5.1
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x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()
airquality <- airquality
str(airquality)
## 'data.frame': 153 obs. of 6 variables:
## $ Ozone : int 41 36 12 18 NA 28 23 19 8 NA ...
## $ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 ...
## $ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ...
## $ Temp : int 67 72 74 62 56 66 65 59 61 69 ...
## $ Month : int 5 5 5 5 5 5 5 5 5 5 ...
## $ Day : int 1 2 3 4 5 6 7 8 9 10 ...
‘data.frame’: 153 obs. of 6 variables:
$ Ozone : int 41 36 12 18 NA 28 23 19 8 NA …
$ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 …
$ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 …
$ Temp : int 67 72 74 62 56 66 65 59 61 69 …
$ Month : int 5 5 5 5 5 5 5 5 5 5 …
$ Day : int 1 2 3 4 5 6 7 8 9 10 …
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"
str(airquality)
## 'data.frame': 153 obs. of 6 variables:
## $ Ozone : int 41 36 12 18 NA 28 23 19 8 NA ...
## $ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 ...
## $ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ...
## $ Temp : int 67 72 74 62 56 66 65 59 61 69 ...
## $ Month : chr "May" "May" "May" "May" ...
## $ Day : int 1 2 3 4 5 6 7 8 9 10 ...
‘data.frame’: 153 obs. of 6 variables:
$ Ozone : int 41 36 12 18 NA 28 23 19 8 NA …
$ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 …
$ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 …
$ Temp : int 67 72 74 62 56 66 65 59 61 69 …
$ Month : chr “May” “May” “May” “May” …
$ Day : int 1 2 3 4 5 6 7 8 9 10 …
summary(airquality)
## Ozone Solar.R Wind Temp
## Min. : 1.00 Min. : 7.0 Min. : 1.700 Min. :56.00
## 1st Qu.: 18.00 1st Qu.:115.8 1st Qu.: 7.400 1st Qu.:72.00
## Median : 31.50 Median :205.0 Median : 9.700 Median :79.00
## Mean : 42.13 Mean :185.9 Mean : 9.958 Mean :77.88
## 3rd Qu.: 63.25 3rd Qu.:258.8 3rd Qu.:11.500 3rd Qu.:85.00
## Max. :168.00 Max. :334.0 Max. :20.700 Max. :97.00
## NA's :37 NA's :7
## Month Day
## Length:153 Min. : 1.0
## Class :character 1st Qu.: 8.0
## Mode :character Median :16.0
## Mean :15.8
## 3rd Qu.:23.0
## Max. :31.0
##
Ozone Solar.R Wind Temp
Min. : 1.00 Min. : 7.0 Min. : 1.700 Min. :56.00
1st Qu.: 18.00 1st Qu.:115.8 1st Qu.: 7.400 1st Qu.:72.00
Median : 31.50 Median :205.0 Median : 9.700 Median :79.00
Mean : 42.13 Mean :185.9 Mean : 9.958 Mean :77.88
3rd Qu.: 63.25 3rd Qu.:258.8 3rd Qu.:11.500 3rd Qu.:85.00
Max. :168.00 Max. :334.0 Max. :20.700 Max. :97.00
NA’s :37 NA’s :7
Month Day
Length:153 Min. : 1.0
Class :character 1st Qu.: 8.0
Mode :character Median :16.0
Mean :15.8
3rd Qu.:23.0
Max. :31.0
airquality$Month<-factor(airquality$Month, levels=c("May", "June","July", "August", "September"))
p1 <- qplot(data = airquality,Temp,fill = Month,geom = "histogram", bins = 20)
p1
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"))
p2
p3 <- airquality %>%
ggplot(aes(Month, Temp, fill = Month)) +
ggtitle("Temperatures") +
xlab("Monthly Temperatures") +
ylab("Frequency") +
geom_boxplot() +
scale_fill_discrete(name = "Month", labels = c("May", "June","July", "August", "September"))
p3
p4 <- airquality %>%
ggplot(aes(Month, Temp, fill = Month)) +
ggtitle("Monthly Temperature Variations") +
xlab("Monthly Temperatures") +
ylab("Frequency") +
geom_boxplot()+
scale_fill_grey(name = "Month", labels = c("May", "June","July", "August", "September"))
p4
p5 <- airquality %>%
ggplot(aes(Month, Temp, color = Month)) +
ggtitle("Monthly Temperature Variations") +
xlab("Monthly Temperatures") +
ylab("Frequency") +
scale_fill_discrete(name = "Month", labels = c("May", "June","July", "August", "September")) +
geom_point(aes(size = Ozone))
p5
## Warning: Removed 37 rows containing missing values (geom_point).
