Q4: Data Import
bike1 <- read.table("bike_sharing_data.csv", sep=",", header=TRUE)
bike2 <- read.table("bike_sharing_data.txt", sep="\t", header=TRUE)
bike3 <- read.csv("bike_sharing_data.csv")
bike4 <- read.delim("bike_sharing_data.txt")
Q5: Data summary
summary(bike1)
## datetime season holiday workingday
## Length:17379 Min. :1.000 Min. :0.00000 Min. :0.0000
## Class :character 1st Qu.:2.000 1st Qu.:0.00000 1st Qu.:0.0000
## Mode :character Median :3.000 Median :0.00000 Median :1.0000
## Mean :2.502 Mean :0.02877 Mean :0.6827
## 3rd Qu.:3.000 3rd Qu.:0.00000 3rd Qu.:1.0000
## Max. :4.000 Max. :1.00000 Max. :1.0000
## weather temp atemp humidity
## Min. :1.000 Min. : 0.82 Min. : 0.00 Length:17379
## 1st Qu.:1.000 1st Qu.:13.94 1st Qu.:16.66 Class :character
## Median :1.000 Median :20.50 Median :24.24 Mode :character
## Mean :1.425 Mean :20.38 Mean :23.79
## 3rd Qu.:2.000 3rd Qu.:27.06 3rd Qu.:31.06
## Max. :4.000 Max. :41.00 Max. :50.00
## windspeed casual registered count
## Min. : 0.000 Min. : 0.00 Min. : 0.0 Min. : 1
## 1st Qu.: 7.002 1st Qu.: 4.00 1st Qu.: 36.0 1st Qu.: 42
## Median :12.998 Median : 16.00 Median :116.0 Median :141
## Mean :12.737 Mean : 34.48 Mean :152.5 Mean :187
## 3rd Qu.:16.998 3rd Qu.: 46.00 3rd Qu.:217.0 3rd Qu.:277
## Max. :56.997 Max. :367.00 Max. :886.0 Max. :977
## sources
## Length:17379
## Class :character
## Mode :character
##
##
##
Q7: Indexing
bike1[6251,]
## datetime season holiday workingday weather temp atemp humidity
## 6251 9/23/2011 0:00 4 0 1 2 25.42 27.275 94
## windspeed casual registered count sources
## 6251 6.0032 5 23 28 Ad Campaign
Q8: Contingency Table
sort(table(bike1$season), decreasing = TRUE)
##
## 3 2 1 4
## 4496 4409 4242 4232
Q10: Wind
high_wind_obs <- subset(bike1, season %in% c(1, 4) & windspeed >= 40)
n_high_wind <- nrow(high_wind_obs)
n_high_wind
## [1] 46