bike_sharing_data <- read.csv("bike_sharing_data.csv")
summary(bike_sharing_data)
## 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
##
##
##
value of season in row 6251
bike_sharing_data[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
season_table <- table(bike_sharing_data$season)
print(season_table)
##
## 1 2 3 4
## 4242 4409 4496 4232
count_winter <- season_table["Winter"]
bike2 <- read.table("bike_sharing_data.txt", sep="\t", header=TRUE)
bike1 <- read.table("bike_sharing_data.csv", sep=",", header=TRUE)
bike4 <- read.delim("bike_sharing_data.txt")
bike3 <- read.csv("bike_sharing_data.csv")
winter_spring_data <- bike_sharing_data[bike_sharing_data$season %in% c(1, 4), ]
high_wind_data <- winter_spring_data[winter_spring_data$windspeed >= 40, ]
num_observations <- nrow(high_wind_data)
print(num_observations)
## [1] 46