Seeing which work, and to get a total of observations and
variables
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")
Question 6
str(bike1)
## 'data.frame': 17379 obs. of 13 variables:
## $ datetime : chr "1/1/2011 0:00" "1/1/2011 1:00" "1/1/2011 2:00" "1/1/2011 3:00" ...
## $ season : int 1 1 1 1 1 1 1 1 1 1 ...
## $ holiday : int 0 0 0 0 0 0 0 0 0 0 ...
## $ workingday: int 0 0 0 0 0 0 0 0 0 0 ...
## $ weather : int 1 1 1 1 1 2 1 1 1 1 ...
## $ temp : num 9.84 9.02 9.02 9.84 9.84 ...
## $ atemp : num 14.4 13.6 13.6 14.4 14.4 ...
## $ humidity : chr "81" "80" "80" "75" ...
## $ windspeed : num 0 0 0 0 0 ...
## $ casual : int 3 8 5 3 0 0 2 1 1 8 ...
## $ registered: int 13 32 27 10 1 1 0 2 7 6 ...
## $ count : int 16 40 32 13 1 1 2 3 8 14 ...
## $ sources : chr "ad campaign" "www.yahoo.com" "www.google.fi" "AD campaign" ...
Indexing for Question 7
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
Contingency table for Question 8
sort(table(bike1$season), decreasing = TRUE)
##
## 3 2 1 4
## 4496 4409 4242 4232
Subsetting Question 10
subset(bike1, windspeed >= 40 & season %in% c("1", "4"))
## datetime season holiday workingday weather temp atemp humidity
## 1008 2/14/2011 15:00 1 0 1 1 22.96 26.515 21
## 1010 2/14/2011 17:00 1 0 1 1 18.86 22.725 33
## 1011 2/14/2011 18:00 1 0 1 1 16.40 20.455 40
## 1015 2/14/2011 22:00 1 0 1 1 13.94 14.395 46
## 1018 2/15/2011 1:00 1 0 1 1 12.30 12.120 42
## 1019 2/15/2011 2:00 1 0 1 1 11.48 11.365 41
## 1120 2/19/2011 9:00 1 0 0 1 16.40 20.455 16
## 1124 2/19/2011 13:00 1 0 0 1 18.04 21.970 16
## 1125 2/19/2011 14:00 1 0 0 1 18.86 22.725 15
## 1126 2/19/2011 15:00 1 0 0 1 18.04 21.970 16
## 1127 2/19/2011 16:00 1 0 0 1 18.04 21.970 16
## 1128 2/19/2011 17:00 1 0 0 1 17.22 21.210 19
## 1259 2/25/2011 14:00 1 0 1 3 22.96 26.515 56
## 1260 2/25/2011 15:00 1 0 1 1 18.86 22.725 41
## 1262 2/25/2011 17:00 1 0 1 1 13.12 13.635 49
## 1265 2/25/2011 20:00 1 0 1 1 12.30 12.880 49
## 1333 2/28/2011 19:00 1 0 1 3 18.04 21.970 88
## 1334 2/28/2011 20:00 1 0 1 3 18.04 21.970 88
## 1478 3/6/2011 21:00 1 0 0 3 9.84 9.090 93
## 8068 12/7/2011 19:00 4 0 1 3 13.94 14.395 87
## 8069 12/7/2011 20:00 4 0 1 3 13.94 14.395 87
## 8706 1/3/2012 13:00 1 0 1 1 7.38 6.060 34
## 8943 1/13/2012 11:00 1 0 1 1 9.84 9.090 38
## 9644 2/11/2012 18:00 1 0 0 2 9.02 9.090 47
## 9647 2/11/2012 21:00 1 0 0 1 5.74 3.790 43
## 9653 2/12/2012 3:00 1 0 0 2 4.10 2.275 46
## 9654 2/12/2012 4:00 1 0 0 2 4.10 2.275 46
## 9662 2/12/2012 12:00 1 0 0 1 5.74 3.790 39
## 9957 2/24/2012 21:00 1 0 1 1 17.22 21.210 35
## 9959 2/24/2012 23:00 1 0 1 1 15.58 19.695 37
## 9971 2/25/2012 11:00 1 0 0 1 12.30 12.880 39
## 9972 2/25/2012 12:00 1 0 0 1 13.12 13.635 29
## 10169 3/4/2012 18:00 1 0 0 1 13.12 13.635 33
## 10193 3/5/2012 18:00 1 0 1 3 11.48 11.365 55
## 10260 3/8/2012 13:00 1 0 1 2 24.60 31.060 49
## 10261 3/8/2012 14:00 1 0 1 2 25.42 31.060 43
## 10262 3/8/2012 15:00 1 0 1 1 26.24 31.060 38
## 10263 3/8/2012 16:00 1 0 1 2 25.42 31.060 41
## 10264 3/8/2012 17:00 1 0 1 1 25.42 31.060 38
## 10290 3/9/2012 19:00 1 0 1 1 17.22 21.210 28
## 16208 11/13/2012 1:00 4 0 1 3 18.04 21.970 88
## 16473 11/24/2012 2:00 4 0 0 1 13.12 13.635 39
## 16483 11/24/2012 12:00 4 0 0 2 12.30 12.880 36
## 17150 12/22/2012 8:00 1 0 0 1 10.66 10.605 44
## 17154 12/22/2012 12:00 1 0 0 1 12.30 12.880 36
## 17345 12/30/2012 13:00 1 0 0 1 12.30 12.880 36
## windspeed casual registered count sources
## 1008 43.9989 19 71 90 www.google.co.uk
## 1010 40.9973 25 218 243 ad campaign
## 1011 40.9973 11 194 205 ad campaign
## 1015 43.9989 1 44 45 www.google.co.uk
## 1018 51.9987 0 5 5 www.google.fi
## 1019 46.0022 1 2 3 www.google.fi
## 1120 43.9989 18 37 55 Ad Campaign
## 1124 40.9973 52 103 155 Twitter
## 1125 43.9989 102 94 196 Twitter
## 1126 50.0021 84 87 171 ad campaign
## 1127 43.0006 39 81 120 blog
## 1128 40.9973 36 91 127 Ad Campaign
## 1259 40.9973 22 55 77 www.bing.com
## 1260 54.0020 31 98 129 www.google.co.uk
## 1262 50.0021 13 180 193 www.google.com
## 1265 40.9973 3 66 69 direct
## 1333 40.9973 8 76 84 Twitter
## 1334 40.9973 8 47 55 facebook page
## 1478 40.9973 1 6 7 ad campaign
## 8068 43.0006 2 31 33 ad campaign
## 8069 43.0006 1 25 26 Twitter
## 8706 43.9989 5 68 73 www.google.co.uk
## 8943 40.9973 12 102 114 www.yahoo.com
## 9644 43.9989 3 105 108 <NA>
## 9647 43.0006 5 43 48 Twitter
## 9653 46.0022 0 14 14 www.yahoo.com
## 9654 47.9988 0 1 1 www.bing.com
## 9662 43.0006 7 133 140 ad campaign
## 9957 54.0020 12 138 150 ad campaign
## 9959 46.0022 9 71 80 Twitter
## 9971 40.9973 29 155 184 www.google.com
## 9972 43.9989 49 218 267 www.google.com
## 10169 40.9973 20 164 184 <NA>
## 10193 43.9989 12 363 375 www.yahoo.com
## 10260 43.0006 35 198 233 www.bing.com
## 10261 43.0006 48 155 203 ad campaign
## 10262 46.0022 24 161 185 ad campaign
## 10263 43.0006 37 305 342 AD campaign
## 10264 43.9989 52 545 597 blog
## 10290 40.9973 12 232 244 www.google.fi
## 16208 43.0006 0 5 5 Twitter
## 16473 40.9973 5 29 34 facebook page
## 16483 40.9973 39 227 266 direct
## 17150 40.9973 8 75 83 ad campaign
## 17154 43.9989 30 169 199 www.yahoo.com
## 17345 43.9989 28 152 180 ad campaign