Regression data to predict the total count of bikes rented. Contains 13 features and 17379 observations. Target column is "count".

Source

https://archive.ics.uci.edu/ml/datasets/bike+sharing+dataset

Pre-processing

  • All columns have been renamed.

  • instant, "registered" and "casual" column have been removed.

  • "season" and "weather" have been converted to factor().

  • "holiday" and "working_day" have been converted to logical().

Examples

data("bike_sharing", package = "mlr3data") str(bike_sharing)
#> Classes ‘data.table’ and 'data.frame': 17379 obs. of 14 variables: #> $ date : chr "2011-01-01" "2011-01-01" "2011-01-01" "2011-01-01" ... #> $ season : Factor w/ 4 levels "winter","spring",..: 1 1 1 1 1 1 1 1 1 1 ... #> $ year : int 0 0 0 0 0 0 0 0 0 0 ... #> $ month : int 1 1 1 1 1 1 1 1 1 1 ... #> $ hour : int 0 1 2 3 4 5 6 7 8 9 ... #> $ holiday : logi FALSE FALSE FALSE FALSE FALSE FALSE ... #> $ weekday : int 6 6 6 6 6 6 6 6 6 6 ... #> $ working_day : logi FALSE FALSE FALSE FALSE FALSE FALSE ... #> $ weather : Factor w/ 4 levels "1","2","3","4": 1 1 1 1 1 2 1 1 1 1 ... #> $ temperature : num 0.24 0.22 0.22 0.24 0.24 0.24 0.22 0.2 0.24 0.32 ... #> $ apparent_temperature: num 0.288 0.273 0.273 0.288 0.288 ... #> $ humidity : num 0.81 0.8 0.8 0.75 0.75 0.75 0.8 0.86 0.75 0.76 ... #> $ windspeed : num 0 0 0 0 0 0.0896 0 0 0 0 ... #> $ count : int 16 40 32 13 1 1 2 3 8 14 ... #> - attr(*, ".internal.selfref")=<externalptr>