Database Reference
In-Depth Information
Extracting features from the bike sharing dataset
To illustrate the concepts in this chapter, we will be using the bike sharing dataset. This
dataset contains hourly records of the number of bicycle rentals in the capital bike sharing
system. It also contains variables related to date and time, weather, and seasonal and holi-
day information.
Note
The dataset is available at
http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset
.
Click on the
Data Folder
link and then download the
Bike-Sharing-Dataset.zip
file.
The bike sharing data was enriched with weather and seasonal data by Hadi Fanaee-T at
the University of Porto and used in the following paper:
Fanaee-T, Hadi and Gama Joao, Event labeling combining ensemble detectors and back-
ground knowledge,
Progress in Artificial Intelligence
, pp. 1-15, Springer Berlin Heidel-
berg, 2013.
The paper is available at
http://link.springer.com/article/10.1007%2Fs13748-013-0040-3
.
Once you have downloaded the
Bike-Sharing-Dataset.zip
file, unzip it. This will
create a directory called
Bike-Sharing-Dataset
, which contains the
day.csv
,
hour.csv
, and the
Readme.txt
files.
The
Readme.txt
file contains information on the dataset, including the variable names
and descriptions. Take a look at the file, and you will see that we have the following vari-
ables available:
•
instant
: This is the record ID
•
dteday
: This is the raw date
•
season
: This is different seasons such as spring, summer, winter, and fall
•
yr
: This is the year (2011 or 2012)
•
mnth
: This is the month of the year
•
hr
: This is the hour of the day
•
holiday
: This is whether the day was a holiday or not
•
weekday
: This is the day of the week
