Loading the data
To start with, let us load the "Bikes Rental" data set (bikes.csv) and get a first hand look into the same.
The dataset contains the following parameters:
instant: record index
dteday: date
season: season (1: springer, 2: summer, 3: fall, 4: winter)
yr: year (0: 2011, 1:2012)
mnth: month (1 to 12)
hr: hour (0 to 23)
holiday: whether day is holiday or not
weekday: day of the week
workingday: if day is neither weekend nor holiday is 1, otherwise is 0.
weathersit:
1: Clear, Few clouds, Partly cloudy, Partly cloudy
2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist
3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds
4: Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow + Fog
temp: Normalized temperature in Celsius.
atemp: Normalized feeling temperature in Celsius.
hum: Normalized humidity. The values are divided to 100 (max)
windspeed: Normalized wind speed. The values are divided to 67 (max)
casual: count of casual users
registered: count of registered users
cnt: count of total rental bikes including both casual and registered
Please follow the below steps:
filePath to store the location path for our dataset file bikes.csv as a string. bikes.csv is located at /cxldata/datasets/project/bikes.csv. This file location is on the Linux box - web consoleread_csv to load this bikes.csv file using the location path defined by filePath variable above and store the loaded file into a dataframe called bikesData.bikesData dataframe by calling an appropriate function of dataframe.PS - Next couple of question depends on this assessment.
Note - Having trouble with the assessment engine? Follow the steps listed here
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