/R_Internship_task

Primary LanguageR

R_Internship_Task

Problem Statement:-

In bike-sharing systems, the entire process from membership to rental and return has been automated. Using these systems, users can easily rent a bike from one location and return it to another. Hence, a bike rental company wants to understand and predict the number of bikes rented daily based on the environment and seasons.

Dataset Description:-

  • Variable - Description
  • 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)
  • holiday - Weather day is a holiday or not
  • weekday - Day of the week
  • workingday - Working day (1: neither weekend nor holiday, 0: other days)
  • 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
  • temp - Normalized temperature in Celsius; The values are divided into 41 (max)
  • atemp - Normalized feeling temperature in Celsius; The values are divided into 50 (max)
  • hum - Normalized humidity; The values are divided into 100 (max)
  • windspeed - Normalized wind speed; The values are divided into 67(max)
  • casual - Count of casual users
  • registered - Count of registered users
  • cnt - Count of total rental bikes including both casual and registered

Tasks to Perform:-

Perform the following tasks on the dataset provided using R:

  1. Exploratory data analysis:
  • Load the dataset and the relevant libraries
  • Perform data type conversion of the attributes
  • Carry out the missing value analysis
  1. Attributes distribution and trends
  • Plot monthly distribution of the total number of bikes rented
  • Plot yearly distribution of the total number of bikes rented
  • Plot boxplot for outliers' analysis
  1. Split the dataset into train and test dataset
  2. Create a model using the random forest algorithm
  3. Predict the performance of the model on the test dataset

How to run the code file:-

  • Dataset file is : 1657875746_day.xlsx
  • R code file is : R_internship_task_WEBRIY.R
  • Put the data and R code file in a folder in the required local machine (where R and R studio softwares already installed beforehand)
  • Now Ctrl+A and run the whole script by clicking on "run" option present in Rstudio
  • All the visualizations plot already putting in github which i got it from the code.