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tashu (version 0.1.1)

Analysis and Prediction of Bicycle Rental Amount

Description

Provides functions for analyzing citizens' bicycle usage pattern and predicting rental amount on specific conditions. Functions on this package interacts with data on 'tashudata' package, a 'drat' repository. 'tashudata' package contains rental/return history on public bicycle system('Tashu'), weather for 3 years and bicycle station information. To install this data package, see the instructions at . top10_stations(), top10_paths() function visualizes image showing the most used top 10 stations and paths. daily_bike_rental() and monthly_bike_rental() shows daily, monthly amount of bicycle rental. create_train_dataset(), create_test_dataset() is data processing function for prediction. Bicycle rental history from 2013 to 2014 is used to create training dataset and that on 2015 is for test dataset. Users can make random-forest prediction model by using create_train_model() and predict amount of bicycle rental in 2015 by using predict_bike_rental().

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Version

Install

install.packages('tashu')

Monthly Downloads

146

Version

0.1.1

License

GPL (>= 2)

Maintainer

Jiwon Min

Last Published

January 13th, 2021

Functions in tashu (0.1.1)

daily_bicycle_rental

Visualize amount of bicycle rental at each day of week.
top10_stations

Visualize top 10 stations that were most used from 2013 to 2015.
create_train_model

Create random-forest training model for bicycle rental prediction.
top10_paths

Visualize Top 10 Pathes that were most used from 2013 to 2015.
predict_bicycle_rental

Predict hourly Demand of bicycle in 2015.
create_train_dataset

Create training dataset on specific station for prediction
create_test_dataset

Create training dataset on specific station for prediction
monthly_bicycle_rental

Visualize the change of bicycle rental amount by temperature and each month.
extract_features

Extract feature columns from train/test dataset