Installation : tashu | Installation : "tashudata" package | 1. Introduction | 2. Data | 3. Analysis function | 4. Prediction stations
Package: tashu 0.1.1
tashu: Analysis and Prediction of Bicycle Rental Amount
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 <https://github.com/zeee1/Tashu_Rpackage>. 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().
Authors:
tashu_0.1.1.tar.gz
tashu_0.1.1.zip(r-4.7-any)tashu_0.1.1.zip(r-4.6-any)tashu_0.1.1.zip(r-4.5-any)
tashu_0.1.1.tgz(r-4.6-any)tashu_0.1.1.tgz(r-4.5-any)
tashu_0.1.1.tar.gz(r-4.7-any)tashu_0.1.1.tar.gz(r-4.6-any)
tashu_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tashu/json (API)
| # Install 'tashu' in R: |
| install.packages('tashu', repos = c('https://zeee1.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:c74a921264. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | NOTE | 190 | ||
| source / vignettes | OK | 298 | ||
| linux-release | NOTE | 151 | ||
| macos-release | NOTE | 164 | ||
| macos-oldrel | NOTE | 218 | ||
| windows-devel | NOTE | 107 | ||
| windows-release | NOTE | 117 | ||
| windows-oldrel | NOTE | 102 | ||
| wasm-release | OK | 132 |
Exports:create_test_datasetcreate_train_datasetcreate_train_modeldaily_bicycle_rentalmonthly_bicycle_rentalpredict_bicycle_rentaltop10_pathstop10_stations
Dependencies:clicpp11dplyrdratfarvergenericsggplot2gluegtableisobandlabelinglifecyclelubridatemagrittrpillarpkgconfigplyrR6randomForestRColorBrewerRcppreshape2rlangS7scalesstringistringrtibbletidyselecttimechangeutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create training dataset on specific station for prediction | create_test_dataset |
| Create training dataset on specific station for prediction | create_train_dataset |
| Create random-forest training model for bicycle rental prediction. | create_train_model |
| Visualize amount of bicycle rental at each day of week. | daily_bicycle_rental |
| Extract feature columns from train/test dataset | extract_features |
| Visualize the change of bicycle rental amount by temperature and each month. | monthly_bicycle_rental |
| Predict hourly Demand of bicycle in 2015. | predict_bicycle_rental |
| Visualize Top 10 Pathes that were most used from 2013 to 2015. | top10_paths |
| Visualize top 10 stations that were most used from 2013 to 2015. | top10_stations |