rtsdata: 'rtsdata' - Efficient Data Storage system for R Time Series.

In rtsdata: R Time Series Intelligent Data Storage

'rtsdata' - Efficient Data Storage system for R Time Series.

Description

The 'rtsdata' package simplifies the management of Time Series in R. This package overwrites the 'getSymbols' function from 'quantmod' package to allow for minimal changes to get started. The 'rtsdata' package provides functionality to **download** and **store** historical time series.

The **download** functionality will intelligently update historical data as needed. The incremental data is downloaded first to updated historical data. The full history is **only** downloaded if incremental data is not consistent. I.e. the last saved record is different from the first downloaded record.

The following download plugins are currently available: * Yahoo Finance - based on 'quantmod' package. * FRED - based on 'quantmod' package. * Quandl - based on 'Quandl' package. Quandl recommends getting an API key. Add following code options(Quandl.api_key = api_key) to your .Rprofile file. * AlphaVantage(av) - based on 'quantmod' package. You need an API key from www.alphavantage.co. Add following code options(getSymbols.av.Default = api_key) to your .Rprofile file. * Tiingo - based on 'quantmod' package You need an API key from api.tiingo.com. Add following code options(getSymbols.av.Default = api_key) to your .Rprofile file.

The download functionality plugins are easily created. The user needs to provide a function to download historical data with ticker, start, and end dates parameters to create new download plugin.

The **storage** functionality provides a consistent interface to store historical time series. The following storage plugins are currently available: * Rdata - store historical time series data in the Rdata files. * CSV - store historical time series data in the CSV files. The CSV storage is not efficient because CSV files will have to be parsed every time the data is loaded. The advantage of this format is ease of access to the stored historical data by external programs. For example the CSV files can be opened in Notepad or Excel. * MongoDB - store historical time series data in the MongoDB GridFS system. The MongoDB storage provides optional authentication. The MongoDB storage functionality is currently only available in the development version at bitbucket.

The storage functionality plugins are easily created. The user needs to provide a functions to load and save data to create new storage plugin.

Author(s)

Maintainer: Irina Kapler [e-mail]

Authors:

• RTSVizTeam [e-mail] [copyright holder]

See Also

Useful links:

• https://bitbucket.org/rtsvizteam/rtsdata

• Report bugs at https://bitbucket.org/rtsvizteam/rtsdata/issues

Examples

 # small toy example

 # register data source to generate fake stock data for use in rtsdata examples
 register.data.source(src = 'sample', data = ds.getSymbol.fake.stock.data)
 
 # Full Update till '2018-02-13'
 data = getSymbols('test', src = 'sample', from = '2018-01-01', to = '2018-02-13', 
					auto.assign=FALSE, verbose=TRUE)
 
 # No updated needed, data is loaded from file
 data = getSymbols('test', src = 'sample', from = '2018-01-01', to = '2018-02-13', 
					auto.assign=FALSE, verbose=TRUE)

 # Incremental update from '2018-02-13' till today
 data = getSymbols('test', src = 'sample', from = '2018-01-01', 
					auto.assign=FALSE, verbose=TRUE)

 # No updated needed, data is loaded from file
 data = getSymbols('test', src = 'sample', from = '2018-01-01', 
					auto.assign=FALSE, verbose=TRUE)

	# data is stored in the 'sample_Rdata' folder at the following location
	ds.default.location()

rtsdata documentation built on Sept. 25, 2023, 9:06 a.m.