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R/MergeCSVs.R

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#' Merges two HMIS CSV sets.
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#'
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#' @param string path to folder contaning first CSV set.
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#' @param string path to folder contaning second CSV set.
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#' @param string path to output where merged CSVs will be written.
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#' @param boolean save in feather file format. Default is false.
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#' @param string Path to folder contaning first CSV set.
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#' @param string Path to folder contaning second CSV set.
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#' @param string Path to output where merged CSVs will be written.
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#' @param boolean Save in feather file format. Default is false. Loading binary data from file takes around 1/10 the time compared to loading a CSV
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#' @export
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#' @examples
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#'
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#' # Data will be saved in CSV format.
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#' mergeHmisCSVs('/Users/user/local/CSV_2016',
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#' '/Users/user/local/CSV_2016',
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#' '/Users/user/local/CSV_2016_and_2017')
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#'
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#'
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#' # Data will be saved in binary format.
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#' mergeHmisCSVs('/Users/user/local/CSV_2016',
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#' '/Users/user/local/CSV_2016',
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#' '/Users/user/local/CSV_2016_and_2017'
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#' feather = TRUE)
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#'
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mergeHmisCSVs <- function(dataPathOne,
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dataPathTwo,
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pathForCombinedData,

README.md

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This allows any HMIS implementation to be more loosely coupled to their software provider, since all HMIS software providers are required to produce HMIS CSVs.
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## HMIS Levels
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HMIS data and methods are structured on three levels, System, Agency, and Project.
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HMIS data and methods are structured on three levels: System, Agency, and Project.
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### System
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HUD requires HMIS software vendors implement tools to pull the following standardized reports:

RHMIS.pdf

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man/mergeHmisCSVs.Rd

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