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# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
#' @title Import a Workplace Analytics Query
#'
#' @description
#' Import a Workplace Analytics Query from a local CSV File, with variable
#' classifications optimised for other 'wpa' functions.
#'
#' @details
#' `import_wpa()` uses `data.table::fread()` to import CSV files for speed,
#' and by default `stringsAsFactors` is set to FALSE.
#' A data frame is returned by the function (not a `data.table`).
#'
#' @param x String containing the path to the Workplace Analytics query to be
#' imported. The input file must be a CSV file, and the file extension must be
#' explicitly entered, e.g. `"/files/standard query.csv"`
#' @param standardise logical. If TRUE, `import_wpa()` runs `standardise_pq()`
#' to make a Collaboration Assessment query's columns name standard and
#' consistent with a Standard Person Query. Note that this will have no effect
#' if the query being imported is not a Ways of Working Assessment query.
#' Defaults as FALSE.
#' @param encoding String to specify encoding to be used within
#' `data.table::fread()`. See `data.table::fread()` documentation for more
#' information. Defaults to `'UTF-8'`.
#'
#' @return A `tibble` is returned.
#'
#' @family Import and Export
#'
#' @export
import_wpa <- function(x,
standardise = FALSE,
encoding = 'UTF-8'){
return_data <-
data.table::fread(x,
stringsAsFactors = FALSE,
encoding = encoding) %>%
as.data.frame()
# Columns which are Dates
dateCols <- sapply(return_data, function(x) all(is_date_format(x)))
dateCols <- dateCols[dateCols == TRUE]
return_data <-
return_data %>%
dplyr::mutate_at(dplyr::vars(names(dateCols)), ~as.Date(., format = "%m/%d/%Y"))
message("Query has been imported successfully!")
## Query check only available for Person Queries
if(identify_query(return_data) == "Person Query"){
check_query(return_data)
}
## Standardise query if `standardise == TRUE`
if(standardise == TRUE & identify_query(return_data) == "Ways of Working Assessment Query"){
message("Standardising column names for a Ways of Working Assessment query to
a Person query...")
return_data <- standardise_pq(return_data)
}
dplyr::as_tibble(return_data)
}
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