R/mgrcoatt_dist.R

In wpa: Tools for Analysing and Visualising Viva Insights Data

# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE.txt in the project root for license information.
# --------------------------------------------------------------------------------------------

#' @title Manager meeting coattendance distribution
#'
#' @description
#' Analyze degree of attendance between employes and their managers.
#' Returns a stacked bar plot of different buckets of coattendance.
#' Additional options available to return a table with distribution elements.
#'
#' @template spq-params
#'
#' @param return String specifying what to return. This must be one of the
#'   following strings:
#'   - `"plot"`
#'   - `"table"`
#'
#' See `Value` for more information.
#'
#' @return
#' A different output is returned depending on the value passed to the `return`
#' argument:
#'   - `"plot"`: ggplot object. A stacked bar plot showing the distribution of
#'   manager co-attendance time.
#'   - `"table"`: data frame. A summary table for manager co-attendance time.
#'
#' @import dplyr
#' @import ggplot2
#' @import reshape2
#' @import scales
#' @importFrom stats median
#' @importFrom stats sd
#'
#' @family Visualization
#' @family Managerial Relations
#'
#' @examples
#' # Return plot
#' mgrcoatt_dist(sq_data, hrvar = "Organization", return = "plot")
#'
#' # Return summary table
#' mgrcoatt_dist(sq_data, hrvar = "Organization", return = "table")
#'
#' @export

mgrcoatt_dist <- function(data,
                          hrvar = "Organization",
                          mingroup = 5,
                          return = "plot") {

myPeriod <-
    data %>%
    mutate(Date=as.Date(Date, "%m/%d/%Y")) %>%
    arrange(Date) %>%
    mutate(Start=first(Date), End=last(Date)) %>%
    filter(row_number()==1) %>%
    select(Start, End)

  ## Basic Data for bar plot
  plot_data <-
    data %>%
    rename(group = !!sym(hrvar)) %>%
    group_by(PersonId) %>%
	filter(Meeting_hours>0) %>%
	mutate(coattendman_rate = Meeting_hours_with_manager / Meeting_hours) %>%
    summarise(periods = n(),
              group = first(group), coattendman_rate=mean(coattendman_rate)) %>%
    group_by(group) %>%
    mutate(Employee_Count = n_distinct(PersonId)) %>%
    filter(Employee_Count >= mingroup)

  ## Create buckets of coattendance time
  plot_data <-
    plot_data %>%
    mutate(bucket_coattendman_rate =
             case_when(coattendman_rate>=0 &  coattendman_rate<.25 ~ "0 - 25%",
                       coattendman_rate>=.25 & coattendman_rate<.5 ~ "25 - 50%",
                       coattendman_rate>=.50 & coattendman_rate<.75 ~ "50 - 75%",
                       coattendman_rate>=.75 ~ "75% +"))


  ## Employee count / base size table
  plot_legend <-
    plot_data %>%
    group_by(group) %>%
    summarize(Employee_Count=first(Employee_Count)) %>%
    mutate(Employee_Count = paste("n=",Employee_Count))

  ## Data for bar plot
  plot_table <-
    plot_data %>%
    group_by(group, bucket_coattendman_rate) %>%
    summarize(Employees=n(),
              Employee_Count=first(Employee_Count),
              percent= Employees / Employee_Count) %>%
    arrange(group, bucket_coattendman_rate)

  ## Table for annotation
  annot_table <-
    plot_legend %>%
    dplyr::left_join(plot_table, by = "group")

	## Remove max from axis labels, and add %
  max_blank <- function(x){
    as.character(
      c(
        scales::percent(
          x[1:length(x) - 1]
          ),
        "")
    )
  }


  ## Bar plot
  plot_object <-
    plot_table %>%
    ggplot(aes(x = group, y=Employees, fill = bucket_coattendman_rate)) +
    geom_bar(stat = "identity", position = position_fill(reverse = TRUE)) +
  	coord_flip() +
    scale_y_continuous(expand = c(.01, 0), labels = max_blank, position = "right") +
	annotate("text", x = plot_legend$group, y = 1.15, label = plot_legend$Employee_Count, size = 3) +
    annotate("rect", xmin = 0.5, xmax = length(plot_legend$group) + 0.5, ymin = 1.05, ymax = 1.25, alpha = .2) +
    annotate(x = length(plot_legend$group) + 0.8,
             xend = length(plot_legend$group) + 0.8,
             y = 0,
             yend = 1,
             colour = "black",
             lwd = 0.75,
             geom = "segment") +
  	scale_fill_manual(name="",
  	                  values = c("#bfe5ee",  "#b4d5dd", "#fcf0eb", "#facebc")) +
    theme_wpa_basic() +
    theme(axis.line = element_blank(),
          axis.ticks = element_blank(),
          axis.title = element_blank()) +
  	labs(title = "Meetings coattended by line manager",
  	     subtitle = paste("Percentage of meetings per person"),
  	     caption = extract_date_range(data, return = "text"))

  ## Table to return
  return_table <-
    plot_table %>%
    select(group, bucket_coattendman_rate,  percent) %>%
    spread(bucket_coattendman_rate,  percent)

  if(return == "table"){

    return_table %>%
      as_tibble() %>%
      return()

  } else if(return == "plot"){

    return(plot_object)

  } else {

    stop("Please enter a valid input for `return`.")

  }
}