LSA 977-982.R

#COHHIO_HMIS
#Copyright (C) 2019  Coalition on Homelessness and Housing in Ohio (COHHIO)

#This program is free software: you can redistribute it and/or modify
#it under the terms of the GNU Affero General Public License as published
#by the Free Software Foundation, either version 3 of the License, or
#any later version.

#This program is distributed in the hope that it will be useful,
#but WITHOUT ANY WARRANTY; without even the implied warranty of
#MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
#GNU Affero General Public License for more details at 
#<https://www.gnu.org/licenses/>.

# Distribution of FAM to IND beds vs HH w/ multiple clients and Singles served

library(tidyverse)
library(lubridate)
library(HMIS)

ReportStart <- "10012018"
ReportEnd <- "09302020"

Inventory <- read_csv("data/Inventory.csv")
Enrollment <- read_csv("data/Enrollment.csv")
Exit <- read_csv("data/Exit.csv")

smallInventory <- Inventory %>%
  filter(beds_available_between(., ReportStart, ReportEnd)) %>%
  select(ProjectID, HouseholdType, BedInventory) %>%
  mutate(HouseholdType = case_when(
    HouseholdType == 1 ~ "Individual",
    HouseholdType == 3 ~ "Households",
    HouseholdType == 4 ~ "ChildrenOnly"
  ))

x <- rowid_to_column(smallInventory)

hhtypes <- spread(x, HouseholdType, BedInventory) %>%
  group_by(ProjectID) %>%
  summarise(ChildrenOnlyBeds = sum(ChildrenOnly, na.rm = TRUE),
            HouseholdBeds = sum(Households, na.rm = TRUE),
            IndividualBeds = sum(Individual, na.rm = TRUE)) %>%
  mutate(percentHHBeds = HouseholdBeds/
           (HouseholdBeds + IndividualBeds))

smallEnrollment <- Enrollment %>%
  left_join(Exit[c("EnrollmentID", "ExitDate")], by = "EnrollmentID") %>%
  filter(served_between(., ReportStart, ReportEnd)) %>%
  select(ProjectID, HouseholdID) %>%
  mutate(HouseholdType = case_when(
    grepl("s_", HouseholdID) == TRUE ~ "IndividualsServed",
    grepl("h_", HouseholdID) == TRUE ~ "HouseholdsServed"
  )) %>% unique()

y <- smallEnrollment %>%
  group_by(ProjectID, HouseholdType) %>%
  summarise(Count = n())

hhserved <- spread(y, HouseholdType, Count, fill = 0) %>%
  mutate(percentHouseholds = HouseholdsServed/
           (HouseholdsServed + IndividualsServed))

z <- full_join(hhtypes, hhserved)

possibleissues <- z %>%
  mutate(
    Diff = abs(percentHHBeds - percentHouseholds)) %>%
  filter(Diff > .75)