Three_weeks.Rmd

---
title: "Three Week Analysis"
author: "T. Poole"
date: '2022-07-30'
output: 
  html_document:
          code_fold: hide
editor_options: 
  markdown: 
    wrap: 72
---

```{r,echo=FALSE,include=FALSE}
library(tidyverse)
library(forcats)

 ## Read in Overtime data ##

        overtime.df <- read_csv(file = "Three_Weeks_OT.csv")

        overtime.df <- na.omit(overtime.df)

 ## Read in run data 7/11/2022 thru 7/30/2022 ##

        Threeweekcalls.df <- read_csv(file = "Threeweeks.csv")
        
 ## Read in mutual aid responses for same time period ##
        
        Threeweekma.df <- read_csv(file = "THREEWEEKSMA.csv")

```
## Average calls per day for the period 7/11/2022 thru 7/30/2022. ##

#### The data frame below details all the calls for the period specified. These calls were queried 0800 hrs 07/31/2022 from the South Burlington Fire Department records management system using "FHpivotsummery" query.

#### If we devide the 20 days into `r nrow(Threeweekcalls.df)`calls returns `r nrow(Threeweekcalls.df)/20` calls per day average. The complete call listing is below.

```{r}
knitr::kable(Threeweekcalls.df,
 caption = "SBFD Calls, 7/11/2022 thru 7/30/2022")
```


## Overtime analysis 07/11/2022 thru 07/30/2022 ##

The table below outlines overtime shifts for the period *(one member working 24hrs = 1 shift)*. The average overtime pershift is `r mean(overtime.df$overtime_shifts)` shifts. The total overtime hours for the period is `r sum(overtime.df$overtime_shifts)*24` hours. The
total shift overtime percentage of the period is `r (sum(overtime.df$overtime_shifts)/sum(overtime.df$full_shift))*100`%.

```{r}
knitr::kable(overtime.df,
 caption = "SBFD Overtime, 7/11/2022 thru 7/31/2022")
```
## Mutual Aid per shift for 7/11/2022 thru 7/30/2022 ##

### this is a test