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template_individual_html_photoexample.Rmd
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template_individual_html_photoexample.Rmd
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---
title: "Disaster Survey Sheet"
output:
html_document:
toc: true
toc_depth: 3
---
```{r setup, echo=FALSE, warning=FALSE, message=FALSE}
library(dplyr)
library(lubridate)
library(jsonlite)
library(knitr)
library(ggplot2)
library(leaflet)
knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE)
options (scipen=4)
cbPalette <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#999999", "#000000", "#8856a7")
###### FOR TESTING #####
field_data <- read.csv("Codefest Data.csv", header=TRUE, sep=",")
#report_id <- 33
#`r disastername`,
report_id <- 27
```
*Report Date: `r Sys.Date()`*
### Property Information
**Name:** `r field_data$name_property_owner[id=report_id]`
**Address:** `r field_data$street_address[id=report_id]`
**Municipality:** `r field_data$city[id=report_id]`
**Zip Code:** `r field_data$zip_code[id=report_id]`
**County:** `r field_data$county[id=report_id]`
**Phone:** `r field_data$phone_number[id=report_id]`
**Type of Applicant or Structure:** `r field_data$property_type[id=report_id]`
**Homeowner or Renter:** `r field_data$owner_type[id=report_id]`
### Insurance Information
**Insurance Agent Name:** `r field_data$name_insurance[id=report_id]`
**Insurance Agent Phone:** `r field_data$phone_insurance[id=report_id]`
**Flood Insurance:** `r field_data$flood_insurance[id=report_id]`
### Estimated Disaster Loss Details
```{r loss_table, echo=FALSE, warning=FALSE, message=FALSE}
# row for each of structure, contents, land and improvements
# bring in variables for market value, amount damaged by disaster, amount covered by insurance
structure <- data.frame("Structure", field_data$marketvalue_structure[id=report_id],
field_data$disaster_structure[id=report_id],
field_data$insurance_structure[id=report_id])
colnames(structure) <- c("Area", "MarketValue", "DisasterLoss", "InsuranceCovered")
contents <- data.frame("Contents", field_data$marketvalue_contents[id=report_id],
field_data$disaster_contents[id=report_id],
field_data$insurance_contents[id=report_id])
colnames(contents) <- c("Area", "MarketValue", "DisasterLoss", "InsuranceCovered")
landimprov <- data.frame("Land & Improvements", field_data$marketvalue_land[id=report_id],
field_data$disaster_land[id=report_id],
field_data$insurance_land[id=report_id])
colnames(landimprov) <- c("Area", "MarketValue", "DisasterLoss", "InsuranceCovered")
# bind these
loss_table <- rbind(structure, contents, landimprov)
# calculate amount and percent of uninsured loss
loss_table$UninsuredLoss <- loss_table$DisasterLoss - loss_table$InsuranceCovered
loss_table$UninsuredLossPercent <- paste(round(loss_table$UninsuredLoss / loss_table$MarketValue*100, 2), "%")
kable(loss_table, col.names = c("Area", "Market Value", "Disaster Loss", "Covered by Insurance",
"Uninsured Loss", "Uninsured Loss %"),
align=c(rep("r", 6)), row.names = F, format.args=list(big.mark = ','))
```
### Building Damage
**Damage Category:** `r field_data$damage_category[id=report_id]`
```{r damage_bysystem, echo=FALSE, warning=FALSE, message=FALSE}
foundation <- data.frame("Foundation", field_data$damage_foundation[id=report_id])
colnames(foundation) <- c("Area", "PercentDamange")
floor <- data.frame("Floor", field_data$damage_floor[id=report_id])
colnames(floor) <- c("Area", "PercentDamange")
exterior <- data.frame("Exterior Walls", field_data$damage_exterior[id=report_id])
colnames(exterior) <- c("Area", "PercentDamange")
#roof <- data.frame("Roof", field_data$damage_roof[id=report_id])
#colnames(roof) <- c("Area", "PercentDamange")
interior <- data.frame("Interior Walls", field_data$damage_interior[id=report_id])
colnames(interior) <- c("Area", "PercentDamange")
plumbing <- data.frame("Plumbing", field_data$damage_plumbing[id=report_id])
colnames(plumbing) <- c("Area", "PercentDamange")
heat_ac <- data.frame("Heating / AC", field_data$damage_hvac[id=report_id])
colnames(heat_ac) <- c("Area", "PercentDamange")
electrical <- data.frame("Electrical", field_data$damage_electrical[id=report_id])
colnames(electrical) <- c("Area", "PercentDamange")
systemdamage <- rbind(foundation, floor, exterior, interior, plumbing, heat_ac, electrical)
colnames(systemdamage) <- c("SystemArea", "PercentDamange")
kable(systemdamage, col.names = c("System Area", "Percent Damaged"), row.names=F)
# thoughts on section of report
# Estimated Replacement Cost looks like sum of percent damanged times fair market value of property
# which is loss_table$MarketValue
```
**Total % Damaged:** `r round(sum(systemdamage$PercentDamange),0)`%
**Estimated Replacement Cost:** $ `r format((sum(systemdamage$PercentDamange * sum(loss_table$MarketValue))), big.mark = ",")`
**Estimated Damage to Contents:** $ `r format(sum(loss_table$DisasterLoss[loss_table$Area=="Contents"]), big.mark=",")`
**Total Estimated Damange:** $ `r format((sum(systemdamage$PercentDamange * sum(loss_table$MarketValue)) + sum(loss_table$DisasterLoss[loss_table$Area=="Contents"])), big.mark=",")`
### Comments
`r field_data$comments[id=report_id]`
### Assessor
**Name of Assessor:** `r field_data$name_of_assessor[id=report_id]`
**Date:** `r field_data$date[id=report_id]`
### Photos
```{r photo1, out.width = "400px"}
knitr::include_graphics("photos/cevisit.jpg")
```
```{r photo2, out.width = "400px"}
knitr::include_graphics("photos/ceVisit5.jpg")
```
```{r map}
# map.data <- filter(muni.data, !is.na(Violation), !is.na(lat))
# leaflet() %>%
# # use the CartoDB map for more subdued map tile colors
# addProviderTiles("CartoDB.Positron") %>%
# setView(lng = -79.8, lat = 40.4212, zoom = 12) %>%
# addCircleMarkers(data = map.data,
# lng = ~long, lat = ~lat,
# popup = paste("Violation:", map.data$Violation,
# "<br> Initial Date:", map.data$EventDate),
# # the marker clusters gives us a nice visual
# # effect where when we zoom out points cluster
# # together, and as we zoom in they are pulled apart
# # showing the individual markers.
# #clusterOptions = markerClusterOptions()
# radius = 5,
# stroke = TRUE,
# color = "#323232",
# weight = 3,
# fillColor = "#7fcdbb",
# fillOpacity = 0.7
# )
```