12-load-nash.Rmd

---
title: "12-load-nash"
output: html_notebook
---

This script loads the Construction Permit Data for Nashville spanning the period of time of 6/15/2016 to 6/15/2021 from a single excel file located in Box. Functions are used to clean column names, check if values are within logical bounds, and evaluate NA values.

```{r Load_setup, echo = FALSE, results='hide'}

## Load libs, common functions

 source(knitr::purl("10-load-data.Rmd"))
 fs::file_delete("10-load-data.R")
```



```{r Load_Construction_Permits, echo = TRUE, results='show'}

nash_permits <- read.csv(expand_boxpath("Nashville/Metro-Bldg-Permits-Last-5yrs.csv")) %>% 
  clean_names() %>% 
  rm_na_cols() %>%
  rename("permit_number" = 1) %>%
  drop_na(permit_number) %>%
  assert(is.numeric, const_cost) %>%
  assert(within_bounds(0, Inf), const_cost) %>%
  #insist(within_n_sds(4), const_cost) %>% 
  #note: found 5 exorbitantly expensive permits, confirming with Allie
  assert(is.character, -const_cost)

nash_permits[nash_permits=="NULL"]<-NA
nash_permits[nash_permits==0]<-NA

nash_permits = nash_permits %>% 
  mutate(date_entered = as.Date(date_entered, format= "%m/%d/%Y")) %>%
  mutate(date_issued = as.Date(date_issued, format= "%m/%d/%Y")) %>%
  mutate(final_insp_date= as.Date(final_insp_date, format= "%m/%d/%Y"))


nash_permits
#NA check

map(nash_permits, ~sum(is.na(.)))

#zero NAs across all columns

```

## Issued Construction Permits
The result of the above code, this dataframe contains permit information, but no data on debris. It seems to have roughly similar information to the Austin data set, except smaller in size and neater.

```{r View_Data, results = 'show'}

nash_permits

#found 5 instances which are exorbitantly expensive:
#11391, 27515, 45893, 57059, 59034

#nash_permits[59034,]

```