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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
<head>
<title>Developing in-house software</title>
<meta charset="utf-8" />
<meta name="author" content="Camille Seaberry" />
<link href="libs/ionicons/css/ionicons.min.css" rel="stylesheet" />
<link rel="stylesheet" href="xaringan-themer.css" type="text/css" />
<link rel="stylesheet" href="theme-extras.css" type="text/css" />
</head>
<body>
<textarea id="source">
class: left, title-slide
# Developing in-house software
## Why I did it & you should too
### Camille Seaberry
### DataHaven
### <br><br><i class="ion ion-link "></i> Follow along: <a href="https://ct-data-haven.github.io/datadev" class="uri">https://ct-data-haven.github.io/datadev</a><br><br><i class="ion ion-code "></i> Get the code: <a href="https://github.com/CT-Data-Haven/datadev" class="uri">https://github.com/CT-Data-Haven/datadev</a>
---
# DataHaven's Community Index
.col3-pad[
#### 2013
]
.col3-pad[
#### 2016
]
.col3-pad[
#### 2019: the takeover
]
---
# Spreadsheet sprawl
.pull-left[]
.pull-right[
### Installing packages is easy
```r
install_github("camille-s/camiller")
install_github("CT-Data-Haven/cwi")
```
]
---
# Shifting my thinking: toward sustainable & reproducible work
.pull-left[
.big-text[
Unhappy Mother's Day, but a new appreciation of behind-the-scenes information
]
]
.pull-right[]
---
# Shifting my thinking: toward sustainable & reproducible work
.pull-left[
<!-- -->
]
.pull-right[
.big-text[I moved 300 miles away to Baltimore]
]
---
# What's a library?
```r
library(tidyverse) # sets up LOTS of functions, how I start my mornings
library(tidycensus) # fetches data from Census API
library(camiller) # first in-house library
library(cwi) # second in-house library
library(showtext) # use nice fonts in plots
library(sf) # work with geospatial data & make maps
library(patchwork) # layout plots together
library(lubridate) # parse dates
```
---
# Functions! If only...
.small-text[
```r
leave_the_house <- function(date = today(), biking = TRUE, working = TRUE) {
day_of_week <- wday(date, label = TRUE, abbr = FALSE)
always_need <- c("keys", "phone", "wallet", "meds")
sometimes_need <- c()
if (biking) {
sometimes_need <- c(sometimes_need, "helmet")
} else {
sometimes_need <- c(sometimes_need, "bus card")
}
if (working) {
sometimes_need <- c(sometimes_need, "laptop")
}
need <- c(always_need, sometimes_need)
cat(
sprintf("Happy %s! Today you need:", day_of_week), "\n",
paste(need, collapse = ", ")
)
}
```
]
---
# Functions! If only...
```r
leave_the_house(biking = TRUE, working = FALSE)
```
```
Happy Monday! Today you need:
keys, phone, wallet, meds, helmet
```
---
# Functions: reduce repetition & clutter
**Tedious and messy**
```r
income_us <- get_acs("us", table = "B19013", year = 2017)
income_state <- get_acs("state", table = "B19013", year = 2017)
income_msa <- get_acs("metropolitan statistical area/micropolitan statistical area", table = "B19013", year = 2017)
income_county <- get_acs("county", table = "B19013", state = "09", year = 2017)
income_towns <- get_acs("county subdivision", table = "B19013", state = "09", year = 2017)
income <- bind_rows(income_us, income_state, income_msa, income_county, income_towns)
# get rid of those extra tables
rm(income_us, income_state, income_msa, income_county, income_towns)
```
**Nice n clean**
```r
income <- multi_geo_acs(table = "B19013", year = 2017, us = TRUE, msa = TRUE)
```
---
# Functions: I *swear* I did this last week!
.left-column-67[
<!-- -->
]
.right-column-33[
<!-- -->
]
.right-column-33[
<!-- -->
]
---
# Functions: make it scale
.left-column-67[
<!-- -->
]
.right-column-33[
<!-- -->
]
.right-column-33[
<!-- -->
]
---
# Functions: encourage good habits
.pull-left[
```r
geo_level_plot(tenure,
value = homeownership,
hilite = "mediumpurple1",
title = "Homeownership rates, 2017")
```
]
.pull-right[
<!-- -->
]
---
# Clean, uniform charts
<!-- -->
---
# Reusable datasets & references
.big-text[How many times can I generate, save, and forget about the same lookup tables and shapefiles?]
.footnote[My old (stolen) laptop was even worse!]
---
# Reusable datasets & references
**Much better:** move those lookup tables & shapefiles to the R package
.pull-left[
```r
head(village2town, n = 5)
```
<table>
<thead>
<tr>
<th style="text-align:left;"> cdp_geoid </th>
<th style="text-align:left;"> place </th>
<th style="text-align:left;"> town_geoid </th>
<th style="text-align:left;"> town </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> 0902550 </td>
<td style="text-align:left;"> Baltic </td>
<td style="text-align:left;"> 0901171670 </td>
<td style="text-align:left;"> Sprague </td>
</tr>
<tr>
<td style="text-align:left;"> 0902690 </td>
<td style="text-align:left;"> Bantam </td>
<td style="text-align:left;"> 0900543370 </td>
<td style="text-align:left;"> Litchfield </td>
</tr>
<tr>
<td style="text-align:left;"> 0904945 </td>
<td style="text-align:left;"> Bethlehem Village </td>
<td style="text-align:left;"> 0900504930 </td>
<td style="text-align:left;"> Bethlehem </td>
</tr>
<tr>
<td style="text-align:left;"> 0906050 </td>
<td style="text-align:left;"> Blue Hills </td>
<td style="text-align:left;"> 0900305910 </td>
<td style="text-align:left;"> Bloomfield </td>
</tr>
<tr>
<td style="text-align:left;"> 0907345 </td>
<td style="text-align:left;"> Branford Center </td>
<td style="text-align:left;"> 0900907310 </td>
<td style="text-align:left;"> Branford </td>
</tr>
</tbody>
</table>
]
.pull-right[
```r
plot(new_haven_sf["geometry"])
```
<!-- -->
]
---
# Reusable datasets & references
Avoid the suffering of finding table numbers on FactFinder
---
# Reusable datasets & references
Avoid the suffering of finding table numbers on FactFinder
```r
basic_table_nums[["pov_age"]]
```
```
## [1] "B17024"
```
```r
get_acs("county", table = basic_table_nums[["pov_age"]], state = "09")
```
---
# Testing, debugging, documenting
### What doesn't kill you makes you stronger
* Does this function do what I *think* it does?
* Are these the most important tasks for me & my coworkers?
* What might break by this time next month?
* How will this scale & remain relevant?
* What am I not thinking of yet?
#### Testing the `qwi_industry` function in `cwi`:
.small-text[
```r
test_that("handles years not in API", {
expect_warning(qwi_industry(1990:2000, industries = "23"), "earlier years are being removed")
expect_error(qwi_industry(1990:1994, industries = "23"), "only available")
# should only return 1996-2000
expect_equal(nrow(suppressWarnings(qwi_industry(1991:2000, industries = "23", annual = T))), 5)
})
```
]
---
# Testing, debugging, documenting
### What doesn't kill you makes you stronger
.pull-left[
* My code is amazing. Now how do I make sure someone uses it?
* If I can't explain a feature, do I really need it?
* What might someone else do wrong?
* How can I avoid "What does this do?" emails and texts?
]
.pull-right[
#### Docs website with `pkgdown`
<iframe src="https://ct-data-haven.github.io/cwi/articles/basic-workflow.html" style="border:0px #ffffff solid;" name="cwidocs" scrolling="yes" frameborder="1" marginheight="0px" marginwidth="0px" height="400px" width="800px" allowfullscreen></iframe>
]
---
background-image: url(img/sketchbook.jpg)
background-size: cover
.white-bkgnd[
# tl;dr
## Package development: lots of work upfront, totally worth it
<i class="ion ion-android-globe "></i> **DataHaven:** [ctdatahaven.org](http://ctdatahaven.org/)
<i class="ion ion-erlenmeyer-flask "></i> **Our side projects blog:** [ct-data-haven.github.io](http://ct-data-haven.github.io/)
<i class="ion ion-social-github "></i> **DataHaven on GitHub:** [github.com/CT-Data-Haven](https://github.com/CT-Data-Haven)
<i class="ion ion-code "></i> **These very slides!** [ct-data-haven.github.io/datadev](https://ct-data-haven.github.io/datadev)
]
</textarea>
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