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library(tidycensus)
library(tidyverse)
#census_api_key("YOUR API KEY GOES HERE")
#Get an API key by going here: https://api.census.gov/data/key_signup.html


# First this tells you what variables are on the ACS
v17 <- load_variables(2017, "acs1")

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source("https://gist.githubusercontent.com/schaunwheeler/6380637/raw/02d345971e3513f69b30fe2ba262578ac3871fe2/amortize.r")
library(tidyverse)
set.seed(1028)
testdata <- tibble(principal=rnorm(20, 200000, 10000),
                   interest=runif(20, .01, .1),
                   months=rbinom(20, 360, .5))

# This will not work because function is not vectorized
# data_withtabs <- testdata %>%
#  mutate(AmTable=amortize(p_input=principal, i_input=interest, n_months=months))

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library(tmaptools)
library(sf)
library(dplyr)
library(stringr)
library(tidycensus)


addresses <- c("3040 E Cornwallis Rd, Durham, NC") # This is RTI HQ

# Google geocodes lat/lon as 35.906156, -78.864160

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library(tidyverse)
set.seed(406)
N <- 2000


library(rbenchmark)

benchmark(
  "rowwise"={
    df <- tibble(x=runif(N), y=runif(N), z=runif(N))

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# https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-03-31/readme.md
library(tidyverse)

# Get the Data

brewing_materials <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/brewing_materials.csv')
beer_taxed <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/beer_taxed.csv')
brewer_size <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/brewer_size.csv')
beer_states <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/beer_states.csv')

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library(tidyverse)
library(survey)
library(srvyr)


data(api)

apisrs_mut <- apisrs %>%
  as_tibble() %>%
  mutate(stype_factor=parse_factor(as.character(stype), levels=c("E", "M", "H")),

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library(tidyverse)
library(tidycensus)

nyc_counties <- c("005", "047", "061", "081", "085")

acsvars <- load_variables(2015, "acs5", cache=TRUE)

options(tigris_use_cache = TRUE)
nyc_tract <- get_acs(geography="tract",
                     variables=c("B16001_001", "B16001_066", "B16001_067", "B16001_068"),

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library(tidyverse)

x <- list(1, 2, 3)
y <- list(3, 3, 3)
z <- list(100, 200, 300)

j <- function(first, second, third) (first + third) * second

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---
title: "Untitled"
author: "Stephanie"
date: "5/25/2021"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

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library(tidycensus)
library(tidyverse)

library(geofacet)

lv19 <- load_variables(2019, "acs1")

d20 <- get_decennial(
   "state",
   variables=c("HU_Tot"="H1_001N",