| rm(list=ls()) | |
| library(dplyr) | |
| library(ggplot2) | |
| library(cowplot) | |
| library(extrafont) | |
| greens <- | |
| data_frame(pop = seq(0, 50, length = 51)) %>% | |
| mutate(tol = 2 - pop/(50/2)) %>% |
Default ggplot2 aesthetics by geom.
| geom | alpha | angle | colour | family | fill | fontface | height | hjust | lineheight | linetype | shape | size | stroke | vjust | weight | width | xmax | xmin | ymax | ymin |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GeomAbline | NA | black | 1 | 0.5 | ||||||||||||||||
| GeomAnnotationMap | NA | NA | grey20 | 1 | 0.5 | |||||||||||||||
| GeomArea | NA | NA | grey20 | 1 | 0.5 | |||||||||||||||
| GeomBar | NA | NA | grey35 | 1 | 0. |
| cl | y | x | fe | |
|---|---|---|---|---|
| 1 | 1.5370923925782167 | -20.96212959102115 | 1 | |
| 1 | -1.8734183679775684 | -1.839943693864785 | 1 | |
| 1 | 7.550159713148152 | 17.039214859757113 | 1 | |
| 1 | 2.8293020975816763 | 16.50853213076337 | 1 | |
| 1 | -1.5116432128953963 | 13.428072424536378 | 1 | |
| 1 | 3.3770810866412213 | 14.014340195044714 | 2 | |
| 1 | 4.006253032023515 | -1.209196878297718 | 2 | |
| 1 | 3.4871187962096153 | 3.077224608721335 | 2 | |
| 1 | 0.042378253992417764 | -5.207642778212252 | 2 |
| ## Background: https://twitter.com/JamesBland_Econ/status/1192519670009434114 | |
| # devtools::install_github("ropensci/RSelenium") | |
| library(RSelenium) | |
| ## Start Selenium driver and browser client | |
| rsd = rsDriver(browser = "firefox") # "chrome" is the default | |
| rsc = rsd$client | |
| ## Navigate to the page |
| ## Context: https://twitter.com/hsantanna/status/1196184374481506304 | |
| ## Thanks to Will May: https://twitter.com/williamcmay/status/1196268860418281472?s=20 | |
| library(tidyverse) | |
| library(rvest) | |
| library(memoise) | |
| ssp_url = 'http://www.ssp.sp.gov.br/estatistica/pesquisa.aspx' | |
| ## get the region/municipality form |
| ### LOAD PACKAGES ### | |
| # install.packages("pacman") | |
| pacman::p_load(tidyverse, bigrquery, DBI, sf, stars, rayshader) | |
| ### DOWNLOAD GLOBAL FISHING WATCH DATA FROM GOOGLE BIGQUERY ### | |
| ## You'll need a valid BigQuery billing ID for this next part. Luckily, you can | |
| ## easily sign up for a 12-month free trial that gives you access to BQ, as well |
| ## Context: https://twitter.com/grant_mcdermott/status/1220409051013697553 | |
| library(tidycensus) | |
| # census_api_key("YOUR KEY GOES HERE", install = TRUE) | |
| library(tigris) | |
| options(tigris_use_cache = TRUE) | |
| library(sf) | |
| library(tidyverse) | |
| ## Get ZIP codes for whole US. First time you run this it will take a while, but |
| ## Context: https://twitter.com/grant_mcdermott/status/1249825585175523328 | |
| set.seed(123) | |
| m = matrix(1:10000000, ncol = 1000) | |
| x_pos = sample.int(nrow(m), size = nrow(m)/2) | |
| y_pos = sample.int(ncol(m), size = ncol(m)/2) | |
| m_pos = (y_pos-1)*nrow(m) + x_pos | |
| library(data.table) |
| ## Context: https://twitter.com/grant_mcdermott/status/1272747522562244608 | |
| ## Note: To get the most out of this function (private repos, etc.), I recommend | |
| ## adding a GitHub Personal Access Token to your .Renviron file. The easiest way | |
| ## to do this is with the {usethis} package. See here: | |
| ## https://happygitwithr.com/github-pat.html#step-by-step | |
| library(gh) | |
| library(purrr) | |
| library(data.table) |
| #' Compare expected returns of 15- vs 30-year home refi. | |
| #' | |
| #' This very simple function assumes you split your disposable income between | |
| #' mortgage repayments and stock investments. The goal is to compare ROI at the end | |
| #' of 30 years, assuming you initially have a choice between 15- and 30-year fixed rate | |
| #' mortgage. | |
| #' | |
| #' @details Under the 15-year scenario, we assume that you pay the monthly premium | |
| #' until the loan is fully repaid (i.e. after 15 years) and then immediately switch | |
| #' over to investing the exact same amount for another 15 years. Under the 30-year |