| library(gapminder) | |
| library(tidyverse) | |
| library(broom) | |
| library(huxtable) | |
| library(lfe) | |
| # Example dataset (via gapminder package) | |
| glimpse(gapminder) | |
| # Create a function to make looping easier |
| # Required packages | |
| # dplyr | |
| # stringr | |
| # glue | |
| lookfor <- function(df, pattern) { | |
| var_i <- names(df) %>% stringr::str_detect(stringr::regex(pattern, ignore_case = TRUE)) | |
| return(names(df)[var_i]) | |
| } |
| # https://ryan-holben.github.io/tex/latex/installation/macos/2016/08/21/installing-tex-on-mac/ | |
| brew cask install basictex | |
| sudo tlmgr update --self | |
| sudo tlmgr install texliveonfly | |
| sudo tlmgr install latexmk | |
| sudo tlmgr install biber | |
| sudo tlmgr install standalone | |
| sudo tlmgr install preview |
| * Marginal means in Stata | |
| * https://www.stata.com/features/overview/marginal-analysis/ | |
| * Probit | |
| webuse nlsw88, clear | |
| quietly probit union wage c.age c.age#c.age collgrad | |
| margins, dydx(age) |
Sources:
County officials stressed the presence of cases, or lack thereof, should not affect how people operate during the coronavirus pandemic.
Staying at home, practicing social distancing and washing your hands are just some practices to maintain, regardless of the number of cases reported in your community.
| # Ignore everything in this directory (place in the directory you want to ignore) | |
| * | |
| # Except this file | |
| !.gitignore |
| # https://github.com/kohler/gifsicle/issues/12 | |
| # brew install imagemagick gifsicle | |
| convert *.jpeg GIF:- | gifsicle --delay=50 --loop --optimize=2 --colors=256 --multifile - > out.gif |
| g_see <- function(dat) { | |
| plot( | |
| googleVis::gvisTable(dat, | |
| options = list(page = "enable") | |
| ) | |
| ) | |
| } | |
| l = ["m"] | |
| def return_list(lst=l): | |
| return(f"lst={lst} and l={l}") | |
| l.append("n") | |
| print(return_list()) # lst=['m', 'n'] and l=['m', 'n'] | |
| print(return_list(lst=l)) # lst=['m', 'n'] and l=['m', 'n'] | |
| l = ["n"] | |
| print(return_list()) # lst=['m', 'n'] and l=['n'] |
| # Adapted from https://www.kaggle.com/jamesleslie/titanic-neural-network-for-beginners | |
| def display_more(df, nrows=1_000, ncols=1_000): | |
| with pd.option_context("display.max_rows", nrows, "display.max_columns", ncols): | |
| display(df) |
