christophergandrud

knitr::opts_knit$set(stop_on_error = 2L)

christophergandrud

#' Generate a random password with R
#' 
#' @param n_char integer with the number of characters for the resulting 
#' password.
#' @param n_special integer with the number of special (non-letter or number)
#' characters in the password.
#' @param special_chars character vector with the special characters that can be 
#' included in the password.
#' 
#' @examples 

christophergandrud

#' Find monadic spatial weights for continuous numeric data in a time series data set
#' df a data frame containing the unit ID variable and time variables as well as 
#' 'location' and dependent variables.
#' id_var a character string identifying the unit ID variable in \code{df}.
#' time_var a character string identifying the time variable in \code{df}.
#' location_var a character string identifying the location of the units in 
#' \code{df}. This is used to create the weighting matrix. Note that the function
#' finds the relative distance between the units by subtracting their 'location'.
#' y_var a character string identifying the dependent variable in \code{df}. Note that
#' an independent variable could also be supplied.

christophergandrud

# ---------------------------------------------------------------------------- #
# Convert an HTML table of OECD member start dates to year-membership dummies
# Christopher Gandrud
# MIT License
# ---------------------------------------------------------------------------- #

# Load required packages
library(rio)
library(rvest)
library(countrycode)

christophergandrud

#' Find key features of a spell including and ordered spell ID and each spell's
#' duration 
#' 
#' @param x a time ordered vector with values identifying a spell. It is 
#' assumed that when a value in this vector changes that the spell has ended.
#' @param id logical specifying whether or not to return the spell ID
#' @param duration logical specifying whether or not to return the spell 
#' duration. 
#' 
#' @examples 

christophergandrud

# ---------------------------------------------------------------------------- #
# Create a missingness map to examine patterns of missing values across variables
# Christopher Gandrud
# MIT LICENSE
# ---------------------------------------------------------------------------- #

# Load required packages
library(WDI)
library(dplyr)
library(Amelia)

christophergandrud

#' Convert a vector into a matrix with two columns
#'
#' @param x a vector

equal_columns <- function(x) {
    round2 = function(x, digits) {
        posneg = sign(x)
        z = abs(x)*10 ^ digits
        z = z + 0.5
        z = trunc(z)

christophergandrud

#' Plot marginal effects from two-way interactions in linear regressions
#' 
#' @param obj fitted model object from \code{lm}
#' @param term1 the first constitutive term's variable name. Note b1 and b2 must 
#' be entered in the order in which they are entered into the \code{lm} model.
#' @param term2 character string of the second constitutive variable's name.
#' @param fitted numeric vector of fitted values of \code{term2} to plot for.
#' 
#' @return a \code{gg} class ggplot2 object
#'

christophergandrud

#' Rescale a vector to be within 0 and 1
#' 
#' @param x a numeric vector to rescale
#' @param na.rm logical. Whether or not to remove NA (missing) values

range01 <- function(x, na.rm = T){
    (x - min(x, na.rm = na.rm)) / 
        (max(x, na.rm = na.rm) - min(x, na.rm = na.rm))
}

christophergandrud

#' Sets valid working directory from vector of possible directories
#' 
#' @param character vector of possible working directores

set_valid_wd <- function(possible) {
    for (i in possible) {
        if (file.exists(i)) {
            setwd(i)
            message(sprintf('Working directory set as: %s', i))
        }