data-raw/DATASET.R

In chan079/loedata: Data package for Lectures on Econometrics

## code to prepare `DATASET` dataset goes here
## https://www.erikhoward.net/how-to-create-an-r-data-package/
## install.packages('~/doc/thebook/loedata_1.0.0.tgz', repos=NULL, type='source')
## Steps: (i) source this file, (ii) build documents (Shift-Ctrl-D), (iii) build and install
setwd('~/doc/thebook/loedata')
library(devtools)
library(usethis)

##usethis::use_data("DATASET")

options(stringsAsFactors = FALSE)
Boyle <- read.csv('../boyle.csv')
Death <- read.csv('../deathrate.csv')
Ekc <- read.csv('../co2gdp2005.csv')
Fastfood <- readRDS('../fastfood.rds')
Firmdata <- readRDS('../opendart/firmdata2018.rds')
Firmdata$corpname <- NULL
Galtonpar <- read.csv('../galtonpar.csv')
Hcons <- read.csv('../hhsvy14.csv')
Hies <- readRDS('../hies16subset.rds')
Hmda <- readRDS('../hmda.rds')
Ivdata <- read.csv('../ivdata.csv')
Klips <- readRDS('../klips11subset.rds')
Klosa <- readRDS('../klosasubset.rds')
names(Klosa) <- gsub('^year', 'wave', names(Klosa))
Ksalary <- readRDS('../avgsal12.rds')
Ksalary <- subset(Ksalary, avgsal > 0 & emp > 0 & sales > 0)
Pubserv <- read.csv('../serv.csv')
Regko <- read.csv('../regdatako3.csv')
RegkoPanel <- read.csv('../regdatako.csv')
# smoke <- read.csv('../smoke.csv')
# Temp <- read.csv('../temperature.csv')
# twoyear <- read.csv('../twoyear.csv')
# wage2 <- readRDS('../wage2.rds')

use_data(Boyle, overwrite = TRUE)
use_data(Death, overwrite = TRUE)
use_data(Ekc, overwrite = TRUE)
use_data(Fastfood, overwrite = TRUE)
use_data(Firmdata, overwrite = TRUE)
use_data(Galtonpar, overwrite = TRUE)
use_data(Hcons, overwrite = TRUE)
use_data(Hies, overwrite = TRUE)
use_data(Hmda, overwrite = TRUE)
use_data(Ivdata, overwrite = TRUE)
use_data(Klips, overwrite = TRUE)
use_data(Klosa, overwrite = TRUE)
use_data(Ksalary, overwrite = TRUE)
use_data(Pubserv, overwrite = TRUE)
use_data(Regko, overwrite = TRUE)
use_data(RegkoPanel, overwrite = TRUE)
#use_data(smoke, overwrite = TRUE)  # Wooldridge
#use_data(Temp, overwrite = TRUE)  # Temperature
#use_data(twoyear, overwrite = TRUE)  # Wooldridge
#use_data(wage2, overwrite = TRUE)  # Wooldridge