Ian Gow iangow

Sys.setenv(PGHOST="192.168.1.192", PGUSER="igow", PGPORT=5434L, PGDATABASE="crsp")
library(dplyr, warn.conflicts = FALSE)
library(dbplyr, warn.conflicts = FALSE)

starwars_db <- tbl_memdb(starwars %>% select(-films, -vehicles, -starships))

is_numeric <- function(df) {
  df %>%
 collect(n = 1) %&gt;%

library(rvest)
#> Loading required package: xml2
library(ggplot2)
library(dplyr, warn.conflicts = FALSE)
library(tidyr)

df <-
    read_html("https://stats.espncricinfo.com/ci/content/records/227046.html") %>%
    html_nodes("table") %>%

library(DBI)
library(dplyr, warn.conflicts = FALSE)
library(ggplot2)

pg <- dbConnect(RPostgres::Postgres())

rs <- dbExecute(pg, "SET work_mem TO '10GB'")

iclink <- tbl(pg, sql("SELECT * FROM ibes.iclink"))

The following is what I needed to do to get Python going on my M1 Mac mini to the extent that I could run code from Chapter 2 of Introduction to Machine Learning with Python.

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh
conda install scipy matplotlib ipython scikit-learn pandas pillow
conda install -c conda-forge jupyterlab

Here is a SAS macro for winsorizing data that seems to be commonly used in accounting and finance research. This code comes from replication materials provided by Fang, Huang and Karpoff ("FHK") here. Below I provide an R function that produces equivalent results.

%MACRO winsorize(var, var_out, by_var, left, right, input, output);
	%LET var_number = 1; 
	%LET var&var_number = %QSCAN(&var, &var_number, %STR( ));
	%DO %WHILE (&&var&var_number NE);
		%LET var_number = %EVAL(&var_number + 1);

Note that this requires dplyr, readr and tidyr packages to be installed.

library(dplyr, warn.conflicts = FALSE)
    
ff_ind_nums <- c(5, 10, 12, 17, 30, 38, 48, 49)

get_ff_ind <- function(num = 48) {
    t <- tempfile(fileext = ".zip")

	DROP SCHEMA tr_ibes CASCADE;

	CREATE SCHEMA tr_ibes;

	ALTER SCHEMA tr_ibes OWNER TO ibes;

	IMPORT FOREIGN SCHEMA tr_ibes
	FROM SERVER wrds
	INTO tr_ibes;

	library(rvest)
	library(dplyr, warn.conflicts = FALSE)
	library(dataverse)
	library(readr)
	library(tidyr)

	Sys.setenv("DATAVERSE_SERVER" = "dataverse.harvard.edu")

	tmp <- tempfile(fileext = ".tab")
	f <- get_file("1976-2016-president.tab", "doi:10.7910/DVN/42MVDX")

	python3 setup.py sdist bdist_wheel
	python3 -m twine upload dist/*