More package author’s introduction, please access this link
Instead of loading everything at once into your RAM, you divide your data into chunks.
To quote author of the disk.frame package: “we go from”R can only deal with data that fits in RAM"
Connect from R to Wharton Research Data Services
to set up connection from R to WRDS (here)
library(RPostgres)
library(dplyr)
# I've set up wrds connection before hand. # Please use your username and password here.
Information can be found in CRSP/COMPUSTAT MERGED DATABASE GUIDE
Change Identifiers:
Ticker: can be reassign to another company - abbreviation used to uniquely identify publicly-traded shares of a stock
CUSIP: A company can have multiple CUSIPS due to structural changes.
more information can be found in URSA Labs
This example is from Arrow Vignettes
arrow
best when working with big data
Prep
library("arrow", warn.conflicts = FALSE)
library("dplyr", warn.conflicts = FALSE)
check if S3 support is included.