get_table: Download data from any WRDS table

Description

Generic function to download data from any table in the WRDS database. Returns a lazy table by default, allowing you to build queries with dplyr before collecting.

Usage

get_table(wrds, library, table, columns = NULL, n = Inf, lazy = TRUE)

Value

A tbl_lazy object (if lazy = TRUE) or a tibble (if lazy = FALSE).

Arguments

wrds: A DBIConnection object returned by wrds_connect().
library: Character. The name of the library (schema), e.g., "crsp", "comp", "ibes".
table: Character. The name of the table within the library.
columns: Character vector of columns to return. If NULL (default), returns all columns. Use describe_table() to see available columns.
n: Maximum number of rows to return. Defaults to Inf (all rows). Use a smaller value (e.g., n = 100) to preview data.
lazy: If TRUE (default), returns a lazy tbl for further filtering with dplyr. Set to FALSE to collect immediately.

Details

This function provides generic access to any WRDS table. For commonly-used tables with standard research filters, prefer the specialized functions:

get_compustat() for Compustat fundamentals with standard filters
get_company() for company header data
link_ccm() for CRSP-Compustat linking

The lazy table can be filtered, selected, and mutated using dplyr verbs, which are translated to SQL and executed on the server:

get_table(wrds, "crsp", "msf") |>
  filter(date >= "2025-01-01") |>
  select(permno, date, ret, prc) |>
  collect()

Examples

Run this code

if (FALSE) {
wrds <- wrds_connect()

# Preview table structure first
describe_table(wrds, "crsp", "msf")

# Get a lazy table and build your query
get_table(wrds, "crsp", "msf") |>
  dplyr::filter(date >= "2025-01-01") |>
  dplyr::select(permno, date, ret, prc, vol) |>
  dplyr::collect()

# Collect immediately with specific columns
get_table(wrds, "crsp", "dsf",
  columns = c("permno", "date", "ret", "prc"),
  lazy = FALSE,
  n = 1000
)

# Access any table in any library
get_table(wrds, "ibes", "statsum_epsus") |>
  dplyr::filter(fpedats >= "2025-01-01") |>
  dplyr::collect()

wrds_disconnect(wrds)
}