Package 'wrds'

Description

Displays a glimpse-like summary of a WRDS table showing column names, types, and human-readable labels, similar to dplyr::glimpse().

Usage

describe_table(wrds, library, table, n = 20, max_cols = 25)

Arguments

Value

Invisibly returns a list with components:

columns

A data frame with column_name, data_type, and label

description

Table description, or NA if unavailable

nrow

Row count

sample

A data frame with sample rows (if n > 0)

Examples

## Not run: 
wrds <- wrds_connect()
describe_table(wrds, "comp", "funda")
wrds_disconnect(wrds)

## End(Not run)

Description

Downloads company-level static data from Compustat including header SIC codes, NAICS codes, state of incorporation, and other identifying information.

Usage

get_company(
  wrds,
  region = c("na", "global"),
  columns = NULL,
  n = Inf,
  lazy = FALSE
)

Arguments

Details

The sic column contains the "header" SIC code, which is the company's most recent SIC classification stored as a character. For historical SIC codes that change over time, use get_compustat() with fill_sic = TRUE, which coalesces the historical sich (integer) with the header sic.

Value

A tibble with company header data. Default columns vary by region:

North America (from comp.company):

• gvkey, conm: Identifiers

• sic, naics: Industry classifications (character)

• state, fic, loc: Geographic information

Global (from comp.g_company):

• gvkey, conm: Identifiers

• sic, naics: Industry classifications

• fic, loc: Geographic information

See Also

get_compustat() for fundamentals data with optional SIC filling

Examples

## Not run: 
wrds <- wrds_connect()

# Get company header data
company <- get_company(wrds)

# Get global companies
g_company <- get_company(wrds, region = "global")

# Lazy query
get_company(wrds, lazy = TRUE) |>
  dplyr::filter(sic == "7370") |>
  dplyr::collect()

wrds_disconnect(wrds)

## End(Not run)

Description

Downloads financial statement data from Compustat with standard filters for clean, analysis-ready data.

Usage

get_compustat(
  wrds,
  frequency = c("annual", "quarterly"),
  region = c("na", "global"),
  start_date = NULL,
  end_date = NULL,
  columns = NULL,
  add_columns = NULL,
  indfmt = "INDL",
  consol = "C",
  fill_sic = FALSE,
  n = Inf,
  lazy = FALSE
)

Arguments

Details

Default filters follow standard practice for most research applications. Region-specific filters are applied automatically based on region:

• datafmt: "STD" for North America, "HIST_STD" for Global

• popsrc: "D" (domestic) for North America, "I" (international) for Global

North America and Global data have different structures and should not be combined without careful column harmonization.

Value

A tibble with Compustat fundamentals. Default columns vary by region:

North America (from comp.funda / comp.fundq):

• Identifiers: gvkey, cusip, tic, conm, datadate

• Time: fyear/fyearq, fyr/fqtr

• Income: ni/niq, ib/ibq, oiadp/oiadpq, revt/revtq

• Balance sheet: at/atq, lt/ltq, seq/seqq, ceq/ceqq

• Market: csho/cshoq, prcc_f/prccq

• Other: sale/saleq, capx/capxy, che/cheq, dlc/dlcq, dltt/dlttq

• Industry: sich (historical SIC); sic (when fill_sic = TRUE, coalesced from sich and header SIC)

Global (from comp.g_funda / comp.g_fundq):

• Identifiers: gvkey, isin, conm, datadate

• Geography: loc, fic, exchg

• Similar financial variables (with some differences, e.g., nit/nitq instead of ni/niq)

See Also

link_ccm() for CRSP-Compustat linking, get_company() for company header data

Examples

## Not run: 
wrds <- wrds_connect()

# Annual North America fundamentals
funda <- get_compustat(wrds)

# Quarterly with date filter
fundq <- get_compustat(wrds,
  frequency = "quarterly",
  start_date = "2020-01-01",
  end_date = "2023-12-31"
)

# Global annual
g_funda <- get_compustat(wrds, region = "global")

# Lazy query for further filtering
get_compustat(wrds, lazy = TRUE) |>
  dplyr::filter(fyear >= 2020) |>
  dplyr::select(gvkey, datadate, at, lt) |>
  dplyr::collect()

# Fill missing SIC codes with header SIC from comp.company
funda_sic <- get_compustat(wrds, fill_sic = TRUE)

# Preview first 100 rows before full download
preview <- get_compustat(wrds, n = 100)

wrds_disconnect(wrds)

## End(Not run)

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)

Arguments

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()

Value

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

See Also

describe_table() to explore table structure, list_tables() to list available tables in a library

Examples

## Not run: 
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)

## End(Not run)

Description

Downloads the CCM (CRSP-Compustat Merged) linking table that maps CRSP PERMNOs to Compustat GVKEYs with valid date ranges.

Usage

link_ccm(
  wrds,
  linktype = c("LC", "LU", "LS"),
  linkprim = c("P", "C"),
  n = Inf,
  lazy = FALSE
)

Arguments

Details

The linking table comes from crsp.ccmxpf_lnkhist. Missing linkenddt values indicate ongoing links and are replaced with the maximum date in the table for easier date-range joins.

To use the link, join on gvkey and ensure your observation date falls within the linkdt to linkenddt range.

Value

A tibble with columns:

gvkey

Compustat company identifier

permno

CRSP permanent security identifier

linkdt

Start date of the link

linkenddt

End date of the link (missing values replaced with max date)

linktype

Type of link

linkprim

Link primacy

References

Ian Gow, Financial Accounting Research, Chapter on Identifiers: https://iangow.github.io/far_book/identifiers.html

See Also

get_compustat()

Examples

## Not run: 
wrds <- wrds_connect()
ccm <- link_ccm(wrds)

# Join with Compustat data
compustat <- get_compustat(wrds)
compustat |>
  dplyr::inner_join(ccm, by = dplyr::join_by(gvkey)) |>
  dplyr::filter(datadate >= linkdt, datadate <= linkenddt)

wrds_disconnect(wrds)

## End(Not run)

Description

Downloads the WRDS-provided linking table that maps IBES tickers to CRSP PERMNOs with valid date ranges and match quality scores.

Usage

link_ibes_crsp(wrds, max_score = 5L, n = Inf, lazy = FALSE)

Arguments

Details

The linking table comes from wrdsapps_link_crsp_ibes.ibcrsphist.

To use the link, join on ticker and ensure your observation date falls within the sdate to edate range.

Value

A tibble with columns:

ticker

IBES ticker

permno

CRSP permanent security identifier

sdate

Start date of the link

edate

End date of the link

score

Match quality score (1 = best, 6 = worst)

References

WRDS IBES-CRSP Linking Table Documentation: https://wrds-www.wharton.upenn.edu/documents/796/IBES_CRSP_Linking_Table_by_WRDS.pdf

See Also

link_ccm()

Examples

## Not run: 
wrds <- wrds_connect()
ibes_link <- link_ibes_crsp(wrds)

# Join with IBES data on ticker and date range
ibes_data |>
  dplyr::inner_join(ibes_link, by = dplyr::join_by(ticker)) |>
  dplyr::filter(date >= sdate, date <= edate)

wrds_disconnect(wrds)

## End(Not run)

Description

Returns a tibble of WRDS schemas the user has access to, with human-readable product names where available.

Usage

list_subscriptions(wrds)

Arguments

Value

A tibble with columns schema and product.

Examples

## Not run: 
wrds <- wrds_connect()
list_subscriptions(wrds)
wrds_disconnect(wrds)

## End(Not run)

Description

Returns a tibble of table names within a WRDS library (schema), with human-readable descriptions where available.

Usage

list_tables(wrds, library)

Arguments

Value

A tibble with columns table and description.

Examples

## Not run: 
wrds <- wrds_connect()
list_tables(wrds, "comp")
wrds_disconnect(wrds)

## End(Not run)

Description

Extracts the first two characters from SIC codes to create broader industry classifications.

Usage

sic_2digit(sic)

Arguments

Details

SIC codes are hierarchical: the first two digits represent major industry groups (e.g., "54" = Retail-Food Stores), while the full 4-digit code provides more specific classifications (e.g., "5412" = Retail-Convenience Stores).

Value

A character vector of 2-digit SIC codes.

Examples

# Convenience Stores (SIC 5412) -> Retail-Food Stores (54)
sic_2digit(5412)
# [1] "54"

sic_2digit(c(5412, 5400))
# [1] "54" "54"

Description

Establishes a connection to the WRDS PostgreSQL server using credentials stored securely in the system keyring.

Usage

wrds_connect(user_key = "wrds_user", password_key = "wrds_pw", keyring = NULL)

Arguments

Details

Credentials must be set up before first use with wrds_set_credentials(). The connection uses bigint = "numeric" so that 64-bit integers from PostgreSQL are returned as doubles, which avoids overflow and works well with tidyverse functions.

Value

A DBIConnection object for the WRDS PostgreSQL database.

See Also

wrds_disconnect(), wrds_set_credentials()

Examples

## Not run: 
wrds <- wrds_connect()
list_subscriptions(wrds)
wrds_disconnect(wrds)

## End(Not run)

Description

Closes a WRDS database connection.

Usage

wrds_disconnect(wrds)

Arguments

Value

Invisibly returns TRUE if disconnection was successful.

Examples

## Not run: 
wrds <- wrds_connect()
wrds_disconnect(wrds)

## End(Not run)

Description

A mapping of WRDS schema names to human-readable product names. Used by list_subscriptions() to enrich results, and available for users who want to look up product names directly.

Usage

wrds_products

Format

A data frame with 613 rows and 2 columns:

schema

WRDS schema or product code

product

Human-readable product name

Source

https://wrds-www.wharton.upenn.edu/users/products/

Description

Interactively stores WRDS username and password in the system keyring for secure, persistent storage.

Usage

wrds_set_credentials(
  user_key = "wrds_user",
  password_key = "wrds_pw",
  keyring = NULL
)

Arguments

Details

This function prompts for username and password interactively. Credentials are stored securely using the operating system's keyring (Keychain on macOS, Credential Manager on Windows, Secret Service on Linux).

Value

Invisibly returns TRUE on success.

Examples

## Not run: 
wrds_set_credentials()

## End(Not run)

Description

Interactively updates the WRDS password stored in the system keyring without changing the username.

Usage

wrds_update_password(password_key = "wrds_pw", keyring = NULL)

Arguments

Value

Invisibly returns TRUE on success.

See Also

wrds_set_credentials(), wrds_connect()

Examples

## Not run: 
wrds_update_password()

## End(Not run)