| Title: | Tidy Fundamental Financial Data from 'SEC's 'EDGAR' 'API' | 
| Version: | 1.0.1 | 
| Description: | Streamline the process of accessing fundamental financial data from the United States Securities and Exchange Commission's ('SEC') Electronic Data Gathering, Analysis, and Retrieval system ('EDGAR') 'API' https://www.sec.gov/edgar/sec-api-documentation, transforming it into a tidy, analysis-ready format. | 
| License: | MIT + file LICENSE | 
| Encoding: | UTF-8 | 
| RoxygenNote: | 7.2.3 | 
| Imports: | dplyr, jsonlite, parallel, tidyr, httr | 
| URL: | https://gerardgimenezadsuar.github.io/tidyedgar/ | 
| NeedsCompilation: | no | 
| Packaged: | 2024-02-09 11:12:56 UTC; gerard | 
| Author: | Gerard Gimenez-Adsuar [aut, cre] | 
| Maintainer: | Gerard Gimenez-Adsuar <gerard@solucionsdedades.cat> | 
| Repository: | CRAN | 
| Date/Publication: | 2024-02-09 15:20:02 UTC | 
Getting quarterly data from all public companies from EDGAR
Description
Getting quarterly data from all public companies from EDGAR
Usage
get_qdata(
  account = "Revenues",
  years = 2020:2023,
  quarters = c("Q3"),
  max_cores = TRUE
)
Arguments
| account | A string representing the account (eg NetIncomeLoss, Revenues, OperatingIncomeLoss, ...) | 
| years | A sequence of numeric values representing the years. | 
| quarters | A string representing the quarter. | 
| max_cores | Boolean limiting the number of cores to 1. | 
Value
A dataframe
Examples
get_qdata(account = "NetIncomeLoss", years = 2022:2023, quarters = c("Q4"))
Getting yearly data from all public companies from EDGAR
Description
Getting yearly data from all public companies from EDGAR
Usage
get_ydata(account = "Revenues", years = 2020:2023)
Arguments
| account | A string representing the account (eg NetIncomeLoss, Revenues, OperatingIncomeLoss, ...) | 
| years | A sequence of numeric values representing the years. | 
Value
A dataframe
Examples
get_ydata(account = "NetIncomeLoss", years = 2022:2023)
Data wrangling for tidy fundamental data from EDGAR
Description
Data wrangling for tidy fundamental data from EDGAR
Usage
prepare_data(df = NULL, quarterly = TRUE, ...)
Arguments
| df | A dataframe, output from get_qdata() or get_ydata(). | 
| quarterly | Boolean indicating if quarterly data is present. | 
| ... | Additional dataframes to be combined from other accounts (NetIncomeLoss, OperatingIncomeLoss, etc). | 
Value
A dataframe
Examples
revenue <- data.frame(
taxonomy = rep("us-gaap", 3),
tag = rep("Revenues", 3),
ccp = rep("CY2020", 3),
uom = rep("USD", 3),
label = rep("Revenues", 3),
description = rep("Amount of revenue recognized from goods sold, services rendered, ...", 3),
pts = rep(2762, 3),
data.accn = c("0001564590-22-012597", "0000002178-23-000038", "0001654954-22-005679"),
data.cik = c(2098, 2178, 2186),
data.entityName = c("ACME CORP", "ADAMS RESOURCES, INC.", "BK TECHNOLOGIES"),
data.loc = c("US-CT", "US-TX", "US-FL"),
data.start = rep("2020-01-01", 3),
data.end = rep("2020-12-31", 3),
data.val = c(164003040, 1022422000, 44139000),
year = rep(2020, 3))
netincome <- data.frame(
taxonomy = rep("us-gaap", 3),
tag = rep("NetIncomeLoss", 3),
ccp = rep("CY2020", 3),
uom = rep("USD", 3),
label = rep("NetIncomeLoss", 3),
description = rep("Net Income from operating activities", 3),
pts = rep(2762, 3),
data.accn = c("0001564590-22-012597", "0000002178-23-000038", "0001654954-22-005679"),
data.cik = c(2098, 2178, 2186),
data.entityName = c("ACME CORP", "ADAMS RESOURCES, INC.", "BK TECHNOLOGIES"),
data.loc = c("US-CT", "US-TX", "US-FL"),
data.start = rep("2020-01-01", 3),
data.end = rep("2020-12-31", 3),
data.val = c(100000, 200000, 4000000),
year = rep(2020, 3))
prepare_data(revenue,netincome, quarterly = FALSE)
Helper function for quarterly financial data retrieval
Description
Helper function for quarterly financial data retrieval
Usage
retrieve_data(account, year, quarter)
Arguments
| account | A string representing the account. | 
| year | A numeric value representing the year. | 
| quarter | A string representing the quarter. | 
Value
A dataframe
Safely calculating the max.
Description
Safely calculating the max.
Usage
safe_max(x, na.rm = FALSE)
Arguments
| x | A number. | 
| na.rm | Boolean. | 
Value
A number.
Getting a summary with the basic financials for all companies
Description
Getting a summary with the basic financials for all companies
Usage
yearly_data(years = 2020:2023)
Arguments
| years | A sequence of numeric values representing the years. | 
Value
A dataframe
Examples
yearly_data(years = 2022:2023)