eodhd is a private company that offers APIs to a set of comprehensive and high quality financial data for over 70+ exchanges across the world. This includes:
Package eodhdR2 is the second and backwards incompatible version of eodhd, allowing fast and intelligent access to most of the API’s endpoints.
A local caching system that saves API queries to the disk, improving execution time and reducing api calls on repeated queries (live quotes are never cached).
A quota management system, informing the user of how much of the API daily quota was used and how much time is left to refresh it.
Function for aggregating and organizing financial information into a single dataframe, allowing easier access to clean financial data in the wide or long format.
Wrappers for every main endpoint of the API, from prices and
fundamentals to options, macro series and sanctions lists (see Coverage
below), plus get_eodhd() as a generic interface to any
endpoint without a dedicated function.
| Family | Functions |
|---|---|
| Prices and quotes | get_prices(), get_intraday(),
get_ticks(), get_real_time(),
get_us_quote_delayed() |
| Company data | get_fundamentals(), parse_financials(),
get_bulk_fundamentals(),
get_historical_market_cap(),
get_insider_transactions() |
| Corporate actions | get_dividends(), get_splits(),
get_dividends_calendar(),
get_splits_calendar() |
| Reference data | get_tickers(), get_exchanges(),
get_exchange_details(), get_search(),
get_screener(), get_symbol_change_history(),
get_id_mapping(), get_technical() |
| Indices | get_index_list(),
get_index_composition() |
| Calendars | get_earnings(), get_earnings_trends(),
get_ipos(), get_economic_events() |
| News and sentiment | get_news(), get_sentiments(),
get_news_word_weights() |
| Macro and rates | get_macro_indicator(), get_ust_rates(),
get_policy_rates(), get_reference_rates(),
get_corporate_hqm_yields(),
get_corporate_cmdi(),
get_funding_stress_spreads(),
get_commodities() |
| Credit risk | get_sovereign_credit_ratings(),
get_sovereign_cds_spreads(),
get_cds_market_aggregates(),
get_default_spreads(),
get_sovereign_risk_premium() |
| Real estate | get_real_estate(),
get_real_estate_detailed(),
get_real_estate_series(),
get_real_estate_countries() |
| Sanctions | get_sanctions_entities(),
get_sanctions_vessels(),
get_sanctions_programs(),
get_sanctions_sources() |
| Options | get_options_contracts(),
get_options_eod(),
get_options_underlyings() |
| Bulk | get_bulk_eod(),
get_bulk_fundamentals() |
| Session and account | set_token(), get_demo_token(),
get_user_info() |
| Anything else | get_eodhd() |
Some endpoints are only available on particular subscriptions. A call to an endpoint outside your plan returns an explicit error from the API, not empty data.
# available in CRAN
install.packages("eodhdR2")
# development version
devtools::install_github("EodHistoricalData/R-Library-for-financial-data-2024")After registering in the eodhd website and choosing a subscription, all users will authenticate an R session using a token from the website. For that:
While using eodhdR2, all authentications are managed
with function eodhdR2::set_token():
eodhdR2::set_token("YOUR_TOKEN")Alternatively, while testing the API, you can use the “demo” token for demonstration.
token <- eodhdR2::get_demo_token()
eodhdR2::set_token(token)
#> ✔ eodhd API token set
#> ℹ Account name: API Documentation 2 (supportlevel1@eodhistoricaldata.com)
#> ℹ Quota: 380273 | 10000000
#> ℹ Subscription: demo
#> ✖ You are using a **DEMONSTRATION** token for testing purposes, with
#> limited access to the data repositories. See <https://eodhd.com/>
#> for registration and, after finding your token, use it with
#> function eodhdR2::set_token("TOKEN").ticker <- "AAPL"
exchange <- "US"
df_prices <- eodhdR2::get_prices(ticker, exchange)
#>
#> ── retrieving price data for ticker AAPL|US ────────────────────────────────────
#> ! Quota status: 380273|10000000, refreshing in 2.77 hours
#> ℹ cache file AAPL_US_eodhd_prices.rds saved
#> ✔ got 11536 rows of prices
#> ℹ got daily data from 1980-12-12 to 2026-09-22
head(df_prices)
#> date open high low close adjusted_close volume ticker
#> 1 1980-12-12 28.7392 28.8736 28.7392 28.7392 0.0981 469033600 AAPL
#> 2 1980-12-15 27.3728 27.3728 27.2608 27.2608 0.0931 175884800 AAPL
#> 3 1980-12-16 25.3792 25.3792 25.2448 25.2448 0.0862 105728000 AAPL
#> 4 1980-12-17 25.8720 26.0064 25.8720 25.8720 0.0883 86441600 AAPL
#> 5 1980-12-18 26.6336 26.7456 26.6336 26.6336 0.0909 73449600 AAPL
#> 6 1980-12-19 28.2464 28.3808 28.2464 28.2464 0.0964 48630400 AAPL
#> exchange ret_adj_close
#> 1 US NA
#> 2 US -0.05096840
#> 3 US -0.07411386
#> 4 US 0.02436195
#> 5 US 0.02944507
#> 6 US 0.06050605library(ggplot2)
p <- ggplot(df_prices, aes(y = adjusted_close, x = date)) +
geom_line() +
theme_light() +
labs(title = "Adjusted Prices of AAPL",
subtitle = "Prices are adjusted to splits, dividends and other corporate events",
x = "Data",
y = "Adjusted Prices")
p
ticker <- "AAPL"
exchange <- "US"
df_div <- eodhdR2::get_dividends(ticker, exchange)
#>
#> ── retrieving dividends for ticker AAPL|US ─────────────────────────────────────
#> ! Quota status: 380280|10000000, refreshing in 2.77 hours
#> ℹ cache file AAPL_US_eodhd_dividends.rds saved
#> ✔ got 92 rows of dividend data
head(df_div)
#> date ticker exchange declarationDate recordDate paymentDate period
#> 1 1987-05-11 AAPL US 1987-04-22 1987-05-15 1987-06-15 <NA>
#> 2 1987-08-10 AAPL US 1987-07-31 1987-08-14 1987-09-15 <NA>
#> 3 1987-11-17 AAPL US 1987-11-13 1987-11-23 1987-12-15 <NA>
#> 4 1988-02-12 AAPL US 1988-01-29 1988-02-19 1988-03-15 <NA>
#> 5 1988-05-16 AAPL US 1988-04-29 1988-05-20 1988-06-15 <NA>
#> 6 1988-08-15 AAPL US 1988-07-25 1988-08-19 1988-09-15 <NA>
#> value unadjustedValue currency
#> 1 0.00054 0.12096 USD
#> 2 0.00054 0.06048 USD
#> 3 0.00071 0.07952 USD
#> 4 0.00071 0.07952 USD
#> 5 0.00071 0.07952 USD
#> 6 0.00071 0.07952 USDlibrary(ggplot2)
p <- ggplot(df_div, aes(y = value, x = date)) +
geom_point(size = 1) +
theme_light() +
labs(title = "Adjusted Dividends of AAPL",
x = "Data",
y = "Adjusted Dividends")
p
ticker <- "AAPL"
exchange <- "US"
l_fun <- eodhdR2::get_fundamentals(ticker, exchange)
#>
#> ── retrieving fundamentals for ticker AAPL|US ──────────────────────────────────
#> ! Quota status: 380301|10000000, refreshing in 2.77 hours
#> ✔ querying API
#> ✔ got 13 elements in raw list
names(l_fun)
#> [1] "General" "Highlights" "Valuation"
#> [4] "SharesStats" "Technicals" "SplitsDividends"
#> [7] "AnalystRatings" "Holders" "InsiderTransactions"
#> [10] "ESGScores" "outstandingShares" "Earnings"
#> [13] "Financials"wide_financials <- eodhdR2::parse_financials(l_fun, "wide")
#>
#> ── Parsing financial data for Apple Inc. | AAPL ──
#>
#> ℹ parsing Balance_Sheet data
#> ℹ quarterly
#> ℹ yearly
#> ℹ parsing Cash_Flow data
#> ℹ quarterly
#> ℹ yearly
#> ℹ parsing Income_Statement data
#> ℹ quarterly
#> ℹ yearly
#> ✔ got 594 rows of financial data (wide format)
head(wide_financials)
#> # A tibble: 6 × 127
#> date filing_date ticker company_name frequency type_financial
#> <date> <date> <chr> <chr> <chr> <chr>
#> 1 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 2 2026-03-31 2026-05-01 AAPL Apple Inc. quarterly Balance_Sheet
#> 3 2025-12-31 2026-01-30 AAPL Apple Inc. quarterly Balance_Sheet
#> 4 2025-09-30 2025-10-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 5 2025-06-30 2025-08-01 AAPL Apple Inc. quarterly Balance_Sheet
#> 6 2025-03-31 2025-05-02 AAPL Apple Inc. quarterly Balance_Sheet
#> # ℹ 121 more variables: currency_symbol <chr>, totalAssets <dbl>,
#> # intangibleAssets <dbl>, earningAssets <dbl>, otherCurrentAssets <dbl>,
#> # totalLiab <dbl>, totalStockholderEquity <dbl>, deferredLongTermLiab <dbl>,
#> # otherCurrentLiab <dbl>, commonStock <dbl>, capitalStock <dbl>,
#> # retainedEarnings <dbl>, otherLiab <dbl>, goodWill <dbl>, otherAssets <dbl>,
#> # cash <dbl>, cashAndEquivalents <dbl>, totalCurrentLiabilities <dbl>,
#> # currentDeferredRevenue <dbl>, netDebt <dbl>, shortTermDebt <dbl>, …long_financials <- eodhdR2::parse_financials(l_fun, "long")
#>
#> ── Parsing financial data for Apple Inc. | AAPL ──
#>
#> ℹ parsing Balance_Sheet data
#> ℹ quarterly
#> ℹ yearly
#> ℹ parsing Cash_Flow data
#> ℹ quarterly
#> ℹ yearly
#> ℹ parsing Income_Statement data
#> ℹ quarterly
#> ℹ yearly
#> ✔ got 71280 rows of financial data (long format)
head(long_financials)
#> # A tibble: 6 × 9
#> date filing_date ticker company_name frequency type_financial
#> <date> <date> <chr> <chr> <chr> <chr>
#> 1 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 2 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 3 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 4 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 5 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> 6 2026-06-30 2026-07-31 AAPL Apple Inc. quarterly Balance_Sheet
#> # ℹ 3 more variables: currency_symbol <chr>, name <chr>, value <dbl>