Get historical TRX market data

Source: R/get_trx_market_data_for_last_n_days.R

Retrieves TRX market data for previous days

get_trx_market_data_for_last_n_days(
  vs_currency = "usd",
  days,
  interval = NULL,
  max_attempts = 3L
)

Arguments

vs_currency

(character): name of the base currency to benchmark TRX against (usd by default). An up-to-date list of supported currencies (both fiat and cryptocurrencies) can be retrieved with the get_supported_coingecko_currencies() function. If an unsupported vs_currency is requested, the call will fail with the respective error message.
days

(numeric or "max"): number of days to look back. If the requested number of days covers dates before 2017-11-09, the retrived data will be clipped at 2017-11-09 (the beginning of history for TRX). If days = "max", the entire available history will be retrieved. Depending on the value of days, the time interval used to present the data will differ - see "Details".
interval

(character or NULL): time interval to present the data. The only currently supported interval is daily. Defaults to NULL.
max_attempts

(integer, positive): specifies the maximum number of additional attempts to call a URL if the first attempt fails (i.e. its call status is different from 200). Additional attempts are implemented with an exponential backoff. Defaults to 3.

Value

A tibble with the following columns:

  • timestamp (POSIXct);

  • vs_currency (character): same as the argument vs_currency;

  • price (double): TRX price, as of datetime;

  • total_trading_vol (double): a 24 h rolling-window trading volume, as of datetime;

  • market_cap (double): TRX market cap, as of datetime.

Details

If days = 1 and interval = NULL, the data will be presented for every few minutes (typically 3-8 minutes). If days is between 2 and 90 (inclusive) and interval = NULL, an (approximately) hourly time step will be used. Daily data are used for days above 90. If interval = "daily", daily data will be used irrespective of the value of days.

Examples

r <- get_trx_market_data_for_last_n_days(
  vs_currency = "gbp",
  days = 30
)
print(r)

#> # A tibble: 721 x 5
#>    timestamp           vs_currency  price total_trading_vol  market_cap
#>    <dttm>              <chr>        <dbl>             <dbl>       <dbl>
#>  1 2021-06-12 22:01:14 gbp         0.0487        903566765. 3487634163.
#>  2 2021-06-12 23:01:11 gbp         0.0486        894340986. 3478379281.
#>  3 2021-06-13 00:01:41 gbp         0.0484        872891643. 3485310799.
#>  4 2021-06-13 01:00:37 gbp         0.0487        866839417. 3471402650.
#>  5 2021-06-13 02:06:54 gbp         0.0491        854218052. 3512810468.
#>  6 2021-06-13 03:01:45 gbp         0.0486        825231596. 3487461917.
#>  7 2021-06-13 04:03:45 gbp         0.0478        799819340. 3443169652.
#>  8 2021-06-13 05:02:57 gbp         0.0479        794260346. 3414856192.
#>  9 2021-06-13 06:04:21 gbp         0.0476        792537509. 3413766509.
#> 10 2021-06-13 07:06:56 gbp         0.0477        803574787. 3418660686.
#> # … with 711 more rows