A quick introduction to the interface

In this section I will briefly introduce the most important aspects of the function calls, formals and how <NA> are handled. Below is a simple starting point; calculating the Bollinger Bands for Bitcoin:

tail(
  talib::bollinger_bands(
    talib::BTC
  )
)
#>                     UpperBand MiddleBand LowerBand
#> 2024-12-26 01:00:00 100487.38   96698.61  92909.83
#> 2024-12-27 01:00:00 100670.65   96512.96  92355.27
#> 2024-12-28 01:00:00 100632.13   96581.91  92531.69
#> 2024-12-29 01:00:00  99628.77   95576.60  91524.43
#> 2024-12-30 01:00:00  96403.53   94231.31  92059.09
#> 2024-12-31 01:00:00  95441.13   93774.23  92107.34

In itself a simple call. Below are the formals:

str(formals(talib::bollinger_bands))
#> Dotted pair list of 8
#>  $ x        : symbol 
#>  $ cols     : symbol 
#>  $ ma       : language SMA(n = 5)
#>  $ sd       : num 2
#>  $ sd_down  : symbol 
#>  $ sd_up    : symbol 
#>  $ na.bridge: logi FALSE
#>  $ ...      : symbol

All functions share the same signature x, cols, na.bridge and ..., while everything else is indicator-specific. The cols-argument is missing, but has a default value hard-coded against the upstream TA-Lib – this is also true for the remaining indicators. The cols-argument accepts a one-sided formula as follows:

tail(
  talib::bollinger_bands(
    talib::BTC,
    cols = ~close
  )
)
#>                     UpperBand MiddleBand LowerBand
#> 2024-12-26 01:00:00 100487.38   96698.61  92909.83
#> 2024-12-27 01:00:00 100670.65   96512.96  92355.27
#> 2024-12-28 01:00:00 100632.13   96581.91  92531.69
#> 2024-12-29 01:00:00  99628.77   95576.60  91524.43
#> 2024-12-30 01:00:00  96403.53   94231.31  92059.09
#> 2024-12-31 01:00:00  95441.13   93774.23  92107.34

In this case the resulting data.frame is the same as above, as the default column for which the bands are calculated is the closing price of the asset.

All indicators are wrapped by model.frame() and its functionality can be accessed via ... as follows:

tail(
  talib::bollinger_bands(
    talib::BTC,
    cols = ~close,
    subset = 1:nrow(talib::BTC) %in% 1:100
  )
)
#>                     UpperBand MiddleBand LowerBand
#> 2024-04-04 02:00:00  72605.20   68193.82  63782.44
#> 2024-04-05 02:00:00  70646.91   67502.88  64358.84
#> 2024-04-06 02:00:00  70087.36   67344.94  64602.52
#> 2024-04-07 02:00:00  70475.41   68122.29  65769.16
#> 2024-04-08 02:00:00  71820.87   69249.88  66678.89
#> 2024-04-09 02:00:00  71848.20   69372.65  66897.09

Here we only calculate the indicator on a subset of the BTC. While this may seem like a redundant ‘wow’-feature at first glance, its primary justification is in the charting interface where only parts of an indicator is of visual interest.

The <NA>-handling in {talib} works a bit differently than na.rm. Before I demonstrate this, we add some missing values randomly to BTC

BTC <- talib::BTC
BTC$close[sample(1:100, size = 20)] <- NA

The naive approach is to calculate the indicator directly:

tail(
  talib::bollinger_bands(
    BTC
  )
)
#>                     UpperBand MiddleBand LowerBand
#> 2024-12-26 01:00:00        NA         NA        NA
#> 2024-12-27 01:00:00        NA         NA        NA
#> 2024-12-28 01:00:00        NA         NA        NA
#> 2024-12-29 01:00:00        NA         NA        NA
#> 2024-12-30 01:00:00        NA         NA        NA
#> 2024-12-31 01:00:00        NA         NA        NA

Which returns <NA> for all values. This is the default behaviour. The function faithfully returns the full object with the same number of rows – filled with <NA>-values.

To avoid this you can set na.bridge = TRUE as follows:

tail(
  object <- talib::bollinger_bands(
    BTC,
    na.bridge = TRUE
  )
)
#>                     UpperBand MiddleBand LowerBand
#> 2024-12-26 01:00:00 100487.38   96698.61  92909.83
#> 2024-12-27 01:00:00 100670.65   96512.96  92355.27
#> 2024-12-28 01:00:00 100632.13   96581.91  92531.69
#> 2024-12-29 01:00:00  99628.77   95576.60  91524.43
#> 2024-12-30 01:00:00  96403.53   94231.31  92059.09
#> 2024-12-31 01:00:00  95441.13   93774.23  92107.34

Again, with the same number of rows as BTC. This behaviour is true for all functions: N-rows in, N-rows out. What na.bridge is doing under the hood, is to extract all <NA>-values, calculate the indicator and then re-adds them in their original position.

Installation

{talib} is finally on CRAN, and can be installed as follows:

install.packages("talib")

It can also be built from source with additional CMake-flags:

install.packages(
  "talib",
  type = "source",
  configure.args = "-O3 -march=native"
)

Contributing and submitting bug-reports

{talib} is still in its early stage so contributions, even if small, bug-reports, suggestions and critiques are gratefully accepted.

Visit the repository here: https://github.com/serkor1/ta-lib-R.

^{Created on 2026-04-24 with reprex v2.1.1}