馃摎 What?
The main selling point of {talib} against the remaining ecosystem is the Japanese Candlestick Patterns, and given that some patterns are rarely observed, if at all, the handling is a bit off if only treated as <matrix> or <data.frame>. Currently the user can do the following to summarize the indicator:
options(talib.normalize = FALSE)
table(talib::engulfing(talib::BTC))
#> CDLENGULFING
#> -100 -80 0 80 100
#> 19 11 297 12 25
While this "works" and is one of many possibilities, a dedicated class could increase the Quality of Life for the end-user if handled explicitly via summary(). The goal is to integrate the patterns into the wider R ecosystem such that, for example, <data.frame> with mixed classes can be handled gracefully without having to account for candlestick patterns explicitly. An example is how summary() handles <data.frame> with <numeric> and <character> simultaneously.
馃摎 What?
The main selling point of {talib} against the remaining ecosystem is the Japanese Candlestick Patterns, and given that some patterns are rarely observed, if at all, the handling is a bit off if only treated as
<matrix>or<data.frame>. Currently the user can do the following to summarize the indicator:While this "works" and is one of many possibilities, a dedicated class could increase the Quality of Life for the end-user if handled explicitly via
summary(). The goal is to integrate the patterns into the wider R ecosystem such that, for example,<data.frame>with mixed classes can be handled gracefully without having to account for candlestick patterns explicitly. An example is howsummary()handles<data.frame>with<numeric>and<character>simultaneously.