R/zzz.R

In business-science/correlationfunnel: Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel

# .onAttach <- function(libname,pkgname) {
#
#     bsu_rule_color <- "#2c3e50"
#     bsu_main_color <- "#1f78b4"
#
#     # Check Theme: If Dark, Update Colors
#     if (rstudioapi::isAvailable()) {
#         tryCatch({
#             theme <- rstudioapi::getThemeInfo()
#         })
#
#
#     }
#
#     bsu_main <- crayon::make_style(bsu_main_color)
#
#     msg1 <- paste0(
#         cli::rule(left = "Using correlationfunnel?", col = bsu_rule_color, line = 2),
#         bsu_main('\nYou might also be interested in applied data science training for business.\n'),
#         bsu_main('</> Learn more at - www.business-science.io </>')
#     )
#
#     msg2 <- paste0(
#         cli::rule(left = "correlationfunnel Tip #1", col = bsu_rule_color, line = 2),
#         bsu_main('\nMake sure your data is not overly imbalanced prior to using `correlate()`.\nIf less than 5% imbalance, consider sampling. :)')
#     )
#
#     msg3 <- paste0(
#         cli::rule(left = "correlationfunnel Tip #2", col = bsu_rule_color, line = 2),
#         bsu_main("\nClean your NA's prior to using `binarize()`.\nMissing values and cleaning data are critical to getting great correlations. :)")
#     )
#
#     msg4 <- paste0(
#         cli::rule(left = "correlationfunnel Tip #3", col = bsu_rule_color, line = 2),
#         bsu_main("\nUsing `binarize()` with data containing many columns or many rows can increase dimensionality substantially.\nTry subsetting your data column-wise or row-wise to avoid creating too many columns.\nYou can always make a big problem smaller by sampling. :)")
#     )
#
#     msg <- c(msg1, msg1, msg2, msg3, msg4)[sample(1:5, size = 1)]
#     packageStartupMessage(msg)
#
# }