Colossus (version 1.3.0)

interact_them: Defines Interactions

Description

interact_them uses user provided interactions define interaction terms and update the data.table. assumes interaction is "+" or "*" and applies basic anti-aliasing to avoid duplicates

Usage

interact_them(df, interactions, new_names, verbose = 0)

Value

returns a list with two named fields. df for the updated dataframe, and cols for the new column names

Arguments

df

a data.table containing the columns of interest

interactions

array of strings, each one is of form term1?*?term2" for term1 interaction of type * or + with term2, "?" dlimits

new_names

list of new names to use instead of default, default used if entry is ''"

verbose

integer valued 0-4 controlling what information is printed to the terminal. Each level includes the lower levels. 0: silent, 1: errors printed, 2: warnings printed, 3: notes printed, 4: debug information printed. Errors are situations that stop the regression, warnings are situations that assume default values that the user might not have intended, notes provide information on regression progress, and debug prints out C++ progress and intermediate results. The default level is 2 and True/False is converted to 3/0.

See Also

Other Data Cleaning Functions: Check_Dupe_Columns(), Check_Trunc(), Check_Verbose(), Convert_Model_Eq(), Correct_Formula_Order(), Date_Shift(), Def_Control(), Def_Control_Guess(), Def_model_control(), Def_modelform_fix(), Event_Count_Gen(), Event_Time_Gen(), Joint_Multiple_Events(), Replace_Missing(), Time_Since(), factorize(), factorize_par(), gen_time_dep()

Examples

library(data.table)
a <- c(0, 1, 2, 3, 4, 5, 6)
b <- c(1, 2, 3, 4, 5, 6, 7)
c <- c(0, 1, 2, 1, 0, 1, 0)
df <- data.table::data.table("a" = a, "b" = b, "c" = c)
interactions <- c("a?+?b", "a?*?c")
new_names <- c("ab", "ac")
vals <- interact_them(df, interactions, new_names)
df <- vals$df
new_col <- vals$cols