Replace_Missing {Colossus}

Automatically assigns missing values in listed columns

Description

Replace_Missing checks each column and fills in NA values

Usage

Replace_Missing(df, name_list, MSV, verbose = FALSE)

Arguments

df

a data.table containing the columns of interest

name_list

vector of string column names to check

MSV

value to replace na with, same used for every column used

verbose

boolean to control if additional information is printed to the console, also accepts 0/1 integer

Value

returns a filled datatable

See Also

Other Data Cleaning Functions: Check_Dupe_Columns(), Check_Trunc(), Correct_Formula_Order(), Date_Shift(), Def_Control(), Def_Control_Guess(), Def_model_control(), Def_modelform_fix(), Joint_Multiple_Events(), Time_Since(), factorize(), factorize_par(), gen_time_dep(), interact_them()

Examples

library(data.table)
## basic example code reproduced from the starting-description vignette

df <- data.table::data.table("UserID"=c(112, 114, 213, 214, 115, 116, 117),
           "Starting_Age"=c(18,  20,  18,  19,  21,  20,  18),
             "Ending_Age"=c(30,  45,  NA,  47,  36,  NA,  55),
          "Cancer_Status"=c(0,   0,   1,   0,   1,   0,   0))
df <- Replace_Missing(df, c("Starting_Age","Ending_Age"), 70)