ExpCTable {SmartEDA} | R Documentation |
Function to create frequency and custom tables
Description
this function will automatically select categorical variables and generate frequency or cross tables based on the user inputs. Output includes counts, percentages, row total and column total.
Usage
ExpCTable(
data,
Target = NULL,
margin = 1,
clim = 10,
nlim = 10,
round = 2,
bin = 3,
per = FALSE,
weight = NULL
)
Arguments
data |
dataframe or matrix |
Target |
target variable (dependent variable) if any. Default NULL |
margin |
margin of index, 1 for row based proportions and 2 for column based proportions |
clim |
maximum categories to be considered for frequency/custom table. Variables will be dropped if unique levels are higher than 'clim' for class factor/character variable. Default value is 10. |
nlim |
numeric variable unique limits. Default 'nlim' values is 3, table excludes the numeric variables which is having greater than 'nlim' unique values |
round |
round off |
bin |
number of cuts for continuous target variable |
per |
percentage values. Default table will give counts |
weight |
a vector of weights, it must be equal to the length of data |
Details
this function provides both frequency and custom tables for all categorical features. And ouput will be generated in data frame
Value
Frequency tables, Cross tables
Columns description for frequency tables:
-
Variable
is Variable name -
Valid
is Variable values -
Frequency
is Frequency -
Percent
is Relative frequency -
CumPercent
is Cumulative sum of relative frequency
Columns description for custom tables:
-
Variable
is Variable name -
Category
is Variable values -
Count
is Number of counts -
Per
is Percentages -
Total
is Total count
Examples
# Frequency table
ExpCTable(mtcars, Target = NULL, margin = 1, clim = 10, nlim = 3, bin = NULL, per = FALSE)
# Crosstbale for Mtcars data
ExpCTable(mtcars, Target = "gear", margin = 1, clim = 10, nlim = 3, bin = NULL, per = FALSE)
# Weighted frequecncy for Mtcars data
ExpCTable(mtcars, margin = 1, clim = 10, nlim = 3, bin = NULL, per = FALSE, weight = "wt")