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.
ExpCTable( data, Target = NULL, margin = 1, clim = 10, nlim = 10, round = 2, bin = 3, per = FALSE )
| 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. |
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
this function provides both frequency and custom tables for all categorical features. And ouput will be generated in data frame
# Frequency table ExpCTable(mtcars, Target = NULL, margin = 1, clim = 10, nlim = 3, bin = NULL, per = FALSE)#> Variable Valid Frequency Percent CumPercent #> 1 cyl 4 11 34.38 34.38 #> 2 cyl 6 7 21.88 56.26 #> 3 cyl 8 14 43.75 100.01 #> 4 cyl TOTAL 32 NA NA #> 5 vs 0 18 56.25 56.25 #> 6 vs 1 14 43.75 100.00 #> 7 vs TOTAL 32 NA NA #> 8 am 0 19 59.38 59.38 #> 9 am 1 13 40.62 100.00 #> 10 am TOTAL 32 NA NA #> 11 gear 3 15 46.88 46.88 #> 12 gear 4 12 37.50 84.38 #> 13 gear 5 5 15.62 100.00 #> 14 gear TOTAL 32 NA NA# Crosstbale for Mtcars data ExpCTable(mtcars, Target = "gear", margin = 1, clim = 10, nlim = 3, bin = NULL, per = FALSE)#> VARIABLE CATEGORY gear:3 gear:4 gear:5 TOTAL #> 1 cyl 4 1 8 2 11 #> 2 cyl 6 2 4 1 7 #> 3 cyl 8 12 0 2 14 #> 4 cyl TOTAL 15 12 5 32 #> 5 vs 0 12 2 4 18 #> 6 vs 1 3 10 1 14 #> 7 vs TOTAL 15 12 5 32 #> 8 am 0 15 4 0 19 #> 9 am 1 0 8 5 13 #> 10 am TOTAL 15 12 5 32 #> 11 gear 3 15 0 0 15 #> 12 gear 4 0 12 0 12 #> 13 gear 5 0 0 5 5 #> 14 gear TOTAL 15 12 5 32