tabulate
Frequency table
Description
Examples
Tabulate Data Vector
Create a frequency table for a vector of data.
Load the patients data set. Display the first five entries of the Gender variable. Each value indicates the gender of a patient.
load patients
Gender(1:5)ans = 5x1 cell
{'Male' }
{'Male' }
{'Female'}
{'Female'}
{'Female'}
Generate a frequency table that shows the number and percentage of Male and Female patients in the data set.
tabulate(Gender)
Value Count Percent
Male 47 47.00%
Female 53 53.00%
Tabulate Positive Integer Vector
Create a frequency table for a vector of positive integers. By default, if a vector x contains only positive integers, then tabulate returns 0 counts for the integers between 1 and max(x) that do not appear in x. To avoid this behavior, convert the vector x to a categorical vector before calling tabulate.
Load the patients data set. Display the first five entries of the Height variable. Each value indicates the height, in inches, of a patient.
load patients
Height(1:5)ans = 5×1
71
69
64
67
64
Create a frequency table that shows, in its second and third columns, the number and percentage of patients in the data set that have a particular height. Display the first five entries and the last five entries of the matrix that tabulate returns. tbl contains one row for each height between 1 and 72 inches, where 72 is the maximum height value in Height.
tbl = tabulate(Height); first = tbl(1:5,:)
first = 5×3
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
last = tbl(end-4:end,:)
last = 5×3
68 15 15
69 8 8
70 11 11
71 10 10
72 4 4
Generate a frequency table that shows Count and Percent values only for heights that appear in the Height variable. Convert Height to a categorical variable, and then call the tabulate function.
newHeight = categorical(Height); tabulate(newHeight)
Value Count Percent
60 1 1.00%
62 3 3.00%
63 7 7.00%
64 12 12.00%
65 8 8.00%
66 15 15.00%
67 6 6.00%
68 15 15.00%
69 8 8.00%
70 11 11.00%
71 10 10.00%
72 4 4.00%
Create Table Array from Tabulated Data
Create a frequency table from a character array by using tabulate. Convert the resulting cell array to a table array, and visualize the results.
Load the carsmall data set. Tabulate the data in the Origin variable, which shows the country of origin of each car in the data set. Convert the resulting cell array tbl to a table array t. Change the Value column to a categorical vector.
load carsmall tbl = tabulate(Origin); t = cell2table(tbl,'VariableNames', ... {'Value','Count','Percent'}); t.Value = categorical(t.Value)
t=6×3 table
Value Count Percent
_______ _____ _______
USA 69 69
France 4 4
Japan 15 15
Germany 9 9
Sweden 2 2
Italy 1 1
Create a bar graph from the frequency table.
bar(t.Value,t.Count) xlabel('Country of Origin') ylabel('Number of Cars')
Tabulate Data with Missing Values
Create a frequency table from a numeric vector with NaN values.
Load the carsmall data set. The MPG variable contains the miles per gallon measurement of 100 cars. For six of the cars, the MPG value is missing (NaN).
load carsmall
numcars = length(MPG)numcars = 100
nanindex = isnan(MPG); numMissingMPG = length(MPG(nanindex))
numMissingMPG = 6
Create a frequency table using MPG. Convert the matrix output from tabulate to a table, and label the table columns.
tbl = tabulate(MPG); t = array2table(tbl,'VariableNames', ... {'Value','Count','Percent'})
t=37×3 table
Value Count Percent
_____ _____ _______
9 1 1.0638
10 2 2.1277
11 1 1.0638
13 4 4.2553
14 5 5.3191
14.5 1 1.0638
15 5 5.3191
15.5 1 1.0638
16 2 2.1277
16.5 2 2.1277
17 1 1.0638
17.5 2 2.1277
18 4 4.2553
18.5 1 1.0638
19 2 2.1277
20 2 2.1277
⋮
The frequency table displays data only for the 94 cars with numeric MPG values. tabulate calculates the percentage of each MPG value in this subset of cars, not the entire set of 100 cars.
tnumcars = sum(t.Count)
tnumcars = 94