Plot Categorical Data

This example shows how to plot data from a categorical array.

Load Sample Data

Load sample data gathered from 100 patients. Display the data types and sizes of the arrays from the patients MAT-file.

load patients
whos

  Name                            Size            Bytes  Class      Attributes

  Age                           100x1               800  double               
  Diastolic                     100x1               800  double               
  Gender                        100x1             13012  cell                 
  Height                        100x1               800  double               
  LastName                      100x1             13216  cell                 
  Location                      100x1             15808  cell                 
  SelfAssessedHealthStatus      100x1             13140  cell                 
  Smoker                        100x1               100  logical              
  Systolic                      100x1               800  double               
  Weight                        100x1               800  double               

Create Categorical Arrays

The workspace variable, Location, lists three unique medical facilities where patients were observed.

To access and compare data more easily, convert Location to a categorical array.

Location = categorical(Location);

Summarize the categorical array. The summary displays the number of times each category appears in Location.

summary(Location)

Location: 100×1 categorical

     County General Hospital       39 
     St. Mary's Medical Center      24 
     VA Hospital                   37 
     <undefined>                    0 

39 patients were observed at County General Hospital, 24 at St. Mary's Medical Center, and 37 at the VA Hospital.

The workspace variable, SelfAssessedHealthStatus, contains four unique values, Excellent, Fair, Good, and Poor.

Convert SelfAssessedHealthStatus to an ordinal categorical array, such that the categories have the mathematical ordering Poor < Fair < Good < Excellent.

SelfAssessedHealthStatus = categorical(SelfAssessedHealthStatus, ...
                                       ["Poor" "Fair" "Good" "Excellent"], ...
                                       Ordinal=true);

Summarize the categorical array, SelfAssessedHealthStatus.

summary(SelfAssessedHealthStatus)

SelfAssessedHealthStatus: 100×1 ordinal categorical

     Poor             11 
     Fair             15 
     Good             40 
     Excellent        34 
     <undefined>       0 

Additional statistics:

    Min         Poor       
    Median      Good       
    Max         Excellent  

Plot Histogram

Create a histogram bar plot directly from SelfAssessedHealthStatus. This categorical array is an ordinal categorical array. The categories have the ordering Poor < Fair < Good < Excellent, which determines the order of the categories along the x-axis of the plot. The histogram function plots the category counts for each of the four categories.

figure
histogram(SelfAssessedHealthStatus)
title("Self Assessed Health Status From 100 Patients")

Create a histogram of the hospital location for only the patients who assessed their health as Fair or Poor.

figure
histogram(Location(SelfAssessedHealthStatus <= "Fair"))
title("Location of Patients in Fair or Poor Health")

Create Pie Chart

Create a pie chart directly from a categorical array.

figure
pie(SelfAssessedHealthStatus);
title("Self Assessed Health Status From 100 Patients")

The function pie accepts the categorical array, SelfAssessedHealthStatus, and plots a pie chart of the four categories.

Create Pareto Chart

Create a Pareto chart from the category counts for each of the four categories of SelfAssessedHealthStatus.

figure
A = countcats(SelfAssessedHealthStatus);
C = categories(SelfAssessedHealthStatus);
pareto(A,C);
title("Self Assessed Health Status From 100 Patients")

The first input argument to pareto must be a vector. If a categorical array is a matrix or multidimensional array, reshape it into a vector before calling countcats and pareto.

Create Scatter Plot

Determine if self-assessed health is related to blood pressure readings. Create a scatter plot of Diastolic and Systolic readings for two groups of patients.

First, create x- and y-arrays of blood pressure readings for two groups of patients. The first group of patients consists of those who assess their self-health as either Poor or Fair. The second group consists of those who assess their self-health as Good or Excellent.

You can use the categorical array, SelfAssessedHealthStatus, to create logical indices. Use the logical indices to extract values from Diastolic and Systolic into different arrays.

X1 = Diastolic(SelfAssessedHealthStatus <= "Fair");
Y1 = Systolic(SelfAssessedHealthStatus <= "Fair");

X2 = Diastolic(SelfAssessedHealthStatus >= "Good");
Y2 = Systolic(SelfAssessedHealthStatus >= "Good");

X1 and Y1 are 26-by-1 numeric arrays containing data for the patients with Poor or Fair health.

X2 and Y2 are 74-by-1 numeric arrays containing data for the patients with Good or Excellent health.

Create a scatter plot of blood pressure readings for the two groups of patients. The plot shows no suggestive differences between the two groups, possibly indicating that blood pressure does not affect how these patients assessed their own health.

figure
h1 = scatter(X1,Y1,"o");
hold on
h2 = scatter(X2,Y2,"x");

title("Blood Pressure for Groups of Patients Assessing Self Health");
xlabel("Diastolic (mm Hg)")
ylabel("Systolic (mm Hg)")
legend("Poor or Fair","Good or Excellent")