• The Idea:
  • In many situations there are multiple pieces of data that need to be organized in a way that makes them easy to work with
  • While this problem can sometimes be solved with a single array, many other times a more powerful organizational scheme is needed
• An Example:
  • A group that has developed a categorical measure of consumer confidence wants to explore the relationships between its measure, the consumer price index (CPI), the civilian unemployment rate (in percent), and the M2 money stock (in billions of dollars) for the year 2018 (on a monthly basis)

• Arrays in General:
  • Make it very easy to perform the same operation(s) on homogeneous values
• For this Example
  • If you were only interested in the CPI, for example, you could store it in a double[] with twelve elements

• Conceptualizing Tables of Data:
  • Row-major form - a collection of rows, each of which has columns
  • Column-major form - a collection of columns, each of which has rows
• Conformal Arrays:
  • Regardless of the form, the arrays will share a common index

Choose the form that satisfies the following criteria:

• The elements of the array must be of the same type
• The indexes must be easily representable as int values

• Using One Array for Each Row:
  • Some elements would be double values and some would be String values
• Using One Array for Each Column:
  • Some arrays would contain nothing but double values and some would contain nothing but String values
  • A 0-based representation of the month can be used for the index

javaexamples/programmingpatterns/conformalarrays/ConformalArrays.java (Fragment: economicdata)

        // Month of the year
        String[] month = {
            "Jan", "Feb", "Mar", "Apr", "May", "Jun",
            "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" };

        // Consumer price index for all urban consumers
        // (not seasonally adjusted)
        double[] cpiaucns = {
          247.867, 248.991, 249.554, 250.546, 251.588, 251.989, 
          252.006, 252.146, 252.439, 252.885, 252.038, 251.233 };

        // Unemployment rate (not seasonally adjusted)
        double[] unratensa = {
            4.5, 4.4, 4.1, 3.7, 3.6, 4.2, 
            4.1, 3.9, 3.6, 3.5, 3.5, 3.7 };

        // M2 money stock (not seasonally adjusted)
        double[] m2ns = {
            13855.1, 13841.2, 14022.9, 14064.4, 13984.6, 14079.2, 
            14113.8, 14170.3, 14204.7, 14211.6, 14272.8, 14473.0 };

        // Consumer confidence
        String[] confidence = {
            "Low", "Low",      "Moderate", "High", "High", "Moderate",
            "Low", "Moderate", "Moderate", "High", "High", "High" };