Getting Started with Data

We have introduced several basic Python data structures: lists, strings, sets, tuples and dictionaries. Take some time to review, compare and contrast these constructs for handling various kinds of collections.

Getting Started with Data

Built-in Atomic Data Types

We will begin our review by considering the atomic data types. Python has two main built-in numeric classes that implement the integer and floating point data types. These Python classes are called intand float. The standard arithmetic operations, +, -, *, /, and ** (exponentiation), can be used with parentheses forcing the order of operations away from normal operator precedence. Other very useful operations are the remainder (modulo) operator, %, and integer division, //. Note that when two integers are divided, the result is a floating point. The integer division operator returns the integer portion of the quotient by truncating any fractional part.

The boolean data type, implemented as the Python bool class, will be quite useful for representing truth values. The possible state values for a boolean object are True and False with the standard boolean operators, and, or, and not.

>>> True
>>> False
>>> False or True
>>> not (False or True)
>>> True and True

Boolean data objects are also used as results for comparison operators such as equality (==) and greater than (>). In addition, relational operators and logical operators can be combined together to form complex logical questions. Table 1 shows the relational and logical operators with examples shown in the session that follows.

 Table 1: Relational and Logical Operators

Operation Name Operator Explanation
less than <
Less than operator
greater than > Greater than operator
less than or equal <= Less than or equal to operator
greater than or equal >= Greater than or equal to operator
equal == Equality operator
not equal ! = Not equal operator
logical and and Both operands True for result to be True
logical or
or One or the other operand is True for the result to be True
logical not not Negates the truth value, False becomes True, True becomes False

Identifiers are used in programming languages as names. In Python, identifiers start with a letter or an underscore (_), are case sensitive, and can be of any length. Remember that it is always a good idea to use names that convey meaning so that your program code is easier to read and understand.

A Python variable is created when a name is used for the first time on the left-hand side of an assignment statement. Assignment statements provide a way to associate a name with a value. The variable will hold a reference to a piece of data and not the data itself. Consider the following session:

>>> theSum = 0
>>> theSum
>>> theSum = theSum + 1
>>> theSum
>>> theSum = True
>>> theSum

The assignment statement theSum = 0 creates a variable called theSum and lets it hold the reference to the data object 0 (see Figure 3). In general, the right-hand side of the assignment statement is evaluated and a reference to the resulting data object is "assigned" to the name on the left-hand side. At this point in our example, the type of the variable is integer as that is the type of the data currently being referred to by theSum. If the type of the data changes (see Figure 4), as shown above with the boolean value True, so does the type of the variable (theSumis now of the type boolean). The assignment statement changes the reference being held by the variable. This is a dynamic characteristic of Python. The same variable can refer to many different types of data.

Figure 3: Variables Hold References to Data Objects

Figure 4: Assignment Changes the Reference