Pyton Fundamental

Python Fundamental Overview In this handout, we will cover the basics of Python statements, variables, identifiers, and the commonly used data types: integers, floating-point numbers, strings, and booleans. Understanding these data types is essential for performing arithmetic operations, handling textual data, and making logical decisions in programs. Additionally, we will explore fundamental control structures, including for and while loops, which allow for repeated execution of code blocks, as well as if, else, and elif statements for conditional decision-making. By mastering these basics, you will gain the foundational skills needed to write and understand simple Python programs. 1 Statements, Variables, and Identifiers A statement is a command that tells the program to do something. assignment of a value to a variable 12 This statement creates the variable x and assigns it the value 12 using the assignment operator. Here's another example: addition of two numbers 1+2 This statement adds the numbers 1 and 2 using the addition operator +. Let's look at one more statement: comparison of two numbers 53 This statement checks if 5 is greater than 3 using the comparison operator >. Programs store and use data, which is kept in the computer's memory. A Python statement often contains one or more variables. A variable holds a value that you can use later in your program. In simple terms, a variable is a name that points to a value stored in the computer's memory. assignment of different values to different variables city_name "Washington DC" average temperature num_of_parks 24 18.3 is_coastal_city False In this snippet (small piece of code), city name, average_temperature, num_of_parks, and is_coastal_city are all variables. We assign values to these variables using the operator. Each line here is an assign-ment statement. You can later use these variables in your code to retrieve their values and update them by assigning new values. Notice that each of these variables stores different types of data. While city_name stores a text, average_temperature and num_of_parks store numerical values, whereas is_coastal_city stores a True/False kind of data. Note 1: Python is case-sensitivel This means city_name and City_Name are not the same. Note 2: In all the above statements, there's a space on both sides of the sign. This is recommended by the style guide for python code (PEP 8), which makes your code easier to read. You can read more about the PEP 8 style guide on the website: https://www.python.org/dev/peps/pep-0008/ As we go through the course, you are expected to follow these rules. An identifier is a name (like city_name or num_of parks in the examples) that you create to name variables, functions, classes, etc. Identifiers must follow these rules: Identifiers can be made up of letters (a-z, A-Z), digits (0-9), and underscores (). Space is not allowed. Identifiers cannot start with a digit. For example, 1day is invalid, but day 1 is valid. Identifiers can be as long as you want. You cannot use special symbols like !,, #,, etc. The dash is used as the minus operator. Keywords cannot be used as identifiers. Keywords (such as False, if, lambda, and import) are reserved words in Python that have special meanings and cannot be used as names for variables or functions. 2 Warning Python has several built-in functions such as print(), type(), sum(), len(), min(), max(), and id(), among others. You will become familiar with these functions as you progress. Although it is technically possible to use these names as variable names, doing so is considered very poor programming practice and is strongly discouraged. For a full list of keywords, please refer to https://docs.python.org/3/reference/lexical analysis.htal@keywords. Alternatively, you can run import keyword keyword.kwlist inside a Jupyter Lab cell. Yet, another alternative is to open the Command Prompt from Anaconda Navigator and run python help() keywords 2 print() Function A function is a pre-written block of code that performs a specific task. You can call a function by writing its name followed by parentheses (). Data given to a function inside the parentheses () is called an argument. The print() function displays output on the screen. print() function example interest "Data Analysis" print(interest) This code yields: Data Analysis In this example, interest is the argument passed to the print() function, and print() displays the value of this argument on the computer screen. The print() function can accept more than one argument separated by a comma.. print() function with more than one argument city_name "Washington DC" print("Hi,", "Welcome to", city_name, ".") This code yields: Hi, Welcome to Washington DC. In this example, city name is a string, which is a sequence of characters enclosed in double quotes". Here is another example another print() example num 15 num 26 result num 1 num_2 print(num 1, "", num 2, "", result) This code yields: 5*6-30 print() function print() is a built-in (ready-to-use) function that displays the output on the computer screen. string is python's text type and we will discuss it shortly. 3 Python Data Types In Python, we can store different kinds of data in a variable. Different data types can perform different tasks. In the examples above, we have seen some of Python's most common four data types: my_name is a string (str), hourly_wage is a floating-point number (float). number of kids is an integer (int), and is employed is a boolean (bool). These types are often referred to as Python's basic data types because they store single values. The following shows some of the most commonly used data structures in Python: Built-in Data Types Basic Complex int (Numeric Integer type float (Numeric Host type) example: 3.14 0.2 str (Text type) xample: 'sc bool (Boolean type) exemples True, Falsa list A collection of items inside namples 12,-4, "De tuples A collection of items inside samples 12.4-91 set A set of iterns inside (1 Cages 12.4.201 dictionary A confection of key, value pairs inside() 100. Figure 1: Most common data types We will learn basic data types first before diving into complex ones. It is noteworthy that Python also has a data type called complex for handling complex numbers, which are written with a j as the imaginary part. We will not use this data type in this class. 3.1 int: Python's Numerical Integer Type int is Python's built-in type for storing integer numbers. An integer is a whole number without a decimal point. The following example assigns an int to a variable: assigning int value to a variable number 1 15