Python Programming with Jupyter and Anaconda
Python is a programming language that is widely used in the industry for data science, machine learning, web development, and more. In this lesson, we will introduce you to the basic concepts of Python programming, including variables, data types, and control flow.
Variables are used to store data in programming languages, and they can hold different types of data. In Python, you don’t need to declare the data type of a variable before using it. Instead, Python will automatically infer the data type based on the value assigned to the variable. For example, you can create a variable called x and assign the value 5 to it like this:
>>> x = 5
In this case, Python will create a variable named x and assign the integer value 5 to it.
Python supports several data types, including integers, floating-point numbers, strings, and booleans. Integers are whole numbers, like 1, 2, 3, and so on. Floating-point numbers are decimal numbers, like 3.14, 2.71828, and so on. Strings are used to represent text and are enclosed in single or double quotes, like 'hello' or "world". Booleans are used to represent true or false values and can be either True or False.
Control flow refers to the order in which statements are executed in a program. Python supports several control flow statements, including if/else statements, for loops, and while loops. If/else statements allow you to execute statements based on a condition. For example, you can use an if statement to check if a variable is greater than 10, and execute some code if the condition is true. For loops allow you to iterate over a sequence of values, like a list or a string. While loops allow you to execute a block of code repeatedly as long as a condition is true.
If you want to learn more about Python programming, we recommend the following resources:
Python documentation
Python for Data Science Handbook
Python Crash Course
Now that you have a basic understanding of Python programming, let’s move on to the next lesson where you will learn how to work with Jupyter Notebooks.
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