MISSION 200

Variables and Data Types

Building on what was taught in the Programming in Python mission, you will continue to build and refine your Python programming skills by learning about variables and data types. Python variables are an important programming concept to know moving forward because they allow you to store values to it so you can refer to the value using the variable you store the value to.

In this mission, you'll learn how to save values using variables and update variables, and how to work with numerical and text data. You'll also learn about the two types of numerical data types in Python, integer and float, and how to convert from one type of numerical data type to another using either `int()` or `float()`. Toward the end of the mission, you'll learn how to manipulate text or string data. As you learn about strings, you'll learn how to link or concatenate two or more strings together to form a single string. Working with strings and being able to manipulate them is part of data cleaning, a crucial skill for data scientists to have, as real-world data from datasets isn't always the cleanest. You'll learn more about working with strings in future missions as well as in our data cleaning advanced course.

While learning about Python variables and data types, you'll work with mobile app store data and company's mottoes to practice storing data to variables and further strengthen your ability to code in the Python programming language.

Objectives

  • Learn how to save values using variables.
  • Learn how to update variables.
  • Learn how to work with numerical data.
  • Learn how to work with text data.

Mission Outline

1. Saving Values
2. Variables
3. Variable Names
4. Updating Variables
5. Syntax Shortcuts
6. Integers and Floats
7. Conversion Between Types
8. Strings
9. Escaping Special Characters
10. String Operations
11. Next steps
12. Takeaways

python-for-data-science-fundamentals

Course Info:

Beginner

The median completion time for this course is 5.8 hours. View Details

This course is free and includes 7 missions, 1 guided project, and 1 tutorial.  It is the first course in the Data Analyst in Python path and Data Scientist in Python path.

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