Dictionaries, Frequency Tables, and Functions in Python

In this course, you’ll continue to learn the fundamentals of Python for data science. We divided these courses into four parts to make mastering the fundamentals quicker and easier. This third part builds on the knowledge you acquired in our Variables, Data Types, and Lists in Python course and our For Loops and Conditional Statements in Python course.

The demand for data science has never been higher — take advantage of this opportunity, and level up your career with Dataquest.

This course focuses on the following:

  • Developing additional data science fundamentals in Python like dictionaries and functions
  • Discovering how to build frequency tables
  • Performing real-world data analysis tasks in an interactive coding environment

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What You’ll Learn

This Dictionaries, Frequency Tables, and Functions in Python course focuses on functions, dictionaries, and frequency tables, which are vital components of data science.

At the end of this course, you’ll have the data science fundamentals you need to get started ⁠— regardless of your end goal or destination.

Enroll in this course if you want to learn how to do the following:

  • Create dictionaries and update dictionary values
  • Define key-value pairs
  • Check for values in a dictionary
  • Discover how to count with dictionaries
  • Build frequency tables
  • Loop over dictionaries
  • Define, create, combine, and debug functions
  • Employ built-in functions
  • Reuse a function with different data inputs
  • Employ keyword and positional arguments
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Data scientists command an average salary of $117k, according to Glassdoor.

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Data science jobs hold the #1 and #3 slots for the fastest-growing jobs on LinkedIn.

Python is the most popular programming language to learn in 2021, according to PYPL.

How Our Dictionaries, Frequency Tables, and Functions in Python Course Works

Through hands-on coding lessons, learners will master the basics of Python programming for data science. Most platforms teach via video-based lessons, especially at the beginner level. At Dataquest, we understand that in order to gain a truly competitive edge, you must begin coding at the start.

In order to take this course, learners must first complete our Variables, Data Types, and Lists in Python course and our For Loops and Conditional Statements in Python course. This will allow you to master key concepts such as defining default arguments, mutable and immutable data, and other tasks data analysts perform on a regular basis.

Another advantage of the Dataquest teaching method is our unique guided projects and practice problems. Both of these assets help improve your skills and expand your portfolio, which will improve your chances of impressing a hiring manager.

Finally, with Dataquest, you’ll never learn alone. We have a vast network of students and professionals who are eager to lend a helping hand. If our robust support tools and active community aren’t able to resolve your problems, we have a team of community managers on standby, ready to serve.

Here’s a glance at part three of our Python for Data Science Fundamentals course:

Enroll in this Course to learn Python for Data Science Fundamentals!

Dictionaries, Frequency Tables, and Functions in Python Lessons List


Python Dictionaries

Learn to build frequency tables using dictionaries.

Python Dictionaries and Frequency Tables

Learn to build frequency tables using dictionaries.

Python Functions: Using Built-in Functions and Creating Functions

Learn how to speed up your workflow using functions.

Python Functions: Arguments, Parameters, and Debugging

Learn how to speed up your workflow using functions.

Who Is This Course for?

This course can benefit virtually anyone. Whether you’re a beginner looking to get into the field or an intermediate user who wants to brush up on the fundamentals, you’ll find what you’re looking for right here.

Here are a few examples of people who might want to take advantage of this Python course:

Students Who Enrolled in this Course Also Enrolled in These:

If you want a complete learning experience, we recommend you enroll in our career paths. The following paths will take you from complete beginner to job-ready in less than a year:

However, if you simply want to expand your current skill-set — either to increase performance at your current job or to land a promotion ⁠— consider enrolling in the following skill paths:

Qualify for In-demand Jobs in Data Science with Python

Understanding data science fundamentals in Python can be beneficial for many different careers across a variety of industries. The skills you’ll learn in this course can help you start your journey to any of the following careers: