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Data Types for Data Science in Python

4.0+
27 reviews
Intermediate

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

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4 Hours15 Videos47 Exercises58,902 Learners

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Course Description

Have you got your basic Python programming chops down for Data Science but are yearning for more? Then this is the course for you. Herein, you'll consolidate and practice your knowledge of lists, dictionaries, tuples, sets, and date times. You'll see their relevance in working with lots of real data and how to leverage several of them in concert to solve multistep problems, including an extended case study using Chicago metropolitan area transit data. You'll also learn how to use many of the objects in the Python Collections module, which will allow you to store and manipulate your data for a variety of Data Scientific purposes. After taking this course, you'll be ready to tackle many Data Science challenges Pythonically.
  1. 1

    Fundamental Sequence Data Types

    Free

    This chapter will introduce you to the fundamental Python data types - lists, sets, and strings. These data containers are critical as they provide the basis for storing and looping over ordered data. To make things interesting, you'll apply what you learn about these types to answer questions about the New York Baby Names dataset!

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    Introduction and lists
    50 xp
    Manipulating lists for fun and profit
    100 xp
    Looping over lists
    100 xp
    Meet the tuples
    50 xp
    Data type usage
    50 xp
    Using and unpacking tuples
    100 xp
    Making tuples by accident
    100 xp
    Strings
    50 xp
    Formatted String Literals ("f" strings)
    100 xp
    Combining multiple strings
    100 xp
    Finding strings in other strings
    100 xp
  2. 2

    Dictionaries - The Root of Python

    At the root of all things Python is a dictionary. Herein, you'll learn how to use them to safely handle data that can viewed in a variety of ways to answer even more questions about the New York Baby Names dataset. You'll explore how to loop through data in a dictionary, access nested data, add new data, and come to appreciate all of the wonderful capabilities of Python dictionaries.

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In the following tracks

Python Programmer

Collaborators

Hugo Bowne-Anderson
Yashas Roy
Jason Myers HeadshotJason Myers

Co-Author of Essential SQLAlchemy and Software Engineer

Jason Myers is a software engineer and author. His area of expertise is in developing data analytics platforms. He has also written the Essential SQLAlchemy book, co-authored with Rick Copeland, that introduces you to working with relational databases in Python.
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  • Jaime P.
    2 months

    Excellent course. It was a fruitful learning experience for people like my, who are starting y the programming word.

  • Saúl V.
    4 months

    Great course. The content is well organized and selected.

  • William M.
    5 months

    It could be the most important course for a Python developer!!!

  • Muhammad M.
    5 months

    Excellent

  • Stefan W.
    6 months

    Great overview of more advanced features. To be honest, some of the examples were not intuitive. It would help to have really simple examples that help one focus on the features.

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"Excellent course. It was a fruitful learning experience for people like my, who are starting y the programming word."

Jaime P.

"Great course. The content is well organized and selected."

Saúl V.

"It could be the most important course for a Python developer!!!"

William M.

Join over 11 million learners and start Data Types for Data Science in Python today!

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