Data Structures in Python

Coursera MOOC / Non-credit USD 49
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Data Structures in Python

About this course

In this course, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. By the end of this course, you will be able to: • Explain how to manipulate dataframes using techniques such as selecting and indexing, boolean masking, grouping and aggregating, and merging and joining • Describe the main features and methods of core pandas data structures such as dataframes • Describe the main features and methods of core NumPy data structures such as arrays and series • Define Python tools such as libraries, packages, modules, and global variables • Describe the main features and methods of built-in Python data structures such as lists, tuples, dictionaries, and sets

What you'll learn

  • Manipulate dataframes using selecting, indexing, boolean masking, and grouping
  • Describe core pandas data structures and their main features
  • Understand core NumPy data structures and their usage
  • Define Python concepts such as libraries and modules
  • Explain built-in Python data structures

Skills you'll gain

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