MISSION 510

NumPy Datatypes

In the previous mission, we learned how to work with CSV data using NumPy. In this mission, we'll learn about datatypes in NumPy.

In particular, you'll:

  • Learn what datatypes are available in NumPy.
  • Learn about ndarrays' limitations of holding only one type of data.
  • How to set the datatype of an ndarray.
  • How to evaluate the memory consumption of an ndarray.
  • Learn about the limitations of fixed-bit length number representations.

As with all Dataquest missions, this is an interactive learning experience. You'll be writing real Python code and using NumPy in our browser-based coding environment so there's no setup and no obstacles between you and learning!

Objectives

  • Learn more about the limitations of NumPy
  • Learn to measure the memory consumption of ndarrays

Mission Outline

  1. Introduction
  2. Fixed NumPy Datatypes
  3. Finding the Datatype
  4. Ndarray from Mixed Lists
  5. Fixed-Length Bit Representations
  6. Memory Consumption
  7. Arithmetic Overflow
  8. Float Limitations
  9. Calculating Memory Requirements
  10. Next Steps
pandas-fundamentals

Course Info:

NumPy for Data Engineers

Intermediate

This is part of our NumPy for Data Engineers course. View Details.

This course includes five missions. It is the ninth course in the Data Engineer path.

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