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freeCodeCamp/curriculum/challenges/english/08-data-analysis-with-python/data-analysis-with-python-course/numpy-algebra-and-size.english.md
Beau Carnes 5ce8abc131
fix: data analysis links (#39499) 
* fix: data analysis links

* fix: add rel attributes to all links in data analysis with python section

* fix: combine rel properties into one attribute

* fix: change single quotes to double

Co-authored-by: moT01 <20648924+moT01@users.noreply.github.com>
2020-09-03 09:48:42 -07:00

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id, title, challengeType, isHidden, videoId
id title challengeType isHidden videoId
5e9a093a74c4063ca6f7c157 Numpy Algebra and Size 11 false XAT97YLOKD8

Description

Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.

More resources:

Tests

question:
  text: |
    What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?

  answers:
    - |
      Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
    - |
      NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
    - |
      NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
    - |
      Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
  solution: 4