Learn how to create a NumPy ARRAY, use broadcasting, ACCESS VALUES, manipulate arrays, and much more in this PYTHON NUMPY tutorial.
Type of Material:
Online Course Module
Recommended Uses:
Self-paced; lecture
Technical Requirements:
Basic programming and data structure knowledge
Identify Major Learning Goals:
This web site aims for helping those who are learning data science to use an array data structure of Numpy for more compact, faster access in reading and writing items, being more convenient and more efficient.
Upon completion of this material, learners should be able to:
- This tutorial focus on the Numpy Array in Python. It shows the learners what NumPy arrays actually are and how to install Numpy (through wheels and Anaconda), how to make arrays even with data files, how broadcasting works, how to manipulate arrays and how to visualize them.
- It presented in detail the many attributes related to the array including, flags and itemsize, as well as other features of scientific computation.
- The provided contents are complete in terms of the features and appropriate.
In summary, the material is very comprehensive and in detail; It contains most of the essential topics in numpy inculding basic data manipulation to data visualization. It contains program code, which can be run immediately in the Webpage. The content is clear and accurate.
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
- After each learning topic, it provides a console box for testing codes to learn by viewing the expected result immediately even if the viewer can not the Python compile on the spot which is very convenient to learn the package of the programming language.
- Even though it does not have fancy graphics or animations, the text and the layout is easily read and follow.
- It can contain a chatroom for the users to share their questions and problems and the solutions.
- The cheat sheet provided is very useful for quick in actual working or project environment.
In summary, the learning objectives of the material are clear. It is divided into different sections, each of which focues on a particular essential skill in numpy. The program codes are included and learners can run the code on-the-fly, which can help learners to grasp the concepts effectively.
Concerns:
It is a bit odd for the first console box that "my_array" content can be shown without defined previously, even though it is understood that the example aims to present the data in 1dimension, 2d or 3d.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
- All contents are consolidated into one single web page so the viewer does not need to go to and fro for a particular topic. By simply scrolling or page search by the running browser, the required topic or keywords can be found.
- The contents are divided into sections and their headings can be found at the top of the page. It would be more convenient if the navigation to different sections to be available across the page.
In summary, the material is very easy to use. It contains the program codes and illustrations to concey the concept in a very effective manner. The Website is very well organized and easy to follow. The interpreter on the page can run python code on-the-fly and hence learners can try the code easily.
Concerns:
It may contain some exercises for learners to practise.
Creative Commons:
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