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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

By : Ivan Idris
2 (1)
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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

2 (1)
By: Ivan Idris

Overview of this book

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents (16 chapters)
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14
C. NumPy Functions' References
15
Index

Time for action – enveloping with Bollinger Bands


We already know how to calculate the SMA. So, if you need to refresh your memory, please review the Time for action – computing the simple average section in this chapter. This example will introduce the NumPy fill() function. The fill() function sets the value of an array to a scalar value. The function should be faster than array.flat = scalar or setting the values of the array one-by-one in a loop. Perform the following steps to envelope with the Bollinger Bands:

  1. Starting with an array called sma that contains the moving average values, we will loop through all the datasets corresponding to those values. After forming the dataset, calculate the standard deviation. Note that at a certain point, it will be necessary to calculate the difference between each data point and the corresponding average value. If we do not have NumPy, we will loop through these points and subtract each of the values one-by-one from the corresponding average. However...

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