Data Processing

Explore how to process data using NumPy arrays by calculating mean, standard deviation, variance, minimum, and maximum values. Understand how to manipulate complex arrays and apply useful array functions to analyze and extract meaningful insights from scientific datasets.

We'll cover the following...

- Mean and standard deviation
- min and max
- Complex arrays
- Some useful functions

NumPy arrays provide diverse functionalities and tools to manipulate extract meaning from raw data.

Mean and standard deviation

Suppose you are measuring the peak value of current passing through a transformer every two hours, but due to temperature changes, there is a fluctuation in the peak value. In order to get a good representation of the data, we will need to calculate the mean value of all 12 readings. The mathematical formula for the mean is given below:

$\overline{a}=\frac{1}{n}\sum_{i=1}^n{a_i}$ ...

1.Introduction

2.Python Refresher

3.Arrays

4.Plotting

5.Systems of Linear Equations

6.Symbolic Computation

7.Scientific Algorithms

8.Random Variables

9.Applications

10.Conclusion

11.Appendix

Assessment

Data Processing

Mean and standard deviation