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Python Data Analysis

You're reading from   Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries FREE CHAPTER 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Measuring dispersion

As we have seen, central tendency presents the middle value of a group of observations but does not provide the overall picture of an observation. Dispersion metrics measure the deviation in observations. The most popular dispersion metrics are range, interquartile range (IQR), variance, and standard deviation. These dispersion metrics value the variability in observations or the spread of observations. Let's see each dispersion measure in detail, as follows:

  • Range: The range is the difference between the maximum and minimum value of an observation. It is easy to compute and easy to understand. Its unit is the same as the unit of observations. Let's compute the range of communication skill scores, as follows:
column_range=data['communcation_skill_score'].max()-data['communcation_skill_score'].min()
print(column_range)

Output:
22

In the preceding code block, we have computed the range of communication skill scores by finding the difference...

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