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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

Describing pandas DataFrames

The pandas DataFrame has a dozen statistical methods. The following table lists these methods, along with a short description of each:

Method

Description

describes

This method returns a small table with descriptive statistics.

count

This method returns the number of non-NaN items.

mad

This method calculates the mean absolute deviation, which is a robust measure similar to standard deviation.

median

This method returns the median. This is equivalent to the value at the 50th percentile.

min

This method returns the minimum value.

max

This method returns the maximum value.

mode

This method returns the mode, which is the most frequently occurring value.

std

This method returns the standard deviation, which measures dispersion. It is the square root of the variance.

var

This method returns the variance.

skew

This method returns skewness. Skewness is indicative of the distribution symmetry.

kurt...

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