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Exploratory Data Analysis with Python Cookbook

You're reading from   Exploratory Data Analysis with Python Cookbook Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781803231105
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Ayodele Oluleye Ayodele Oluleye
Author Profile Icon Ayodele Oluleye
Ayodele Oluleye
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Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Generating Summary Statistics 2. Chapter 2: Preparing Data for EDA FREE CHAPTER 3. Chapter 3: Visualizing Data in Python 4. Chapter 4: Performing Univariate Analysis in Python 5. Chapter 5: Performing Bivariate Analysis in Python 6. Chapter 6: Performing Multivariate Analysis in Python 7. Chapter 7: Analyzing Time Series Data in Python 8. Chapter 8: Analysing Text Data in Python 9. Chapter 9: Dealing with Outliers and Missing Values 10. Chapter 10: Performing Automated Exploratory Data Analysis in Python 11. Index 12. Other Books You May Enjoy

Using line and boxplots to visualize time series data

The line chart connects time series data points through a straight line that displays the peaks (high points) and valleys (low points) in the data. The x axis of the line chart typically represents our time intervals, while the y axis represents a variable of interest that we intend to track in relation to time. With the line chart, it is easy to spot trends or changes over time.

On the other hand, the boxplot gives us a sense of the underlying distribution of a dataset through five key metrics. The metrics include minimum, first quartile, median, third quartile, and maximum. You can check out Chapter 4, Performing Univariate Analysis in Python, for more details about the boxplot and its components. When used on time series data, the x axis typically represents our time intervals, while the y axis represents a variable of interest. The time intervals on the x axis are typically summarized time intervals, for example, hourly summarized...

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