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Learning pandas

Learning pandas - Second Edition

By : Michael Heydt, Nicola Rainiero, Sonali Dayal
3.5 (2)
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Learning pandas

Learning pandas

3.5 (2)
By: Michael Heydt, Nicola Rainiero, Sonali Dayal

Overview of this book

You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
Table of Contents (16 chapters)
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Visualization

One of the most important parts of data analysis is in creating a great visualization to immediately convey the underlying meaning in the data. Data visualization is effective, as we humans are visual creatures and have evolved to be able to discern meaning when information is laid out in a way that our brain can interpret almost immediately when the impulses from the retina hit the brain.

Over the years, there has been significant research that has resulted in many effective visualization techniques to convey specific patterns in data. These patterns have been implemented in visualization libraries, and pandas is designed to utilize these and make their use very simple.

This chapter will cover several of these techniques, primarily focusing on matplotlib, and many of the common visualizations. We will do this in three steps. The first introduces the general concepts...

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Learning pandas
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