Pandas Cookbook Petrou Theodore by Petrou, Theodore instant download after payment.

Key Features Learn to use the power of Pandas to solve most complex scientific
computing problems Leverage fast, robust data structures in Pandas to gain
most from your data Perform various data analysis tasks efficiently with ease
Book Description

Pandas is one of the most efficient scientific computing packages in Python.
It has an enormous amount of power and flexibility to tackle any data task in
a variety of ways. It is common for advanced users to write “ugly” Pandas
code. With this book, you will explore data in Pandas through dozens of
practice problems with detailed solutions in iPython notebooks

This book will provide you with clean, clear recipes and solutions on how to
handle common data manipulation tasks. You will be introduced to Pandas and
its various features. You will learn about working with different types of
data sets, data manipulation, and data wrangling. You will explore the power
of Pandas DataFrames and find out about Boolean and multi-indexing with
Pandas. You will perform statistical, time series computations, and implement
them in financial and scientific applications.

By the end of this book, you will know how to perform fast and accurate
scientific computing in Python.

What you will learn Group, aggregate, transform, reshape and filter data to
discover meaningful insights Combine and merge data from different sources
through Pandas SQL-like operations Create beautiful and insightful
visualizations through Pandas direct hooks to Matplotlib and Seaborn Perform
efficient and powerful analyses with Pandas time series functionality Build
pipelines to import, clean and prepare real-world messy data sets for machine
learning Create big data workflows for processing data that is too large to
fit in the memory About the Author

**Ted Petrou** is a data scientist at Schlumberger where he spends the vast
majority of his time exploring data. Some of his projects include using
targeted sentiment analysis to discover the root cause of part failure from
engineer text, developing customized client/server dashboarding applications
and real-time web services to avoid mispricing of sales items. Ted received
his Masters degree in statistics from Rice University and used his analytical
skills to play poker professionally and teach math before becoming a data
scientist. He is also head of Houston Data Science and a top Pandas answerer
on stackoverflow.