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Data Wrangling with Python

You're reading from Data Wrangling with Python Creating actionable data from raw sources

Product type Paperback

Published in Feb 2019

Publisher Packt

ISBN-13 9781789800111

Length 452 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (2):

Shubhadeep Roychowdhury

Dr. Tirthajyoti Sarkar

View More author details

Table of Contents (12) Chapters

Data Wrangling with Python

Preface

1. Introduction to Data Wrangling with Python

2. Advanced Data Structures and File Handling FREE CHAPTER

3. Introduction to NumPy, Pandas, and Matplotlib

4. A Deep Dive into Data Wrangling with Python

5. Getting Comfortable with Different Kinds of Data Sources

6. Learning the Hidden Secrets of Data Wrangling

7. Advanced Web Scraping and Data Gathering

8. RDBMS and SQL

9. Application of Data Wrangling in Real Life

Appendix

Pandas DataFrames

The pandas library is a Python package that provides fast, flexible, and expressive data structures that are designed to make working with relational or labeled data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis/manipulation tool that's available in any language.

The two primary data structures of pandas, Series (one-dimensional) and DataFrame (two-dimensional), handle the vast majority of typical use cases. Pandas is built on top of NumPy and is intended to integrate well within a scientific computing environment with many other third-party libraries.

Exercise 37: Creating a Pandas Series

In this exercise, we will learn about how to create a pandas series object from the data structures that we created previously. If you have imported pandas as pd, then the function to create...

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Authors (2)

Dr. Tirthajyoti Sarkar

Dr. Tirthajyoti Sarkar

Dr. Tirthajyoti Sarkar works as a senior principal engineer in the semiconductor technology domain, where he applies cutting-edge data science/machine learning techniques for design automation and predictive analytics. He writes regularly about Python programming and data science topics. He holds a Ph.D. from the University of Illinois and certifications in artificial intelligence and machine learning from Stanford and MIT.

See other products by Dr. Tirthajyoti Sarkar

Shubhadeep Roychowdhury

Shubhadeep Roychowdhury

Shubhadeep Roychowdhury holds a master's degree in computer science from West Bengal University of Technology and certifications in machine learning from Stanford. He works as a senior software engineer at a Paris-based cybersecurity startup, where he is applying state-of-the-art computer vision and data engineering algorithms and tools to develop cutting-edge products. He often writes about algorithm implementation in Python and similar topics.

See other products by Shubhadeep Roychowdhury

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