Pandas for Everyone

Python Data Analysis

Nonfiction, Computers, Database Management, Programming, Programming Languages
Cover of the book Pandas for Everyone by Daniel Y. Chen, Pearson Education
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Daniel Y. Chen ISBN: 9780134547053
Publisher: Pearson Education Publication: December 15, 2017
Imprint: Addison-Wesley Professional Language: English
Author: Daniel Y. Chen
ISBN: 9780134547053
Publisher: Pearson Education
Publication: December 15, 2017
Imprint: Addison-Wesley Professional
Language: English

The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python

Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.

Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems.

Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes.

Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem.

  • Work with DataFrames and Series, and import or export data
  • Create plots with matplotlib, seaborn, and pandas
  • Combine datasets and handle missing data
  • Reshape, tidy, and clean datasets so they’re easier to work with
  • Convert data types and manipulate text strings
  • Apply functions to scale data manipulations
  • Aggregate, transform, and filter large datasets with groupby
  • Leverage Pandas’ advanced date and time capabilities
  • Fit linear models using statsmodels and scikit-learn libraries
  • Use generalized linear modeling to fit models with different response variables
  • Compare multiple models to select the “best”
  • Regularize to overcome overfitting and improve performance
  • Use clustering in unsupervised machine learning
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python

Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.

Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems.

Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes.

Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem.

More books from Pearson Education

Cover of the book Cisco Unified Presence Fundamentals by Daniel Y. Chen
Cover of the book Effortless E-Commerce with PHP and MySQL by Daniel Y. Chen
Cover of the book iPhone and iPad Apps Marketing by Daniel Y. Chen
Cover of the book New Business Networking by Daniel Y. Chen
Cover of the book Psychology Express: Occupational Psychology (Undergraduate Revision Guide) by Daniel Y. Chen
Cover of the book CCNA Portable Command Guide by Daniel Y. Chen
Cover of the book Choose Your Own Outcome! (Collection) by Daniel Y. Chen
Cover of the book Mission, Vision, and Effective Nonprofit Leadership by Daniel Y. Chen
Cover of the book The Flip Mino Pocket Guide by Daniel Y. Chen
Cover of the book Object Thinking by Daniel Y. Chen
Cover of the book Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself by Daniel Y. Chen
Cover of the book Establishing Your Major Social Media Objectives and Key Strategies by Daniel Y. Chen
Cover of the book How to Measure Social Media by Daniel Y. Chen
Cover of the book Apple Training Series by Daniel Y. Chen
Cover of the book Windows PowerShell 3.0 First Steps by Daniel Y. Chen
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy