Language:
English
Pages:
1 online resource (512 pages)
,
illustrations
Edition:
Second edition.
Series Statement:
Addison-Wesley data & analytics series
Parallel Title:
Erscheint auch als Druck-Ausgabe Chen, Daniel Y. Pandas for Everyone
DDC:
006.3/12
Keywords:
Python (Computer program language)
;
Electronic spreadsheets
;
Electronic data processing
;
Electronic data processing
;
Electronic spreadsheets
;
Python (Computer program language)
Abstract:
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 data sets. Pandas for Everyone, 2nd Edition, brings together practical knowledge and insight for solving real problems with Pandas, even if youre 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 data science problems such as using regularization to prevent data overfitting, or when to use unsupervised machine learning methods to find the underlying structure in a data set. Chen gives you a jumpstart on using Pandas with a realistic data set and covers combining data sets, handling missing data, and structuring data sets 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.
Note:
Includes index
