Synopsis
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...
About the Author
Daniel Chen is a graduate student in the interdisciplinary PhD program in Genetics, Bioinformatics & Computational Biology (GBCB) at Virginia Tech. He is involved with Software Carpentry as an instructor and lesson maintainer. He completed his master’s degree in public health at Columbia University Mailman School of Public Health in Epidemiology, and currently works at the Social and Decision Analytics Laboratory under the Biocomplexity Institute of Virginia Tech...
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Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series)
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Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series)
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Pandas for Everyone: Python Data Analysis (Paperback)
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Paperback. Condition: new. Paperback. Today, analysts must manage data characterised 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, visualise 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 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 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 visualisation. 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 theyre 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 generalised linear modeling to fit models with different response variables Compare multiple models to select the best Regularise to overcome overfitting and improve performance Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780134546933
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