Python Data Science Cookbook by Taryn Voska (.ePUB)+

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File Size: 10 MB

Python Data Science Cookbook: Practical solutions across fast data cleaning, processing, and machine learning workflows with pandas, NumPy, and scikit-learn by Taryn Voska
Requirements: .ePUB, .PDF, .MOBI/.AZW reader, 10 MB
Overview: This book’s got a bunch of handy recipes for data science pros to get them through the most common challenges they face when using Python tools and libraries. Each recipe shows you exactly how to do something step-by-step. You can load CSVs directly from a URL, flatten nested JSON, query SQL and NoSQL databases, import Excel sheets, or stream large files in memory-safe batches. Once the data’s loaded, you’ll find simple ways to spot and fill in missing values, standardize categories that are off, clip outliers, normalize features, get rid of duplicates, and extract the year, month, or weekday from timestamps. You’ll learn how to run quick analyses, like generating descriptive statistics, plotting histograms and correlation heatmaps, building pivot tables, creating scatter-matrix plots, and drawing time-series line charts to spot trends. You’ll learn how to build polynomial features, compare MinMax, Standard, and Robust scaling, smooth data with rolling averages, apply PCA to reduce dimensions, and encode high-cardinality fields with sparse one-hot encoding using feature engineering recipes.
Genre: Non-Fiction > Tech & Devices

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