Hands-On Data Analysis with Pandas - Second Edition

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Get to grips with pandas, a high-performance Python library for data discovery, manipulation, and preparation for analytical tasks. This resource enables efficient data analysis and manipulation, applying pandas to various real-world scenarios through step-by-step examples. Data analysis is crucial across numerous fields, where the ability to work with data and extract insights adds significant value. This guide teaches you to analyze data, initiate machine learning, and effectively use Python libraries relevant to data science, including pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn data wrangling techniques to reshape, clean, and aggregate data. The exploration of data analysis includes calculating summary statistics and visualizing data to identify patterns. The final chapters cover applications of anomaly detection, regression, clustering, and classification using scikit-learn for predictive modeling based on historical data. This updated edition provides essential skills for using pandas 1.x to perform diverse data manipulation tasks, reproduce analyses, and visualize data for informed decision-making—knowledge applicable across multiple domains. Ideal for data science beginners, analysts, and Python developers, this book guides you through each stage of data analysis and scientific computing. It is also beneficial for data scientists looking to integrate pandas into the