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Python for Data Analysis

📊 Python for Data Analysis: NumPy, pandas, and IPython: The provided text consists of excerpts from a book titled "Python for Data Analysis" by Wes McKinney, a practical guide focused on manipulating and analyzing data using Python. The source introduces essential data science libraries like NumPy for vectorized array operations and the foundational array object, the ndarray, and pandas, highlighting its Series and DataFrame structures for high-level data handling. Additionally, the excerpts cover various data wrangling techniques, including data loading from different file formats (CSV, JSON, HTML, databases), data transformation, string manipulation using Python and regular expressions, and applying group operations for aggregation and analysis. The material also touches upon interactive computing with IPython, code profiling, and plotting/visualization using matplotlib and Basemap for geographical data, as well as an appendix with Python language essentials.