Python數據分析工具包：Pandas

Python Data Analysis Library 或 pandas 是連接 SciPy 和 NumPy 的一種工具，該工具是為了解決數據分析任務而創建的。Pandas 納入了大量庫和一些標準的數據模型，提供了高效地操作大型數據集所需的工具。Comma-separated values (CSV) 文件表示在有關各方之間分發數據的最常見的方法之一。Pandas 提供了一種優化庫功能來讀寫多種文件格式，包括 CSV 和高效的 HDF5 格式。

• A fast and efficient DataFrame object for data manipulation with integrated indexing;
• Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format;
• Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form;
• Flexible reshaping and pivoting of data sets;
• Intelligent label-based slicing, fancy indexing, and subsetting of large data sets;
• Columns can be inserted and deleted from data structures for size mutability;
• Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets;
• High performance merging and joining of data sets;
• Hierarchical axis indexing provides an intuitive way of working with high-dimensional data in a lower-dimensional data structure;
• Time series-functionality: date range generation and frequency conversion, moving window statistics, moving window linear regressions, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data;
• The library has been ruthlessly optimized for performance, with critical code paths compiled to C;
• Python with pandas is in use in a wide variety of academic and commercial domains, including Finance, Neuroscience, Economics, Statistics, Advertising, Web Analytics, and more.
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