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Use pandas for efficient data manipulation from "summary" of Python for Data Analysis by Wes McKinney
Pandas is a powerful library in Python for data manipulation and analysis. It provides data structures and functions that are designed to make working with structured data fast, easy, and expressive. Pandas is built on top of NumPy, a fundamental package for scientific computing with Python. It makes use of NumPy arrays for its underlying data structure, which allows for high performance computing with data in memory. One of the key features of pandas is its DataFrame object, which is essentially a two-dimensional table of data with rows and columns. DataFrames can store a variety of data types and can be manipulated in numerous ways. You can think of a DataFrame as a spreadsheet or SQL table, with rows representing individual entries or observations, and columns representing different variables or features. Pandas provides a wide range of functions and methods for manip...
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