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Pandas

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  Pandas is a software library written for the Python Programming Language for Data Manipulation and Analysis. In particular, it offers Data Structures and Operations for Manipulating Numerical Tables and Time Series. It is free software released under the Three-Clause BSD License  What Is Pandas? Pandas is a library for Data Analysis. Extremely powerful table (DataFrame)  system built off of NumPy. What Can We Do With Pandas? Tools For Reading And Writing Data Between Manay Formats. Intelligently Grab Data Based On Indexing, Logic, Subsetting and More. Handle Missing Data. Adjust and Restructure Data. Section Goals: Series and DataFrames Conditional Filtering and Useful Methods Missing Data Group By Operations Combinig DataFrames Text Methos and Time Methods Input and Outputs Series: A Series is a Data Structure in Pandas that holds an Array of Information along With a Named Index. The Named Index Differentiates this from a Simple NumPy Array. Formal Definition: One-Dime...
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Numpy

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NumPy is a one of  the Data Science library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The ancestor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers Section Goals:     Understand NumPy     Create Arrays With NumPy     Retrieve Information From A NumPy Array Through Slicing And Indexing     Learn Basic NumPy Operations What Is NumPy?     Python Library For Creating N-Dimensional Arrays     Ability To Quickly Broadcast functions     Built-in Linear Algebra, Statistical Distributions, Trigonometric And Random Number Capabilities Why Use NumPy?     While NumPy Structures Look Similar To Standerf Python Lists, They Are Much More Efficient!!!     T...
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