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Hands-On Data Analysis with NumPy and Pandas [electronic resource] Implement Python Packages from Data Manipulation to Processing

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서명/저자사항Hands-On Data Analysis with NumPy and Pandas : Implement Python Packages from Data Manipulation to Processing/ by Curtis Miller. [electronic resource].
개인저자Miller, Curtis.
발행사항Birmingham: Packt Publishing Ltd, 2018.
형태사항1 online resource (166 pages).
기타형태 저록Print version: Miller, Curtis. Hands-On Data Analysis with NumPy and Pandas : Implement Python Packages from Data Manipulation to Processing. Birmingham : Packt Publishing Ltd, ©2018 9781789530797
ISBN9781789534245
1789534240


내용주기Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Setting Up a Python Data Analysis Environment; What is Anaconda?; Installing Anaconda; Exploring Jupyter Notebooks; Exploring alternatives to Jupyter; Spyder; Rodeo; ptpython; Package management with Conda; What is Conda?; Conda environment management; Managing Python; Package management; Setting up a database; Installing MySQL; MySQL connectors; Creating a database; Summary; Chapter 2: Diving into NumPY; NumPy arrays; Special numeric values; Creating NumPy arrays; Creating ndarray.
Slicing a DataFrameSummary; Chapter 5: Arithmetic, Function Application, and Mapping with pandas; Arithmetic; Arithmetic with DataFrames; Vectorization with DataFrames; DataFrame function application; Handling missing data in a pandas DataFrame; Deleting missing information; Filling missing information; Summary; Chapter 6: Managing, Indexing, and Plotting; Index sorting; Sorting by values; Hierarchical indexing; Slicing a series with a hierarchical index; Plotting with pandas; Plotting methods; Summary; Other Books You May Enjoy; Index.
요약Chapter 3: Operations on NumPy Arrays; Selecting elements explicitly; Slicing arrays with colons; Advanced indexing; Expanding arrays; Arithmetic and linear algebra with arrays; Arithmetic with two equal-shaped arrays; Broadcasting; Linear algebra; Employing array methods and functions; Array methods; Vectorization with ufuncs; Custom ufuncs; Summary; Chapter 4: pandas are Fun! What is pandas?; What does pandas do?; Exploring series and DataFrame objects; Creating series; Creating DataFrames; Adding data; Saving DataFrames; Subsetting your data; Subsetting a series; Indexing methods.
요약In this book, you will explore two important Python packages used by Data Analysts, NumPy & pandas. You will dive into different concepts such as reading, sorting, grouping of data, and also learn how to work with different data formats for your data analysis projects.
일반주제명Python (Computer program language)
Numerical analysis --Data processing.
Information visualization.
Data capture & analysis.
Database design & theory.
Information architecture.
Information visualization.
Computers --Data Modeling & Design.
Computers --Data Processing.
Information visualization.
Numerical analysis --Data processing.
Python (Computer program language)
언어영어
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