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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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| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Hands-On Data Analysis with NumPy and Pandas : Implement Python Packages from Data Manipulation to Processing/ by Curtis Miller. [electronic resource]. |
| 개인저자 | Miller, Curtis. |
| 발행사항 | Birmingham: Packt Publishing Ltd, 2018. |
| 형태사항 | 1 online resource (166 pages). |
| 기타형태 저록 | Print 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 |
| ISBN | 9781789534245 1789534240 |
| 내용주기 | Cover; 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. |
| 요약 | Chapter 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. |
| 요약 | In 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. |
| 일반주제명 | Python (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) |
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