Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications
Review questions and exercises; Chapter 3: Data Basics; Sources of data; UCI machine learning; Introduction to the Python pandas package; Several ways to input data; Inputting data using R; Inputting data using Python; Introduction to the Quandl data delivery platform; Dealing with missing data; Dat...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing
2018.
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| Colección: | EBSCO Academic eBook Collection Complete.
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| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b45003397*spi |
| Sumario: | Review questions and exercises; Chapter 3: Data Basics; Sources of data; UCI machine learning; Introduction to the Python pandas package; Several ways to input data; Inputting data using R; Inputting data using Python; Introduction to the Quandl data delivery platform; Dealing with missing data; Data sorting; Slicing and dicing datasets; Merging different datasets; Data output; Introduction to the cbsodata Python package; Introduction to the datadotworld Python package; Introduction to the haven and foreign R packages; Introduction to the dslabs R package; Generating Python datasets. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. You will learn different ways to retrieve data from various sources and different visualization tools packages available in Python, R, and Julia. |
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| Notas: | General issues for optimization problems. |
| Descripción Física: | 1 recurso electrónico |
| Formato: | Forma de acceso: World Wide Web. |
| ISBN: | 9781788834735 |
