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Statistical Application Development with R and Python - Second Edition.
Software Implementation Illustrated with R and Python About This Book Learn the nature of data through software which takes the preliminary concepts right away using R and Python. Understand data modeling and visualization to perform efficient statistical analysis with this guide. Get well versed wi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2017.
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| Edición: | 2nd ed. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Author; Acknowledgment; About the Reviewers; www.PacktPub.com; Customer Feedback; Table of Contents; Preface; Chapter 1: Data Characteristics; Questionnaire and its components; Understanding the data characteristics in an R environment; Experiments with uncertainty in computer science; Installing and setting up R; Using R packages; RSADBE
- the books R package; Python installation and setup; Using pip for packages; IDEs for R and Python; The companion code bundle; Discrete distributions; Discrete uniform distribution; Binomial distribution.
- Hypergeometric distributionNegative binomial distribution; Poisson distribution; Continuous distributions; Uniform distribution; Exponential distribution; Normal distribution; Summary; Chapter 2: Import/Export Data; Packages and settings
- R and Python; Understanding data.frame and other formats; Constants, vectors, and matrices; Time for action
- understanding constants, vectors, and basic arithmetic; What just happened?; Doing it in Python; Time for action
- matrix computations; What just happened?; Doing it in Python; The list object; Time for action
- creating a list object.
- What just happened?The data.frame object; Time for action
- creating a data.frame object; What just happened?; Have a go hero; The table object; Time for action
- creating the Titanic dataset as a table object; What just happened?; Have a go hero; Using utils and the foreign packages; Time for action
- importing data from external files; What just happened?; Doing it in Python; Importing data from MySQL; Doing it in Python; Exporting data/graphs; Exporting R objects; Exporting graphs; Time for action
- exporting a graph; What just happened?; Managing R sessions.
- Time for action
- session managementWhat just happened?; Doing it in Python; Pop quiz; Summary; Chapter 3: Data Visualization; Packages and settings
- R and Python; Visualization techniques for categorical data; Bar chart; Going through the built-in examples of R; Time for action
- bar charts in R; What just happened?; Doing it in Python; Have a go hero; Dot chart; Time for action
- dot charts in R; What just happened?; Doing it in Python; Spine and mosaic plots; Time for action
- spine plot for the shift and operator data; What just happened?
- Time for action
- mosaic plot for the Titanic datasetWhat just happened?; Pie chart and the fourfold plot; Visualization techniques for continuous variable data; Boxplot; Time for action
- using the boxplot; What just happened?; Doing it in Python; Histogram; Time for action
- understanding the effectiveness of histograms; What just happened?; Doing it in Python; Have a go hero; Scatter plot; Time for action
- plot and pairs R functions; What just happened?; Doing it in Python; Have a go hero; Pareto chart; A brief peek at ggplot2; Time for action
- qplot; What just happened?
- Time for action
- ggplot.