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Statistical Application Development with R and Python

You're reading from   Statistical Application Development with R and Python Develop applications using data processing, statistical models, and CART

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Product type Paperback
Published in Aug 2017
Publisher
ISBN-13 9781788621199
Length 432 pages
Edition 2nd Edition
Languages
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Author (1):
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Prabhanjan Narayanachar Tattar Prabhanjan Narayanachar Tattar
Author Profile Icon Prabhanjan Narayanachar Tattar
Prabhanjan Narayanachar Tattar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Data Characteristics FREE CHAPTER 2. Import/Export Data 3. Data Visualization 4. Exploratory Analysis 5. Statistical Inference 6. Linear Regression Analysis 7. Logistic Regression Model 8. Regression Models with Regularization 9. Classification and Regression Trees 10. CART and Beyond Index

Understanding data.frame and other formats

Any software comes with its structure and nuances. The Questionnaire and its component section of Chapter 1, Data Characteristics, introduced various facets of data. In the current section, we will go into the details of how R works with data of different characteristics. Depending on the need, we have different formats of the data. In this section, we will begin with simpler objects and move up the ladder toward some of the more complex ones.

Constants, vectors, and matrices

R has five inbuilt objects that store certain constant values. The five objects are LETTERS, letters, month.abb, month.name, and pi. The first two objects contain the letters A-Z in upper and lower cases. The third and fourth objects have months in their abbreviated form and the complete month names. Finally, the object pi contains the value of the famous irrational number. So here, the exercise for the reader is to find the value of the irrational number e. The details about...

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