A Tour of Data Science

Learn R and Python in Parallel

Nailong Zhang

• Publisher: Chapman and Hall/CRC
• Year: 2020
• eBook ISBN: 9781000215274
• Topic: Computer Science
• Subtopic: Statistics for Business & Economics
• Index: Computer Science

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source.

Key features:

• Allows you to learn R and Python in parallel
• Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools – data.table and pandas
• Provides a concise and accessible presentation
• Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc.

Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.

CHAPTER 1

Introduction to R/Python Programming

In this chapter, I will give an introduction to general R and Python programming in a parallel fashion.

1.1 CALCULATOR

R and Python are general-purpose programming languages that can be used for writing softwares in a variety of domains. But for now, let us start with using them as basic calculators. The first thing is to have them installed. R¹ and Python² can be downloaded from their official website. In this book, I will be using R 3.5 and Python 3.7.

To use R/Python as basic calculators, let’s get familiar with the interactive mode. After the installation, we can type R or Python (it is case insensitive so we can also type r/python) to invoke the interactive mode. Since Python 2 is installed by default on many machines, in order to avoid invoking Python 2 we type python3.7 instead.

R

 1 2 ∼ $R 1 4 R version 3.5.1 (2018–07–02) — “Feather Sp\footnoteray” 5 Copyright (C) 2018 The R Foundation for Statistical Computing 6 Platform: x86_64—apple—darwin15.6.0 (64—bit) 7 8 R is free software and comes with ABSOLUTELY NO WARRANTY. 9 You are welcome to redistribute it under certain conditions. 10 Type ’license()’ or ’licence()’ for distribution details. 11 

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¹ https://www.r-project.org

² https://www.python.org

 12 Natural language support but running in an English locale 13 14 R is a collaborative project with many contributors. 15 Type ’contributors()’ for more information and 16 ’citation()’ on how to cite R or R packages in publications. 17 18 Type ’demo()’ for some demos, ’help()’ for on—line help, or 19 ’help. start()’ for an HTML browser interface to help. 20 Type ’q ()’ to quit R. 21 22 > 

Python

 1 ∼ $python 3.7 2 Python 3.7.1 (default, Nov 6 2018, 18:45:35) 3 [Clang 10.0.0 (clang–1000.11.45.5)] on darwin 4 Type “help”, “copyright”, “credits” or “license” for more information. 5 >>> 

The messages displayed by invoking the interactive mode depend on both the version of R/Python installed and the machine. Thus, you may see different messages on your local machine. As the messages said, to quit R we can type q(). There are 3 options prompted by asking the user if the workspace should be saved or not. Since we just want to use R as a basic calculator, we quit without saving workspace.

To quit Python, we can simply type exit().

R

 1 > q() 2 Save workspace image? [y/n/c]: n 3 ∼ $ 

Once we are inside the interactive mode, we can use R/Python as a calculator.

R

 1 > 1+1 2 [1] 2 3 > 2 * 3 + 5 4 [1] 11 5 > log (2) 6 [1] 0.6931472 7 > exp (0) 8 [1] 1 

Python

 1 >>> 1+1 2 2 3 >>> 2*3+5 4 11 5 >>> log (2) 6 Traceback (most recent call last): 7 File “<stdin>”, line 1, in <module> 8 NameError: name ’log’ is not defined 9 >>> exp (0) 10 Traceback (most recent call last): 11 File “<stdin>”, line 1, in <module= 12 NameError: name ’exp’ is not defined 

From the code snippet above, R is working as a calculator perfectly. However, errors are raised when we call log(2) and exp(2) in Python. The error messages are self-explanatory - log function and exp function don’t exist in the current Pyth...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• Chapter 1 ■ Introduction to R/Python Programming
• Chapter 2 ■ More on R/Python Programming
• Chapter 3 ■ data.table and pandas
• Chapter 4 ■ Random Variables, Distributions & Linear Regression
• Chapter 5 ■ Optimization in Practice
• Chapter 6 ■ Machine Learning - A gentle introduction
• Bibliography
• Index