Data science fundamentals with R, Python, and open data / Marco Cremonini.

Format:

Book

Author/Creator:

Cremonini, Marco, author.

Contributor:

Wiley InterScience (Online service)

Language:

English

Subjects (All):

Data mining.

R (Computer program language).

Python (Computer program language).

Physical Description:

1 online resource (xxii, 455 pages) : illustrations

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, Inc., [2024]

Contents:

Preface xiii

About the Companion Website xvii

Introduction xix

1 Open-Source Tools for Data Science 1

1.1 R Language and RStudio 1

1.2 Python Language and Tools 5

1.3 Advanced Plain Text Editor 8

1.4 CSV Format for Datasets 8

2 Simple Exploratory Data Analysis 13

2.1 Missing Values Analysis 13

2.2 R: Descriptive Statistics and Utility Functions 15

2.3 Python: Descriptive Statistics and Utility Functions 17

3 Data Organization and First Data Frame Operations 23

3.1 R: Read CSV Datasets and Column Selection 24

3.2 R: Rename and Relocate Columns 36

3.3 R: Slicing, Column Creation, and Deletion 38

3.4 R: Separate and Unite Columns 45

3.5 R: Sorting Data Frames 49

3.6 R: Pipe 55

3.7 Python: Column Selection 59

3.8 Python: Rename and Relocate Columns 67

3.9 Python: NumPy Slicing, Selection with Index, Column Creation and Deletion 69

3.10 Python: Separate and Unite Columns 81

3.11 Python: Sorting Data Frame 85

4 Subsetting with Logical Conditions 99

4.1 Logical Operators 99

4.2 R: Row Selection 101

5 Operations on Dates, Strings, and Missing Values 127

5.1 R: Operations on Dates and Strings 129

5.2 R: Handling Missing Values and Data Type Transformations 141

5.3 R: Example with Dates, Strings, and Missing Values 154

5.4 Pyhton: Operations on Dates and Strings 165

5.5 Python: Handling Missing Values and Data Type Transformations 173

5.6 Python: Examples with Dates, Strings, and Missing Values 182

6 Pivoting and Wide-long Transformations 195

6.1 R: Pivoting 197

6.2 Python: Pivoting 202

7 Groups and Operations on Groups 221

7.1 R: Groups 222

7.2 Python: Groups 244

8 Conditions and Iterations 271

8.1 R: Conditions and Iterations 272

8.2 Python: Conditions and Iterations 284

9 Functions and Multicolumn Operations 307

9.1 R: User-defined Functions 308

9.2 R: Multicolumn Operations 316

9.3 Python: User-defined and Lambda Functions 330

10 Join Data Frames 347

10.1 Basic Concepts 348

10.2 Python: Join Operations 369

11 List/Dictionary Data Format 393

11.1 R: List Data Format 395

11.2 R: JSON Data Format and Use Cases 410

11.3 Python: Dictionary Data Format 422

Questions 443

Index 447.

Notes:

Includes index.

Electronic reproduction. Hoboken, N.J. Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on August 01, 2024).

Other Format:

Print version: Cremonini, Marco. Data science fundamentals with R, Python, and open data

ISBN:

1394213263

9781394213252

1394213255

9781394213276

1394213271

9781394213269

Publisher Number:

90101435962

Access Restriction:

Restricted for use by site license.