Foundational Python for data science:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston ; Columbus ; New York
Addison-Wesley
[2022]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xii, 231 Seiten Illustrationen, Diagramme |
| ISBN: | 9780136624356 0136624359 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents at a Glance xiii Preface I: Learning Python In a Notebook Environment 1 Introduction to Notebooks 2 Fundamentals of Python 4 Other Data Structures 5 Execution Control 8 SciPy 9 Pandas 37 55 67 II: Data Science Libraries 7 NumPy 13 25 3 Sequences 6 Functions 3 83 85 103 113 10 Visualization Libraries 135 11 Machine Learning Libraries 12 Natural Language Toolkit III: Intermediate Python 159 171 13 Functional Programming 173 14 Object-Oriented Programming 15 Other Topics 153 187 201 A Answers to End-of-Chapter Questions Index 221 215 1
Table of Contents Preface xiii I: Learning Python in a Notebook Environment 1 Introduction to Notebooks 3 Running Python Statements 4 Jupyter Notebooks 4 5 Google Colab Colab Text Cells 6 Colab Code Cells Colab Files 9 9 Managing Colab Documents Colab Code Snippets 2 11 11 Magic Functions Questions 10 11 Existing Collections System Aliases Summary 12 12 12 Fundamentals of Python Basic Types in Python 13 14 High-Level Versus Low-Level Languages Statements 15 15 Performing Basic Math Operations 21 Using Classes and Objects with Dot Notation Summary Questions 3 Sequences 22 23 25 25 Shared Operations Testing Membership Indexing Slicing 1 26 27 Interrogation 27 Math Operations Lists and Tuples 29 28 26 22
vlil Contents Creating Lists and Tuples 29 Adding and Removing List Items Sorting Lists 4 Strings 32 Ranges 34 30 31 Unpacking Summary 35 Questions 35 32 Other Data Structures 37 37 Dictionaries 38 Creating Dictionaries Accessing, Adding, and Updating by Using Keys Removing Items from Dictionaries Dictionary Views 39 40 Checking to See If a Dictionary Has a Key 43 The get Method Valid Key Types 44 The hash Method Sets Set Operations Frozensets Summary Questions 5 45 46 48 53 53 53 Execution Control 55 Compound Statements 55 Compound Statement Structure Evaluating to True or False if Statements while Loops for Loops 56 56 59 62 63 break and continue Statements 6 Summary 65 Questions 65 Functions 67 Defining Functions 67 Control Statement 68 64 43 38
Contents Docstrings 68 69 Parameters Return Statements Scope in Functions Decorators 75 76 Anonymous Functions Summary 75 80 81 Questions 81 II: Data Science Libraries 7 NumPy 83 85 Installing and Importing NumPy Creating Arrays 86 Indexing and Slicing 89 Element-by-Element Operations Filtering Values 94 Some Array Methods 95 Broadcasting 98 NumPy Math 100 102 102 Questions 8 ScIPy 91 92 Views Versus Copies Summary 86 103 SciPy Overview 103 The scipy.mise Submodule 104 The scipy. special Submodule The scipy. stats Submodule Discrete Distributions 108 111 Questions Pandas 105 105 Continuous Distributions Summary 9 105 111 113 About DataFrames 113 Creating DataFrames 114 Creating a DataFrame from a Dictionary 114 ix
x Contents Creating a DataFrame from a List of Lists Creating a DataFrame from a File Interacting with DataFrame Data Heads and Tails Descriptive Statistics 118 120 Bracket Syntax 121 Optimized Access by Label 123 Optimized Access by Index 124 Masking and Filtering 125 Pandas Boolean Operators 129 131 The replace Method 133 Interactive Display Summary 126 127 Manipulating DataFrames 133 133 Questions 10 Visualization Libraries matplotlib 135 135 Styling Plots 137 Labeled Data 140 Plotting Multiple Sets of Data Object-Oriented Style Seaborn Plotły Bokeh 141 143 144 Seaborn Themes 145 148 149 Other Visualization Libraries Summary Questions 11 117 117 Accessing Data Manipulating Data 116 151 151 151 Machine Learning Libraries 153 Popular Machine Learning Libraries How Machine Learning Works Transformations 153 154 154 Splitting Test and Training Data Training and Testing 156 155 115
Contents Learning More About Scikit-learn 12 Summary 157 Questions 157 Natural Language Toolkit NLTK Sample Texts 161 165 Classifying Text Summary 169 Exercises 169 166 171 III: Intermediate Python 13 159 159 Frequency Distributions Text Objects 157 Functional Programming 173 173 Introduction to Functional Programming Scope and State 174 174 Depending on Global State Changing State 175 Changing Mutable Data 176 Functional Programming Functions List Comprehensions List Comprehension Basic Syntax Replacing map and filter Multiple Variables 181 182 182 Generator Expressions Generator Functions 14 179 180 181 Dictionary Comprehensions Generators 177 179 Summary 184 Questions 185 183 Object-Oriented Programming Grouping State and Function Classes and Instances 187 187 188 Private Methods and Variables Class Variables Special Methods 190 191 Representation Methods 192 190 xi
xli Contents Rich Comparison Methods Math Operator Methods 196 Inheritance Summary 199 Questions 15 192 195 199 Other Topics 201 201 Sorting Lists 201 Reading and Writing Files Context Managers datetime Objects 206 207 Regular Expressions Character Sets 204 205 208 Character Classes 209 209 Groups Named Groups 210 210 Find All Find Iterator 211 Substitution 211 Substitution Using Named Groups Compiling Regular Expressions A Summary 212 Questions 212 211 Answers to End-of-Chapter Questions Index 221 211 215
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| adam_txt |
Contents at a Glance xiii Preface I: Learning Python In a Notebook Environment 1 Introduction to Notebooks 2 Fundamentals of Python 4 Other Data Structures 5 Execution Control 8 SciPy 9 Pandas 37 55 67 II: Data Science Libraries 7 NumPy 13 25 3 Sequences 6 Functions 3 83 85 103 113 10 Visualization Libraries 135 11 Machine Learning Libraries 12 Natural Language Toolkit III: Intermediate Python 159 171 13 Functional Programming 173 14 Object-Oriented Programming 15 Other Topics 153 187 201 A Answers to End-of-Chapter Questions Index 221 215 1
Table of Contents Preface xiii I: Learning Python in a Notebook Environment 1 Introduction to Notebooks 3 Running Python Statements 4 Jupyter Notebooks 4 5 Google Colab Colab Text Cells 6 Colab Code Cells Colab Files 9 9 Managing Colab Documents Colab Code Snippets 2 11 11 Magic Functions Questions 10 11 Existing Collections System Aliases Summary 12 12 12 Fundamentals of Python Basic Types in Python 13 14 High-Level Versus Low-Level Languages Statements 15 15 Performing Basic Math Operations 21 Using Classes and Objects with Dot Notation Summary Questions 3 Sequences 22 23 25 25 Shared Operations Testing Membership Indexing Slicing 1 26 27 Interrogation 27 Math Operations Lists and Tuples 29 28 26 22
vlil Contents Creating Lists and Tuples 29 Adding and Removing List Items Sorting Lists 4 Strings 32 Ranges 34 30 31 Unpacking Summary 35 Questions 35 32 Other Data Structures 37 37 Dictionaries 38 Creating Dictionaries Accessing, Adding, and Updating by Using Keys Removing Items from Dictionaries Dictionary Views 39 40 Checking to See If a Dictionary Has a Key 43 The get Method Valid Key Types 44 The hash Method Sets Set Operations Frozensets Summary Questions 5 45 46 48 53 53 53 Execution Control 55 Compound Statements 55 Compound Statement Structure Evaluating to True or False if Statements while Loops for Loops 56 56 59 62 63 break and continue Statements 6 Summary 65 Questions 65 Functions 67 Defining Functions 67 Control Statement 68 64 43 38
Contents Docstrings 68 69 Parameters Return Statements Scope in Functions Decorators 75 76 Anonymous Functions Summary 75 80 81 Questions 81 II: Data Science Libraries 7 NumPy 83 85 Installing and Importing NumPy Creating Arrays 86 Indexing and Slicing 89 Element-by-Element Operations Filtering Values 94 Some Array Methods 95 Broadcasting 98 NumPy Math 100 102 102 Questions 8 ScIPy 91 92 Views Versus Copies Summary 86 103 SciPy Overview 103 The scipy.mise Submodule 104 The scipy. special Submodule The scipy. stats Submodule Discrete Distributions 108 111 Questions Pandas 105 105 Continuous Distributions Summary 9 105 111 113 About DataFrames 113 Creating DataFrames 114 Creating a DataFrame from a Dictionary 114 ix
x Contents Creating a DataFrame from a List of Lists Creating a DataFrame from a File Interacting with DataFrame Data Heads and Tails Descriptive Statistics 118 120 Bracket Syntax 121 Optimized Access by Label 123 Optimized Access by Index 124 Masking and Filtering 125 Pandas Boolean Operators 129 131 The replace Method 133 Interactive Display Summary 126 127 Manipulating DataFrames 133 133 Questions 10 Visualization Libraries matplotlib 135 135 Styling Plots 137 Labeled Data 140 Plotting Multiple Sets of Data Object-Oriented Style Seaborn Plotły Bokeh 141 143 144 Seaborn Themes 145 148 149 Other Visualization Libraries Summary Questions 11 117 117 Accessing Data Manipulating Data 116 151 151 151 Machine Learning Libraries 153 Popular Machine Learning Libraries How Machine Learning Works Transformations 153 154 154 Splitting Test and Training Data Training and Testing 156 155 115
Contents Learning More About Scikit-learn 12 Summary 157 Questions 157 Natural Language Toolkit NLTK Sample Texts 161 165 Classifying Text Summary 169 Exercises 169 166 171 III: Intermediate Python 13 159 159 Frequency Distributions Text Objects 157 Functional Programming 173 173 Introduction to Functional Programming Scope and State 174 174 Depending on Global State Changing State 175 Changing Mutable Data 176 Functional Programming Functions List Comprehensions List Comprehension Basic Syntax Replacing map and filter Multiple Variables 181 182 182 Generator Expressions Generator Functions 14 179 180 181 Dictionary Comprehensions Generators 177 179 Summary 184 Questions 185 183 Object-Oriented Programming Grouping State and Function Classes and Instances 187 187 188 Private Methods and Variables Class Variables Special Methods 190 191 Representation Methods 192 190 xi
xli Contents Rich Comparison Methods Math Operator Methods 196 Inheritance Summary 199 Questions 15 192 195 199 Other Topics 201 201 Sorting Lists 201 Reading and Writing Files Context Managers datetime Objects 206 207 Regular Expressions Character Sets 204 205 208 Character Classes 209 209 Groups Named Groups 210 210 Find All Find Iterator 211 Substitution 211 Substitution Using Named Groups Compiling Regular Expressions A Summary 212 Questions 212 211 Answers to End-of-Chapter Questions Index 221 211 215 |
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| isbn | 9780136624356 0136624359 |
| language | English |
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| title_auth | Foundational Python for data science |
| title_exact_search | Foundational Python for data science |
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| title_full | Foundational Python for data science Kennedy R. Behrman |
| title_fullStr | Foundational Python for data science Kennedy R. Behrman |
| title_full_unstemmed | Foundational Python for data science Kennedy R. Behrman |
| title_short | Foundational Python for data science |
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