An edition of Python Basics: With Illustrations from the Financial Markets
(2019)
Python Basics
With Illustrations from the Financial Markets
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The material presented here is a condensed introduction to Python and its data science related libraries such as NumPy, Pandas, and Matplotlib. The illustrative examples we use are associated with the financial markets.
We think it should also be useful to
- Anyone who wants a brief introduction to Python and the key components
of its data science stack, and
- Python programmers who want a quick refresher on using Python for
data analysis.
We do not expect any of our readers to have a formal background in computer science, although some familiarity with programming would be nice to have. The concepts and ideas here are covered with several examples to help connect theory to practice.
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Previews available in: English
Subjects
Python, Programming, Financial markets, algorithmic trading, trading, algorithm, codingShowing 1 featured edition. View all 1 editions?
| Edition | Availability |
|---|---|
1
Python Basics: With Illustrations from the Financial Markets
2019, QuantInsti Quantitative Learning Pvt. Ltd.
in English
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aaaa
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Book Details
Table of Contents
Contents
1 Introduction
Page 1 |
1.1 What is Python?
Page 1 |
1.2 Where is Python used?
Page 2 |
1.3 Why Python?
Page 2 |
1.4 History of Python
Page 6 |
1.5 Python 3 versus Python 2
Page 7 |
1.6 Key Takeaways
Page 10 |
2 Getting Started with Python
Page 11 |
2.1 Python as a Calculator
Page 11 |
2.1.1 Floating Point Expressions
Page 14 |
2.2 Python Basics
Page 17 |
2.2.1 Literal Constants
Page 17 |
2.2.2 Numbers
Page 18 |
2.2.3 Strings
Page 18 |
2.2.4 Comments
Page 19 |
2.2.5 print() function
Page 20 |
2.2.6 format() function
Page 22 |
2.2.7 Escape Sequence
Page 23 |
2.2.8 Indentation
Page 24 |
2.3 Key Takeaways
Page 25 |
3 Variables and Data Types in Python
Page 27 |
3.1 Variables
Page 27 |
3.1.1 Variable Declaration and Assignment
Page 27 |
3.1.2 Variable Naming Conventions
Page 28 |
3.2 Data Types
Page 31 |
3.2.1 Integer
Page 31 |
3.2.2 Float
Page 32 |
3.2.3 Boolean
Page 34 |
3.2.4 String
Page 35 |
3.2.5 Operations on String
Page 38 |
3.2.6 type() function
Page 41 |
3.3 Type Conversion
Page 42 |
3.4 Key Takeaways
Page 45 |
4 Modules, Packages and Libraries
Page 47 |
4.1 Standard Modules
Page 50 |
4.2 Packages
Page 52 |
4.3 Installation of External Libraries
Page 53 |
4.3.1 Installing pip
Page 54 |
4.3.2 Installing Libraries
Page 54 |
4.4 Importing modules
Page 56 |
4.4.1 import statement
Page 56 |
4.4.2 Selective imports
Page 57 |
4.4.3 The Module Search Path
Page 59 |
4.5 dir()function
Page 61 |
4.6 Key Takeaways
Page 63 |
5 Data Structures
Page 65 |
5.1 Indexing and Slicing
Page 65 |
5.2 Array
Page 67 |
5.2.1 Visualizing an Array
Page 67 |
5.2.2 Accessing Array Element
Page 68 |
5.2.3 Manipulating Arrays
Page 68 |
5.3 Tuples
Page 70 |
5.3.1 Accessing tuple elements
Page 71 |
5.3.2 Immutability
Page 72 |
5.3.3 Concatenating Tuples
Page 72 |
5.3.4 Unpacking Tuples
Page 73 |
5.3.5 Tuple methods
Page 73 |
5.4 Lists
Page 74 |
5.4.1 Accessing List Items
Page 75 |
5.4.2 Updating Lists
Page 75 |
5.4.3 List Manipulation
Page 77 |
5.4.4 Stacks and Queues
Page 80 |
5.5 Dictionaries
Page 82 |
5.5.1 Creating and accessing dictionaries
Page 82 |
5.5.2 Altering dictionaries
Page 85 |
5.5.3 Dictionary Methods
Page 86 |
5.6 Sets
Page 88 |
5.7 Key Takeaways
Page 92 |
6 Keywords & Operators
Page 95 |
6.1 Python Keywords
Page 95 |
6.2 Operators
Page 106 |
6.2.1 Arithmetic operators
Page 106 |
6.2.2 Comparison operators
Page 107 |
6.2.3 Logical operators
Page 109 |
6.2.4 Bitwise operator
Page 110 |
6.2.5 Assignment operators
Page 114 |
6.2.6 Membership operators
Page 118 |
6.2.7 Identity operators
Page 118 |
6.2.8 Operator Precedence
Page 119 |
6.3 Key Takeaways
Page 121 |
7 Control Flow Statements
Page 123 |
7.1 Conditional Statements
Page 123 |
7.1.1 The if statement
Page 123 |
7.1.2 The elif clause
Page 125 |
7.1.3 The else clause
Page 125 |
7.2 Loops
Page 126 |
7.2.1 The while statement
Page 126 |
7.2.2 The for statement
Page 128 |
7.2.3 The range() function
Page 128 |
7.2.4 Looping through lists
Page 130 |
7.2.5 Looping through strings
Page 131 |
7.2.6 Looping through dictionaries
Page 131 |
7.2.7 Nested loops
Page 133 |
7.3 Loop control statements
Page 134 |
7.3.1 The break keyword
Page 134 |
7.3.2 The continue keyword
Page 135 |
7.3.3 The pass keyword
Page 136 |
7.4 List comprehensions
Page 137 |
7.5 Key Takeaways
Page 140 |
8 Iterators & Generators
Page 143 |
8.1 Iterators
Page 143 |
8.1.1 Iterables
Page 143 |
8.1.2 enumerate() function
Page 145 |
8.1.3 The zip()function
Page 146 |
8.1.4 Creating a custom iterator
Page 147 |
8.2 Generators
Page 149 |
8.3 Key Takeaways
Page 151 |
9 Functions in Python
Page 153 |
9.1 Recapping built-in functions
Page 154 |
9.2 User defined functions
Page 155 |
9.2.1 Functions with a single argument
Page 156 |
9.2.2 Functions with multiple arguments and a return statement
Page 157 |
9.2.3 Functions with default arguments
Page 159 |
9.2.4 Functions with variable length arguments
Page 160 |
9.2.5 DocStrings
Page 162 |
9.2.6 Nested functions and non-local variable
Page 164 |
9.3 Variable Namespace and Scope
Page 166 |
9.3.1 Names in the Python world
Page 167 |
9.3.2 Namespace
Page 168 |
9.3.3 Scopes
Page 169 |
9.4 Lambda functions
Page 174 |
9.4.1 map() Function
Page 175 |
9.4.2 filter() Function
Page 176 |
9.4.3 zip() Function 177
9.5 Key Takeaways
Page 179 |
10 NumPy Module
Page 181 |
10.1 NumPy Arrays
Page 182 |
10.1.1 N-dimensional arrays
Page 185 |
10.2 Array creation using built-in functions
Page 186 |
10.3 Random Sampling in NumPy
Page 188 |
10.4 Array Attributes and Methods
Page 192 |
10.5 Array Manipulation
Page 198 |
10.6 Array Indexing and Iterating
Page 203 |
10.6.1 Indexing and Subsetting
Page 203 |
10.6.2 Boolean Indexing
Page 205 |
10.6.3 Iterating Over Arrays
Page 210 |
10.7 Key Takeaways
Page 212 |
11 Pandas Module
Page 215 |
11.1 Pandas Installation
Page 215 |
11.1.1 Installing with pip
Page 216 |
11.1.2 Installing with Conda environments
Page 216 |
11.1.3 Testing Pandas installation
Page 216 |
11.2 What problem does Pandas solve?
Page 216 |
11.3 Pandas Series
Page 217 |
11.3.1 Simple operations with Pandas Series
Page 219 |
11.4 Pandas DataFrame
Page 223 |
11.5 Importing data in Pandas
Page 228 |
11.5.1 Importing data from CSV file
Page 228 |
11.5.2 Customizing pandas import
Page 228 |
11.5.3 Importing data from Excel files
Page 229 |
11.6 Indexing and Subsetting
Page 229 |
11.6.1 Selecting a single column
Page 230 |
11.6.2 Selecting multiple columns
Page 230 |
11.6.3 Selecting rows via []
Page 231 |
11.6.4 Selecting via .loc[] (By label)
Page 232 |
11.6.5 Selecting via .iloc[] (By position)
Page 233 |
11.6.6 Boolean indexing
Page 234 |
11.7 Manipulating a DataFrame
Page 235 |
11.7.1 Transpose using .T
Page 235 |
11.7.2 The .sort_index() method
Page 236 |
11.7.3 The .sort_values() method
Page 236 |
11.7.4 The .reindex() function
Page 237 |
11.7.5 Adding a new column
Page 238 |
11.7.6 Delete an existing column
Page 239 |
11.7.7 The .at[] (By label)
Page 241 |
11.7.8 The .iat[] (By position)
Page 242 |
11.7.9 Conditional updating of values
Page 243 |
11.7.10 The .dropna() method
Page 244 |
11.7.11 The .fillna() method
Page 246 |
11.7.12 The .apply() method
Page 247 |
11.7.13 The .shift() function
Page 248 |
11.8 Statistical Exploratory data analysis
Page 250 |
11.8.1 The info() function
Page 250 |
11.8.2 The describe() function
Page 251 |
11.8.3 The value_counts() function
Page 252 |
11.8.4 The mean() function
Page 252 |
11.8.5 The std() function
Page 253 |
11.9 Filtering Pandas DataFrame
Page 253 |
11.10Iterating Pandas DataFrame
Page 255 |
11.11Merge, Append and Concat Pandas DataFrame
Page 256 |
11.12TimeSeries in Pandas
Page 259 |
11.12.1 Indexing Pandas TimeSeries
Page .259 |
11.12.2 Resampling Pandas TimeSeries
Page 262 |
11.12.3 Manipulating TimeSeries
Page 263 |
11.13Key Takeaways
Page 265 |
12 Data Visualization with Matplotlib
Page 267 |
12.1 Basic Concepts
Page 268 |
12.1.1 Axes
Page 269 |
12.1.2 Axes method v/s pyplot
Page 272 |
12.1.3 Multiple Axes
Page 273 |
12.2 Plotting
Page 275 |
12.2.1 Line Plot
Page 276 |
12.2.2 Scatter Plot
Page 289 |
12.2.3 Histogram Plots
Page 294 |
12.3 Customization
Page 300 |
12.4 Key Takeaways
Page 313 |
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| August 22, 2019 | Edited by Rekhit | Edited without comment. |
| August 21, 2019 | Created by Rekhit | Added new book. |