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Python for Data Science
Introduction
Introduction(same as video on front page) (1:10)
Resources(Notebooks and Datasets)
Installation/Jupyter/Comments(Windows and MacOS/Jupyter Notebook)
Windows - Download Anaconda Distribution(includes Python) (2:42)
Windows - Install Anaconda Distribution (4:46)
Windows - Setting Up Environment (4:53)
Windows - Opening Jupyter Notebook (2:18)
MacOS - Anaconda Download and Install (3:31)
MacOS - Conda Environment (4:31)
MacOS -Jupyter Notebook (2:09)
Jupyter Notebook Interface and Shortcuts (8:02)
Python Fundamentals
How to Use Markdown Cells(Adding Headers, Links and Images) (2:04)
Comments - Inline and Block Comments (4:40)
Python Indentation (3:37)
Writing Single and Multiple Lines of Code (3:08)
Understanding Variables (2:28)
Main Data Types(Integer, Float, String, List, Dictionary) (5:36)
Lists - How To Use (11:09)
Dictionaries - How To Use (4:25)
Creating A Tuple (1:09)
Tuple - How To Use (5:21)
Create A Set (2:13)
Set - How To Use (3:08)
Operators (12:04)
Fill+in+Activity+(Fundamentals)
Decision and Looping Structures
Introducing Decision and Looping Structures (2:57)
If Statement (4:00)
Else Statement (3:16)
Elif (2:52)
For Loop (2:44)
While Loop (4:16)
Break And Continue Statements (3:23)
Functions
Introducing Functions (4:31)
Functions - General Syntax (4:17)
+ 1 Function (3:00)
Fav Band Function (3:34)
Celsius to Fahrenheit Function (3:42)
Optional Return Statement(and comparing to Print Statement) (4:48)
Defining a Function vs Calling(including different ways to call) (13:20)
Practical, Readl World Example - Function to Get Reddit Data (15:28)
Lamba Intro(Anonymous Functions) (2:38)
Formal Function vs Lambda for splitting strings (5:41)
Fill+in+Activity+(Looping+&+Functions)
Nested Data, Nested Iteration and List Comprehension
Introducing you to Nested Data and Iteration (1:58)
Simple Nested Example (4:43)
Double Indexing (3:41)
Assigning Values (2:27)
List of Dicts and Dicts of Dicts Example (4:25)
Nested Iteration - Iterating through List of Lists (4:23)
Defining List Comprehension and Syntax (5:04)
List Comprehension - Simple Examples (4:01)
List Comp as an Alternative to Loops (4:04)
PracticalReal World Example - Using Common Mathematical Notation (3:20)
Practical, Real World Example - Creating a Constrained ID (4:52)
Activity - Building Intuition(Loops, Nested Data, Iteration and List Comp) (5:06)
Fill+in+Activity+(Nested+and+List+Comprehension)
Numpy
Introducing Numpy (2:36)
Creating Our First Numpy Array (3:21)
Shaping An Array (4:27)
Creating a Sequence of Integers and Floats (2:04)
Element-Wise Operations (4:51)
A Range with a Shape(arrange function with reshape function) (2:00)
Numpy Indexing (5:09)
Numpy Slicing (2:46)
Indexing and Slicing with Breast Cancer Wisconsin Data-set (4:44)
Delete Elements (6:40)
Append (3:03)
Insert Elements (8:01)
Reshape - 1 Feature (5:32)
Flatten (2:26)
Transpose (2:31)
Concatenate (6:36)
Splitting (4:28)
Aggregate, Statistical Functions (3:18)
Numpy+Fill-In+Activity
Pandas
Introducing Pandas (1:30)
For SAS Programmers - Analogous Terms in Pandas(Python) (7:23)
Using Series As Input Into DataFrame (3:51)
Comparing Series and DataFrame (7:28)
Importing TSLA Dataset (2:45)
Index Based Selection(iloc) (2:35)
Label Based Selection(loc) (4:17)
Conditional Selection (5:08)
Summary Functions (3:14)
Grouping(groupby) (3:41)
Sorting (2:17)
Checking Data Types and Converting (3:20)
Dealing With Missing Values (6:37)
Dropping Columns-Variables and Records-Rows (2:51)
Renaming Columns-Variables and Records-Rows (3:40)
Concat Function + Pop Quiz (14:01)
Real World Activity - Add new Columns and Predict Stock Movement (3:56)
Activity Solutions
Solution - Fill in Activity - Fundamentals (7:49)
Solution - Fill in Activity - Looping and Functions (11:44)
Solution - Fill in Activity - Nested and List Comprehension (3:45)
Solution - Fill in Activity - Numpy (9:07)
Resources(Notebooks and Datasets)
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