




Wed Aug 26 
Book Draft: Table of Contents, 1. Preface, 2.12.3 What is this course about? What is Python? Why Python 2.4 Install Python (Anaconda) or run in the cloud? 
Assignment: Running Python Notebook. 
Introductory remarks Jupyter notebook Demo (notebook). 
Python Data Science HB (PDSHB): Chapter 1. IPython PDSHB Notebook Index. (Notebooks contain the text of PDSHB + executable text snippets) 
Wed Sep 02 
Book Draft: 3.13.3 Python types I, More Python types II. 
Running python assignment due. 
Notebook demo (notebook), Python types notebook, Python types I: Strings, numbers. Python types II: Sequences, Dictionaries, sets. 
VanDerPlas: Whirlwind Tour of Python: Chapter 7: Notebooks. 
Wed Sep 09 
Book Draft: Ifthen statements, Boolean results, loops, List comprehension, 
Assignment: Python types assignment due. 
Loops, conditional clauses notebook. 
VanDerPlas: Whirlwind Tour of Python: Chapter 8, 9, 12: Notebooks. 
Wed Sep 16 
Book Draft: 5.1: importing, 5.2 Namespaces, 5.3 block structure, 5.4 Functions and function parameters, import, namespaces, classes. 

Notebooks: Functions. 

Wed Sep 23 
Book Draft: Book Draft: 4.6 Functions. 4.7. Functions 
Functions assignment due. 
Notebooks: Functions. Sets, Set operations, Set example, Iterators and generators, Climate change problem (containers), DNA string (containers, coding), DNA translation(Dictionary codebook). 
VanDerPlas: Whirlwind Tour of Python: Chapter 9: Notebooks. 
Wed Sep 30 
Book Draft: Numpy: 6.1  6.4 

Notebooks: Intro to numpy: arrays, tables, splicing, arithmetic with arrays, arrays versus lists, Boolean arrays and Boolean indexing, fancy indexing. More nitty gritty on Boolean arrays (from PDSHB), Numpy tools A broader survey of numpy capabilities (From Handson Machine Learning). In class Boolean notebook, Numpy broadcasting (notes/examples). 
Python Data Science HB (PDSHB): Chapter 2. Numpy. PDSHB Notebook Index. 
Wed Oct 07 

Functions assignment solution. In class Boolean notebook solutions. 


Wed Oct 14 
Book Draft: Intro to pandas and pandas data frames 6.4  6.8., Pandas tutorial. 
Numpy assignment due, Midterm Study notebook, Midterm Study answers. 
Lecture: Mid Semester Review. Tools: Pandas Intro (HOML). Pandas notebook I, Pandas notebook II 
Python Data Science HB (PDSHB): Chapter 3. Pandas. PDSHB Notebook Index. 
Wed Oct 21 

Midterm 2020. 
Notebooks: Pivot tables and merges in Pandas, Census data example, Importing and loading files in Colab. 

Wed Oct 28 
Book Draft: Introducing Regular Expressions, Reading in and tokenizing text data. 
Final project suggestions, Numpy assignment solution. 
Regular expressions notebook. 
VanDerPlas: Whirlwind Tour of Python: Chapter 15: Notebooks. NLTK Book ch. 3 
Wed Nov 04 
Book Draft: Chap. 7: Classification of text. Regression, Chap. 7: Linear classifiers, SVM classification, Applying linear classifiers to text: Movie review example. 
Pandas assignment due . 
notebooks: Regression. Linear Classifiers (SVMs). Iris data classification (sklearn). Classifying movie review (NLTK); precision, recall, etcetera. Sklearn/Insult classification. 
Python Data Science HB (PDSHB): Chapter 5. Machine learning. PDSHB Notebook Index. 
Wed Nov 11 
H'day 
H'day 
H'day 
H'day 
Wed Nov 18 
Book Draft: Chap. 9: Social networks intro, Gephi demo. 
Project suggestions revisited. 
Social Networks lectures slides, and New using networkx notebook, Centrality experiments, Assortativity notebook. 

Wed Nov 25 
H'day 
H'day 
H'day 
H'day 
Wed Dec 02 
Book Draft: Chap. 7: Regression. Regression, 

Matplotlib Intro, 03_Classification (HOML). Regression, Regression and classification. 
NLTK Book ch. 3 
Wed Dec 09 
Book Draft: Chap. 8: Visualization. 
Either Regular expressions assignment or Anna Karenina Assignment or Classifying insults, or Regression and classification, or Census data example (Section 1.9 has an assignment). Final project due in one week! 
Notebooks: Plotting basics, Box and violin plots, color maps 1, color maps 2, Mandelbrot and others. Linear Mapping examples. 

Wed Dec 16 


Dimensionality reduction with LSI slides, Dimensionality reduction with LSI notes, Python code for LSI example, 
