




Tue Aug 27 
Book Draft: Table of Contents, 1. Preface, 2.12.2.1 Why Python? Installing Python Installing Python (Anaconda) 
Running python assignment(Due Thurs. Sep 5) 
Introductory remarks 
Automate the Boring Stuff: Part 1: Chapters 15. 
Thu Aug 29 
Book Draft: 2.2.2 Starting up Python, 2.2.3 First Python session 

Jupyter notebook Demo (notebook). 
Automate the Boring Stuff: Part 1: Chapters 15. 
Tue Sep 03 
Book Draft: 3.13.3 
Running python assignment due, running_python assignment solution and discussion. 


Thu Sep 05 




Tue Sep 10 
Book Draft: Python types, More Python types 

Notebook demo (notebook), Today's notebook (zipfile) 
Automate the Boring Stuff: Part One: Chapters 4, 5, 6 
Thu Sep 12 




Tue Sep 17 
Book Draft: Ifthen statements, Boolean results, loops, List comprehension, 
Python types assignment due. 

Automate the Boring Stuff: Chapters 2 and 3. 
Thu Sep 19 


Loops. 

Tue Sep 24 
Book Draft: 4.6 Functions. 
Quiz on Python types. Python types discussion notebook. Python types solution notebook. 
Logic of Functions, Functions. 
Automate the Boring Stuff: Chapter 3 
Thu Sep 26 




Tue Oct 01 
Book Draft: 4.7. Functions 5.1: importing, 5.2 Namespaces, 5.3 block structure, 5.4 Functions and function parameters, import, namespaces, classes. 
Functions assignment due. 
Programming odds and ends: Data structures (combining types), double loops, code blocks. imports and namespaces, classes, Intro Python classes, Summary notebook programming topics. 
Automate the Boring Stuff: Chapter 2, 8 
Thu Oct 03 




Tue Oct 08 
Book Draft: Numpy: 6.1  6.4 
Quiz on loops and functions and more Python types. Functions assignment answers. 
Intro to numpy: arrays, tables, splicing, arithmetic with arrays, arrays versus lists. More numpy (HOML) arrays, Indexing with Boolean arrays, Boolean indexing, fancy indexing, creating subarrays. 

Thu Oct 10 




Tue Oct 15 
Book Draft: Intro to pandas and pandas data frames 6.4  6.8., Pandas tutorial. 
Numpy assignment due, Midterm Study notebook, Midterm Study answers, Midterm more study problems, Midterm more study problems solution. 
Tools: Pandas Intro (HOML). Pandas notebook I, Pandas notebook II (Note that pandas notbook II presupposes that pandas notebook I has already been downloaded.) Pivot tables and merges in Pandas, Census data example, 

Thu Oct 17 




Tue Oct 22 

Numpy quiz (3rd quiz!), Numpy assignment solution. 
Lecture: Review 

Thu Oct 24 

Midterm (copy of old midterm) 


Tue Oct 29 
Book Draft: Introducing Regular Expressions, Reading in and tokenizing text data. 
Final project suggestions, Pandas assignment due . 
Regular expressions notebook. 
Automate the Boring Stuff: Chapters 7 
Thu Oct 31 




Tue Nov 05 
Book Draft: Chap. 7: Classification of text. Chap. 7: Linear classifiers, SVM classification, Applying linear classifiers to text: Movie review example. 
Pandas quiz. Pandas assignment solution. 
Classifying insults. Support Vector Machines, Classifying movie reviews with Naive Bayes, Regression, Regression and classification. 
NLTK Book ch. 3 
Thu Nov 07 




Tue Nov 12 
Book Draft: Chap. 9: Social networks intro, Gephi demo. 
Project suggestions revisited. 
Social Networks lectures slides, and Using networkx notebook, Networkx graphs with mousable nodes (using javascript), community detection, Community detection with a weighted graph, Facebook notebook. 

Thu Nov 14 




Tue Nov 19 
Book Draft: Chap. 7: Regression. Regression, 

03_Classification (HOML). Regression, Regression and classification. 
NLTK Book ch. 3 
Thu Nov 21 




Tue Nov 26 

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). 
Color and color maps I: Parallel coordinates plots. Color and color maps II: Correlation heat maps.. Visualizing higher dimensional data with color, Boxplot notebook, Geographic visualization. Kernel density estimates. Projections. 

Thu Nov 28 
H'day 
H'day 
H'day 
H'day 
Tue Dec 03 
Book Draft: Visualization. 

Visualizations that tell a story (Using bokeh). Geographic visualization. Kernel density estimates. Projections. 

Thu Dec 05 




Tue Dec 10 
Book Draft: Dimensionality reduction. 
Assignment solutions: Regular expressions, Anna Karenina, Regression and Classification, Census data. 
Dimensionality reduction with LSI slides, Dimensionality reduction with LSI notes, Python code for LSI example. 

Thu Dec 12 




Tue Dec 17 

Assignments: Final projects due: Tu Dec 17 

