San Jose State University : Site Name


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Buddy likes to climb trees.

Ronald Mak

Department of Computer Science
Department of Applied Data Science
Spring Semester 2023

Office hours: MW 4:30 – 5:30 PM Clark Hall CL 325
Office location: Clark Hall CL 325 (mostly working from home)

DATA 200 Computational Programming for Analytics (section 21)

W 6:00 - 8:45 PM room BBC 021


# Assigned Due Assignment
1 Feb 1 Feb 8 Initial program
2 Feb 8 Feb 15 If statements and loops

Solutions: Assignment2-solutions.ipynb
Fun graphs: BinarySearchGraphs.ipynb
3 Feb 15 Feb 22 Watering Plans

Solution: WateringPlans.ipynb
4 Feb 22 Mar 1 List Practice

Solution: Assignment4-solutions.ipynb
5 Mar 1 Mar 8 1. Dictionaries
2. Sets

Solution: Assignment5.1-solutions.ipynb    Assignment5.2-solutions.ipynb
6 Mar 8 Mar 15 Matrix Multiplication with numpy

Solution: Assignment6-solution.ipynb   
7 Mar 15 Mar 22 SJSU Administrators and Professors
8 Mar 22 Apr 5 Simple Data Analysis


Week Date Content
1 Jan 25 Waiver test
2 Feb 1 Slides: Python's role in data analytics; software installations; ways to run Python code; introduction to Python programming

Notebooks: 02_02.ipynb   02_03.ipynb   02_04.ipynb   02_05.ipynb   02_06.ipynb   02_07.ipynb   02_08.ipynb   02_09.ipynb   AgeHistogram.ipynb
Python programs:  
3 Feb 8 Slides: Python control statements: if, while, and for; measures of central tendency

Notebooks: 03_05.ipynb   03_06.ipynb   03_07.ipynb   03_08.ipynb   03_09.ipynb   03_10.ipynb   03_11.ipynb   03_13.ipynb   03_14.ipynb   03_15.ipynb   03_16.ipynb   03_17.ipynb
4 Feb 15 Slides: Functions; program design and development; Assignment #3

04_02.ipynb   04_03.ipynb   04_04.ipynb   04_05.ipynb   04_07.ipynb   04_08.ipynb   04_09.ipynb   04_10.ipynb   04_11.ipynb   NumberTranslator.ipynb
5 Feb 22 Slides: More about functions; lists

Notebooks: 04_12.ipynb   04_13.ipynb   04_14.ipynb   04_15.ipynb   05_02.ipynb   05_03.ipynb   05_04.ipynb   05_05.ipynb   05_06.ipynb   05_07.ipynb   05_08.ipynb   05_09.ipynb   05_10.ipynb   05_12.ipynb   05_15.ipynb   05_16.ipynb   Scope.ipynb

Practice quiz: Quiz-0222-1401.ipynb
6 Mar 1 Slides: Dictionaries and sets

06.02.01.ipynb   06.02.02.ipynb   06.02.03.ipynb   06.02.04.ipynb   06.02.05.ipynb   06.02.07.ipynb   06.02.08.ipynb   06.02.09.ipynb   06.03.00.ipynb   06.03.01.ipynb   06.03.02.ipynb   06.03.03.ipynb   06.03.04.ipynb
7 Mar 8 Slides: numpy

Notebooks: 07_02.ipynb   07_03.ipynb   07_04.ipynb   07_05.ipynb   07_06.ipynb   07_07.ipynb   07_08.ipynb   07_09.ipynb   07_10.ipynb   Scores-list.ipynb   Scores_array.ipynb   MatrixMultiplication.ipynb
8 Mar 15 Slides: A deeper look at strings; regular expressions

Notebooks: 08_02.01.ipynb   08_02.02.ipynb   08_02.03.ipynb   08_03.ipynb   08_04.ipynb   08_05.ipynb   08_06.ipynb   08_07.ipynb   08_08.ipynb   08_09.ipynb   08_10.ipynb   08_11.ipynb   08_12.01.ipynb   08_12.02.ipynb   08_12.03.ipynb
9 Mar 22 Slides: File I/O; reading and writing CSV files; analysis of Titanic survival data

Notebooks: 09_03.01.ipynb   09_03.02.ipynb   09_04.ipynb   09_05.ipynb   09_08.01.ipynb   09_08.02.ipynb   09_09.ipynb   09_10.ipynb   09_11.ipynb   09_12.01.ipynb  
Analysis of Titanic survival data: TitanicSurvival.ipynb    TitanicERROR.ipynb
Copy file program:
CSV data files: UsedCars.csv   TitanicSurvival.csv
JSON data file: accounts.json


This course emphasizes learning the Python programming language and its libraries well enough to develop data analytical applications. Class meetings will encourage high class participation. Mini-labs during each class meeting will give you opportunities to try what you just learned.

Course Learning Outcomes (CLO)


Classified standing or instructor consent.

Recommended Books

Python for Everyone, Edition 2.0

Cay Horstmann and Rance Necaise
Wiley, 2019
ISBN 978-1-943153-67-1

An excellent book for beginning programmers. Dr. Horstmann was a professor in the Computer Science Department at SJSU.
Intro to Python for Computer Science and Data Science:
Learning to Program with AI, Big Data and The Cloud

Paul Deitel and Harvey Deitel
Pearson Education, 2019
ISBN 978-1107186125

Another excellent book for beginning programmers, more focused on data science.
Python for Programmers with Introductory AI Case Studies

Paul Deitel and Harvey Deitel
Pearson Education, 2019
ISBN 978-0135224335

Essentially the same book as the one above but without the introductory material for beginning programmers. The first part of the class will be based on the first ten chapters of this book.
Hands-On Data Analysis with Pandas, second edition

Stephanie Molin
Packt Publishing, 2021
ISBN 978-1-80056-345-2

The last part of the class will be based on the first two sections of this book.

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