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    Education

    Python for Everybody (Video/PY4E)

    These are the video lectures to supplement the textbook ‘Python for Everybody: Exploring Information’ and its associated web site www.py4e.com

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    Copyright: © Dr. Charles R. Severance, CC-BY-NC

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    Latest Episodes:
    15.4 Database Key Types Sep 28, 2016
    Show notes

    We look at primary keys, logical keys and foreign keys. We look at how foreign keys are represented in the database.


    15.5 Representing Relationships in Database Tables Sep 28, 2016
    Show notes

    We look at how we map a logical database model to a physical database model by adding columns and constraints to model the table-to-table relationships.


    15.6 Multi-Table Retrieval using JOIN Sep 28, 2016
    Show notes

    We look at how to reconstruct complete views of the data when data is properly distributed across multiple tables and connected via foreign keys. We learn the JOIN operation and ON clause in SQL.


    Worked Example: Multiple Tracks Sep 28, 2016
    Show notes

    We work through a track data example with four tables.


    15.7 Many-to-Many Relationships Sep 28, 2016
    Show notes

    We look at how to build a connector table to represent many-to-many relationships such as students and courses in database tables. We also learn about composite primary keys.


    Worked Example: Many-to-Many Sep 28, 2016
    Show notes

    We extend the Twitter example to represent friends using Many-to-Many relationships.


    16.1 Visualizing Map Data Sep 27, 2016
    Show notes

    In this assignment we make use of the Google GeoCoding API to look up addresses, store the data in a database and then use Google Maps to visualize the data.


    Worked Example: Retrieving Geocoded Data Sep 27, 2016
    Show notes

    Worked Example: Retrieving Geocoded Data


    16.2 Building a Web Search Engine Sep 27, 2016
    Show notes

    We build a web crawler that retrieves web pages and links from those pages an copies the pages into the database. Once we have retrieved our web data we run a simple Page Rank algorithm on the data and visualize the results.


    Worked Example: A Web Crawler Sep 27, 2016
    Show notes

    Worked Example: A Web Crawler


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