Course Catalogs

Course Catalogs

The course_catalogs method allows you to quickly parse the UW Course Catalog for any/all UW Campuses. Parsing can be as quick as 5 seconds for all three campuses, but may take up to 45 seconds depending on the strength of your internet connection.

Import

from uwtools import course_catalogs

Args

Arg	Type	Default	Description
campuses	list or dict	['Seattle', 'Bothell', 'Tacoma']	The Campuses to get the course catalogs from. Can either be a list of campuses, or a dict where the keys are the campuses and values are a list of departments to parse from that campus. The dictionary parameter would resemble this: {'Seattle': ['EE', 'MSE', 'POLS'], 'Bothell': ['BBUS']}. You can select which campuses and departments you want to parse.
struct	str	'df'	Short for Data Structure and determines the return type for the course catalog. 'df' -> Pandas DataFrame. 'dict' -> Python Dictionary
show_progress	bool	False	Displays a progress meter in the console if True, otherwise does not.

Returns

A Pandas DataFrame or Python Dictionary (depending on the struct parameter) representing the course catalogs for all UW Campuses in the campuses list.

Storing Information in Files

Since every time this method is called, the UW Course Catalog is parsed, it is recommended that you store the data in a file for later use, to prevent parsing the catalog more than necessary.

If you use the default struct='df', you can store the information as a csv file using the following:

import uwtools

# Get the course catalogs from the uwtools library as a
# pandas DataFrame
course_catalog_df = uwtools.course_catalogs(struct='df')

course_catalog_df.to_csv('FILE_LOCATION')

To read in this information again:

import pandas as pd

course_catalog = pd.read_csv('FILE_LOCATION')
course_catalog.set_index('Course ID', axis=1, inplace=True)
course_catalog.fillna('', inplace=True)

---

If you're not familiar with the Pandas library, you can choose struct='dict', and create a .json file with the Dictionary as follows:

import json
import uwtools

# Get the course catalogs from the uwtools library as a
# python Dictionary
course_catalog_dict = uwtools.course_catalogs(struct='dict')

with open('FILE_LOCATION', mode='w') as f:
    # Indent and sort_keys are optional parameters, but help when looking 
    # through the .json file
    json.dump(course_catalog_dict, f, indent=4, sort_keys=True)

To read in this information again:

import json

with open('FILE_LOCATION', mode='r') as f:
    course_catalog_dict = json.loads(f.read())

Examples

Progress Bar

Progress bar will show you how many iterations have passed, as well as iterations per second (it/s) and the elapsed time.

578it [00:23, 17.15it/s]

DataFrame [struct='df']

Columns used in the DataFrame are (in this order):

['Campus', 'Department Name', 'College', 'Course Number', 'Course Name', 'Credits', 'Areas of Knowledge', 'Quarters Offered', 'Offered with', 'Prerequisites', 'Co-Requisites', 'Description']

Column Descriptions are listed at the bottom of the page.

The call to the course_catalogs function with the following parameters will yield the DataFrame below.

course_catalogs(campuses=['Seattle', 'Bothell', 'Tacoma'], struct='df', show_progress=False)

            Campus Department Name  ... Co-Requisites                                        Description
Course ID                           ...
TBECON220   Tacoma          TBECON  ...                Introduces microeconomic theory applied to ind...
TBECON221   Tacoma          TBECON  ...                Involves the study and analysis of the aggrega...
TBECON420   Tacoma          TBECON  ...                Applies tools of intermediate microeconomic th...
TBECON421   Tacoma          TBECON  ...                Focuses on the use of intermediate economic th...
TBECON422   Tacoma          TBECON  ...                Examines the statistical tools that are used t...
...            ...             ...  ...           ...                                                ...
ENVH598    Seattle            ENVH  ...                Supervised project work on a topic related to ...
ENVH599    Seattle            ENVH  ...                Assignment to an environmental research or ser...
ENVH600    Seattle            ENVH  ...                Prerequisite: permission of departmental advis...
ENVH700    Seattle            ENVH  ...                Prerequisite: permission of departmental advis...
ENVH800    Seattle            ENVH  ...                Prerequisite: permission of departmental advis...

Dictionary [struct='dict']

The Dictionary option for the Course Catalogs returns a dictionary with course names (department name followed by the 3-digit course code) as keys, and dictionaries containing all course information as values.

The call to the course_catalogs function with the following parameters will yield the Dictionary below.

course_catalogs(campuses=['Seattle', 'Bothell', 'Tacoma'], struct='dict', show_progress=False)

{
    "AA101": {
        "Areas of Knowledge": "NW",
        "Campus": "Seattle",
        "Co-Requisites": "",
        "College": "College of Engineering",
        "Course Name": "Air and Space Vehicles",
        "Course Number": "101",
        "Credits": "5",
        "Department Name": "AA",
        "Description": "",
        "Offered with": "",
        "Prerequisites": "",
        "Quarters Offered": ""
    },
    "AA198": {
        "Areas of Knowledge": "NW",
        "Campus": "Seattle",
        "Co-Requisites": "",
        "College": "College of Engineering",
        "Course Name": "Special Topics in Aeronautics and Astronautics",
        "Course Number": "198",
        "Credits": "1-5, max. 10",
        "Department Name": "AA",
        "Description": "Introduces the field of Aeronautics and Astronautics. Topics include aircraft flight, rocket propulsion, space travel, and contemporary space missions. May include hands-on activities. For non-majors.",
        "Offered with": "",
        "Prerequisites": "",
        "Quarters Offered": ""
    },
    ...

Column Descriptions

Column Name	Description
Campus	The campus the course is offered at.
Department Name	The name of the department the course is a part of. Denoted by a series of capital letters with no spaces.
College	The college the department of the course is in. Example: Electrical Engineering (EE) is in the College of Engineering.
Course Number	The 3 digit number identifying the course.
Course Name	The name of the course.
Credits	The number of credits offered for the course. Some courses have variable credits offered/different credit options. Check out the UW's guide for the credit system here.
Areas of Knowledge	Areas of Knowledge essentially are credit types. More Information.
Quarters Offered	The quarters of the year the course is offered. Autumn, Winter, Spring, Summer.
Offered with	At times, a course may be offered alongside a similar course in a different department.
Prerequisites	Courses that must be taken in order to take the course.
Co-Requisites	Courses that must be taken at the same time the desired course is being taken.
Description	The description of the course objectives.