Syracuse University
OP-16: Commute Modal Split

1) Housing data

·         Filter to relevant terms (Fall 2022 - Spring 2023)

·         Remove duplicate entries by filtering to their maximum length of stay

·         If a student is present in the data frame they’re deemed to be an “On Campus” student

2) Class data (use all classes)

·         Filter to relevant terms (Fall 2022/Spring 2023)

·         Filter to only classes taken on “Main Campus” or the various study abroad centers (China, England, France, Hong Kong, Italy, Chile, Spain, Turkey)

·         Filter to classes taken “in person”

·         Filter to status “enrolled”

·         Filter to grades that result in some type of grade (Pass/Fail, A-F, etc)

·         Count/total the number of classes each student is taking

3) Study Abroad data

·         Filter to relevant terms (Fall 2022/Spring 2023)

·         Geocode missing lat/lons

·         Calculate distance from home address to study abroad destination

o   Total Study Abroad Travel Miles – 

4) Students who take Classes on Campus

·         Bring in Class data frame (with count of the number of classes a student is taking)

·         Join (left join) student data containing home address, home state, home country

5) Student Commuting Habits

·         Use data frame of student class counts and home address data

·         Join (left join) parking data provided by Parking Services

·         Join (left join) previously altered housing data (indicating if student lived on campus or not)

·         Assume that if student is in the data frame and IS NOT living on campus, they’re living off campus

o   Students taking on-line classes and classes not on campus were previously removed

·         Assume if a student is in the data frame and DOES NOT have a parking pass, they don’t have a parking pass

·         Establish a commuting distance for each student

o   If the student’s home to campus distance is less than 50 and they having a parking pass, they travel “x” distance

o   If the student’s home to campus distance is more than 50 and they have a parking pass, they live closer than indicated. Assign them a distance of 8 (mean distance from home)

o   If the student’s home to campus distance is less than 50 and they do not have a parking pass, assign them a distance of 0 (they commute some other way or are on campus)

o   If the student’s home to campus distance is more than 50 and they  do not have a parking pass, assign them a distance of 8 (they commute some other way or drive but park elsewhere)

6) Separate students who we KNOW ARE driving

·         Filter to students with “Parking Pass” and live “Off Campus”

·         If the student doesn’t have a US address assign them a commute distance of 8 miles

·         Establish Commuting number - Divide the number of classes they take by 2

o   Assuming they don’t make separate trips for each class

·         Establish One Way Weekly Miles - Multiply Commuting number (above) by (Commuting Distance)

·         Establish One Way Yearly Miles – Multiply Weekly Miles by 32 (number of weeks of classes)

7) Sort students who we don’t know their commuting method

·         Filter to students with NO “Parking Pass” and live “Off Campus”

·         Calculate a row number for each student in the data frame

·         Regardless of where or how far away they live, sort students into these buckets

o   % Walk to class

o % Bike to Class

o  % take the bus to class

o  % Drive to class

§  We can make the above assumption based on all classes are “in person”, “on campus”, classes. They should be getting to campus on a semi-regular basis.

·         Based on the above, calculate a new Commuting Distance for them as follows

o   Walk – 1mile

o   Bike – 1mile

o   Bus – 3miles

o   Driving – 8 Miles

·         Establish Commuting number - Divide the number of classes they take by 2

o   Assuming they don’t make separate trips for each class

·         Establish One Way Weekly Miles - Multiply Commuting number (above) by (Commuting Distance)

·         Establish One Way Yearly Miles – Multiply Weekly Miles by 32 (number of weeks of classes)

8) Calculate different student commuting numbers

·         Bind data from data frame 6 and data frame 7 to rejoin all students into one data frame

·         Total Yearly miles per method of Transportation

o   Driving – 

o   Bus – 

o   Walk – 

o   Bike – 

9) Calculate Total Miles Per Student

·     

Calculating Faculty Travel Mileage

1) Base Faculty/Staff data

·         Filter Faculty/Staff that have the same EMPLID and Same City (removing duplicates)

·         Calculate the distance from “home” to campus

·         Join (left join) Parking Pass data provided by Parking Services

2) Separate Faculty/Staff we KNOW ARE driving

·         Filter to Faculty/Staff that have “Parking Pass”

·         If a Faculty/Staff member doesn’t have a distance from home to campus, or if that distance is greater than 100 miles, assign them a Commuting Distance of 7

o   We’re assuming Faculty/Staff are not commuting >100 miles multiple times a week

·         Establish a Commuting number for each Faculty/Staff member

o   Faculty and Full Time – 4

o   Faculty and Part Time – 2

o   Staff and Full Time – 5

o   Staff and Part Time – 3

·         Calculate One Way Miles Per Week by multiplying Commuting Distance by Commuting Number

3) Sort Faculty/Staff whose commuting method we’re unsure of

·         Filter to Faculty/Staff that have “Parking Pass”

·         Regardless of Distance from campus, sort Faculty/Staff into these buckets

o  % Walk to work

o % take the bus to work

o   % Drive to work

·         Based on the above, calculate a new Commuting Distance for them as follows

o   Walk – 1mile

o   Bus – 3miles

o   Driving – 8 Miles

·         Establish a Commuting number for each Faculty/Staff member

o   Faculty and Full Time – 4

o   Faculty and Part Time – 2

o   Staff and Full Time – 5

o   Staff and Part Time – 3

·         Calculate One Way Miles Per Week by multiplying Commuting Distance by Commuting Number

4) Combine the “Driving” and “Non Driving” Faculty/Staff data frames

·         If the employee is faculty assume they commute for 32 weeks a year

o   If the employee is staff, they commute for 52 weeks a year

·         Calculate “One Way Yearly Commute” by multiplying one way weekly miles by Fac/Staff Weeks

o   Driving – 

o   Bus – 

o   Walking – 

5) Calculate Holiday commuting for Faculty/Staff

·         Use original unduplicated Faculty/Staff data frame

·         Filter to all faculty/staff who commute more than 100 miles (this number can be changed)

·         Calculate “To School” miles as miles (distance from home)

·         Calculate Thanksgiving miles as 2 x miles (distance from home)

·         Calculate Christmas miles as 2 x miles (distance from home)

·         Calculate Spring break miles as 2 x miles (distance from home)

·         Calculate “From School” miles as miles (distance from home)

o   3,146,824 miles traveled for Holidays and Breaks

6) Calculate all staff miles

·         Join (left join) Commuting and Holiday Travel data frames

·         Calculate total miles per year per faculty/staff member

o   Total Miles Traveled – 

We lowered the campus shuttle 7 points due to the fact that some of the students we are assuming are riding the bus, walk or bike.