Box-Plots for Education Hosted By Education Resource Strategies

competition
complete
$7,500

Woohoo! This competition has come to a close!

Many thanks to the participants for all of their hard work and commitment to using data for good!

Problem description

This is where you'll find all of the documentation about this dataset and the problem we are trying to solve. For this competition, there are three subsections to the problem description:

The features in this dataset


Your goal is to predict the probability that a certain label is attached to a budget line item. Each row in the budget has mostly free-form text features, except for the two below that are noted as float. Any of the fields may or may not be empty

  • FTE float - If an employee, the percentage of full-time that the employee works.
  • Facility_or_Department - If expenditure is tied to a department/facility, that department/facility.
  • Function_Description - A description of the function the expenditure was serving.
  • Fund_Description - A description of the source of the funds.
  • Job_Title_Description - If this is an employee, a description of that employee's job title.
  • Location_Description - A description of where the funds were spent.
  • Object_Description - A description of what the funds were used for.
  • Position_Extra - Any extra information about the position that we have.
  • Program_Description - A description of the program that the funds were used for.
  • SubFund_Description - More detail on Fund_Description
  • Sub_Object_Description - More detail on Object_Description
  • Text_1 - Any additional text supplied by the district.
  • Text_2 - Any additional text supplied by the district.
  • Text_3 - Any additional text supplied by the district.
  • Text_4 - Any additional text supplied by the district.
  • Total float - The total cost of the expenditure.

Feature data example


For example, a single row in the dataset might have these values:

FTE 1
Facility_or_Department NaN
Function_Description Care and Upkeep of Building Services
Fund_Description General
Job_Title_Description CLEANER
Location_Description BUILDING OPERATIONS SECTION
Object_Description Regular *
Position_Extra NaN
Program_Description NaN
SubFund_Description Operation and Maintenance of Plant Services
Sub_Object_Description NaN
Text_1 FACILITIES ADMINISTRATION
Text_2 FACILITIES
Text_3 NaN
Text_4 NaN
Total 36664.44

The labels in this dataset


For each of these rows, ERS attaches one label from each of 9 different categories:

  • Function:

    • Aides Compensation
    • Career & Academic Counseling
    • Communications
    • Curriculum Development
    • Data Processing & Information Services
    • Development & Fundraising
    • Enrichment
    • Extended Time & Tutoring
    • Facilities & Maintenance
    • Facilities Planning
    • Finance, Budget, Purchasing & Distribution
    • Food Services
    • Governance
    • Human Resources
    • Instructional Materials & Supplies
    • Insurance
    • Legal
    • Library & Media
    • NO_LABEL
    • Other Compensation
    • Other Non-Compensation
    • Parent & Community Relations
    • Physical Health & Services
    • Professional Development
    • Recruitment
    • Research & Accountability
    • School Administration
    • School Supervision
    • Security & Safety
    • Social & Emotional
    • Special Population Program Management & Support
    • Student Assignment
    • Student Transportation
    • Substitute Compensation
    • Teacher Compensation
    • Untracked Budget Set-Aside
    • Utilities
  • Object_Type:

    • Base Salary/Compensation
    • Benefits
    • Contracted Services
    • Equipment & Equipment Lease
    • NO_LABEL
    • Other Compensation/Stipend
    • Other Non-Compensation
    • Rent/Utilities
    • Substitute Compensation
    • Supplies/Materials
    • Travel & Conferences
  • Operating_Status:

    • Non-Operating
    • Operating, Not PreK-12
    • PreK-12 Operating
  • Position_Type:

    • (Exec) Director
    • Area Officers
    • Club Advisor/Coach
    • Coordinator/Manager
    • Custodian
    • Guidance Counselor
    • Instructional Coach
    • Librarian
    • NO_LABEL
    • Non-Position
    • Nurse
    • Nurse Aide
    • Occupational Therapist
    • Other
    • Physical Therapist
    • Principal
    • Psychologist
    • School Monitor/Security
    • Sec/Clerk/Other Admin
    • Social Worker
    • Speech Therapist
    • Substitute
    • TA
    • Teacher
    • Vice Principal
  • Pre_K:

    • NO_LABEL
    • Non PreK
    • PreK
  • Reporting:

    • NO_LABEL
    • Non-School
    • School
  • Sharing:

    • Leadership & Management
    • NO_LABEL
    • School Reported
    • School on Central Budgets
    • Shared Services
  • Student_Type:

    • Alternative
    • At Risk
    • ELL
    • Gifted
    • NO_LABEL
    • Poverty
    • PreK
    • Special Education
    • Unspecified
  • Use:

    • Business Services
    • ISPD
    • Instruction
    • Leadership
    • NO_LABEL
    • O&M
    • Pupil Services & Enrichment
    • Untracked Budget Set-Aside

Note, there is a hierarchical relationship for these labels. If a line is marked as Non-Operating in the Operating_Status category, then all of the other labels should be marked as NO_LABEL since ERS does not analyze and compare non-operating budget items.

Label example


The row in the example above would have the following labels attached to it:

Function Facilities & Maintenance
Object_Type Base Salary/Compensation
Operating_Status PreK-12 Operating
Position_Type Custodian
Pre_K Non PreK
Reporting School
Sharing School Reported
Student_Type Unspecified
Use O&M

Submission format


Your goal is to predict a probability for each possible label in the dataset given a row of new data. Each of these probabilities goes in a separate column in the submission file. The submission must be 50064x104 where 50064 is the number of rows in the test dataset (excluding the header) and 104 is the number of columns (excluding a first column of row ids). The columns in the submission have the format ColumnName__PossibleLabel, which we have listed below for your convenience. This is simply a flattening of the labels that we listed above.

  • Function__Aides Compensation
  • Function__Career & Academic Counseling
  • Function__Communications
  • Function__Curriculum Development
  • Function__Data Processing & Information Services
  • Function__Development & Fundraising
  • Function__Enrichment
  • Function__Extended Time & Tutoring
  • Function__Facilities & Maintenance
  • Function__Facilities Planning
  • Function__Finance, Budget, Purchasing & Distribution
  • Function__Food Services
  • Function__Governance
  • Function__Human Resources
  • Function__Instructional Materials & Supplies
  • Function__Insurance
  • Function__Legal
  • Function__Library & Media
  • Function__NO_LABEL
  • Function__Other Compensation
  • Function__Other Non-Compensation
  • Function__Parent & Community Relations
  • Function__Physical Health & Services
  • Function__Professional Development
  • Function__Recruitment
  • Function__Research & Accountability
  • Function__School Administration
  • Function__School Supervision
  • Function__Security & Safety
  • Function__Social & Emotional
  • Function__Special Population Program Management & Support
  • Function__Student Assignment
  • Function__Student Transportation
  • Function__Substitute Compensation
  • Function__Teacher Compensation
  • Function__Untracked Budget Set-Aside
  • Function__Utilities
  • Object_Type__Base Salary/Compensation
  • Object_Type__Benefits
  • Object_Type__Contracted Services
  • Object_Type__Equipment & Equipment Lease
  • Object_Type__NO_LABEL
  • Object_Type__Other Compensation/Stipend
  • Object_Type__Other Non-Compensation
  • Object_Type__Rent/Utilities
  • Object_Type__Substitute Compensation
  • Object_Type__Supplies/Materials
  • Object_Type__Travel & Conferences
  • Operating_Status__Non-Operating
  • Operating_Status__Operating, Not PreK-12
  • Operating_Status__PreK-12 Operating
  • Position_Type__(Exec) Director
  • Position_Type__Area Officers
  • Position_Type__Club Advisor/Coach
  • Position_Type__Coordinator/Manager
  • Position_Type__Custodian
  • Position_Type__Guidance Counselor
  • Position_Type__Instructional Coach
  • Position_Type__Librarian
  • Position_Type__NO_LABEL
  • Position_Type__Non-Position
  • Position_Type__Nurse
  • Position_Type__Nurse Aide
  • Position_Type__Occupational Therapist
  • Position_Type__Other
  • Position_Type__Physical Therapist
  • Position_Type__Principal
  • Position_Type__Psychologist
  • Position_Type__School Monitor/Security
  • Position_Type__Sec/Clerk/Other Admin
  • Position_Type__Social Worker
  • Position_Type__Speech Therapist
  • Position_Type__Substitute
  • Position_Type__TA
  • Position_Type__Teacher
  • Position_Type__Vice Principal
  • Pre_K__NO_LABEL
  • Pre_K__Non PreK
  • Pre_K__PreK
  • Reporting__NO_LABEL
  • Reporting__Non-School
  • Reporting__School
  • Sharing__Leadership & Management
  • Sharing__NO_LABEL
  • Sharing__School Reported
  • Sharing__School on Central Budgets
  • Sharing__Shared Services
  • Student_Type__Alternative
  • Student_Type__At Risk
  • Student_Type__ELL
  • Student_Type__Gifted
  • Student_Type__NO_LABEL
  • Student_Type__Poverty
  • Student_Type__PreK
  • Student_Type__Special Education
  • Student_Type__Unspecified
  • Use__Business Services
  • Use__ISPD
  • Use__Instruction
  • Use__Leadership
  • Use__NO_LABEL
  • Use__O&M
  • Use__Pupil Services & Enrichment
  • Use__Untracked Budget Set-Aside

Submission values


Again, you must submit a probability for each label. Valid probabilities are in the range [0, 1].
Function__Aides Compensation Function__Career & Academic Counseling Function__Communications ... Use__O&M Use__Pupil Services & Enrichment Use__Untracked Budget Set-Aside
180042 0.027027 0.027027 0.027027 ... 0.125 0.125 0.125
28872 0.027027 0.027027 0.027027 ... 0.125 0.125 0.125
186915 0.027027 0.027027 0.027027 ... 0.125 0.125 0.125
412396 0.027027 0.027027 0.027027 ... 0.125 0.125 0.125
427740 0.027027 0.027027 0.027027 ... 0.125 0.125 0.125