Generates, filters, parses, and cleans data regarding the financial disclosures of judges in the American Judicial System

Overview

This repository contains code that gets data regarding financial disclosures from the Court Listener API

  • main.py: contains driver code that interacts with all the other files. Only file that should be run. When run it will grab all the data and populate output.csv with it
  • auth_token.py: Reads API authentication token.
  • AUTH_TOKEN.txt: Contains API authentication token. Obtain yours from here and paste it into this file
  • fields.py: contains the code that grabs all the fields from every disclosure
  • lookups.py: contains some extra lookup tables (aside form the ones embedded in fields.py) for the values returned from the API
  • utils.py: contains some utility functions
  • requirements.txt: contains the list of dependencies used. Install them by running pip install -r requirements.txt
  • README.txt: readme in txt format

Overview

Every year judges file a financial disclosure form as mandated by law. Courtlistener parses these forms which are PDFs into their database. Here is an example of one of the unederlying forms that will help me explain what every row in our data is: https://storage.courtlistener.com/us/federal/judicial/financial-disclosures/9529/patricia-a-sullivan-disclosure.2019.pdf Disclosures are seperated into certain categories, such as positions, or investments. Each individual listing under a certain type of disclosure, is a row in our data. So if you look at that PDF, Member and Officer at Board of Directors of Roger Williams University School of Law, would be the basis for one row. If you scroll down to investments, MFS Investment Management (Educational Funds) (H), would also be the basis for one row. For that row, the fields listed below under Disclosure Fields -> Investments will all be filled out (unless they are not present in the courtlistner database). The Common Fields and Person Fields will also be filled out. Person fields are fields unique to the judge, and common fields unique to the report. So for the two example rows, the common fields and person fields would remain constant (as the judge and report are the same), but the disclosure fields will be different. For the first one, the fields under Disclosure Fields -> Positions will be filled out, with the rest of the disclosure fields empty, and for the second one the fields under Disclosure Fields -> Investments would be filled out.

=============
Common Fields
=============



sha1: SHA1 hash of the generated PDF
is_amended: Is disclosure amended?
Disclosure PDF: PDF of the original filed disclosure
Year Disclosed: Date of judicial agreement.
report_type: Financial Disclosure report type
addendum_redacted: Is the addendum partially or completely redacted?
Disclosure Type: Type of the disclosure, (investments, debts, etc)

=============
Disclosure Fields
=============


Note: Depending on the Disclosure Type field above, the corresponding fields will be filled in for the row


agreements:
        date_raw: Date of judicial agreement.
        parties_and_terms: Parties and terms of agreement (ex. Board Member NY Ballet)
        redacted: Does the agreement row contain redaction(s)?
        financial_disclosure: The financial disclosure associated with this agreement.
        id: ID of the record.
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

debts:
        creditor_name: Liability/Debt creditor
        description: Description of the debt
        value_code: Form code for the value of the judicial debt, substituted with the numerical values of the range.
        value_code_max: The maximum value of the value_code.
        redacted: Does the debt row contain redaction(s)?
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

gifts:
        source: Source of the judicial gift. (ex. Alta Ski Area).
        description: Description of the gift (ex. Season Pass).
        value: Value of the judicial gift, (ex. $1,199.00)
        redacted: Does the gift row contain redaction(s)?
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

investments:
        page_number: The page number the investment is listed on.  This is used to generate links directly to the PDF page.
        description: Name of investment (ex. APPL common stock).
        redacted: Does the investment row contains redaction(s)?
        income_during_reporting_period_code: Increase in investment value - as a form code. Substituted with the numerical values of the range.
        income_during_reporting_period_code_max: Maximum value of income_during_reporting_period_code.
        income_during_reporting_period_type: Type of investment (ex. Rent, Dividend). Typically standardized but not universally.
        gross_value_code: Investment total value code at end of reporting period as code (ex. J (1-15,000)). Substituted with the numerical values of the range.
        gross_value_code_max: Maximum value of the gross_value_code.
        gross_value_method: Investment valuation method code (ex. Q = Appraisal)
        transaction_during_reporting_period: Transaction of investment during reporting period (ex. Buy, Sold)
        transaction_date_raw: Date of the transaction, if any (D2)
        transaction_date: Date of the transaction, if any (D2)
        transaction_value_code: Transaction value amount, as form code (ex. J (1-15,000)). Substituted with the numerical values of the range.
        transaction_value_code_max: Maximum value of transaction_value_code.
        transaction_gain_code: Gain from investment transaction if any (ex. A (1-1000)). Substituted with the numerical values of the range.
        transaction_gain_code_max: Maximum value of transaction_gain_code.
        transaction_partner: Identity of the transaction partner
        has_inferred_values: If the investment name was inferred during extraction. This is common because transactions usually list the first purchase of a stock and leave the name value blank for subsequent purchases or sales.
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

non_investment_incomes:
        date_raw: Date of non-investment income (ex. 2011).
        source_type: Source and type of non-investment income for the judge (ex. Teaching a class at U. Miami).
        income_amount: Amount earned by judge, often a number, but sometimes with explanatory text (e.g. 'Income at firm: $xyz').
        redacted: Does the non-investment income row contain redaction(s)?
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

positions:
        non judiciary position: Position title (ex. Trustee).
        organization_name: Name of organization or entity (ex. Trust #1).
        redacted: Does the position row contain redaction(s)?
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown

reimbursements:
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown
        source: Source of the reimbursement (ex. FSU Law School).
        date_raw: Dates as a text string for the date of reimbursements. This is often conference dates (ex. June 2-6, 2011). 
        location: Location of the reimbursement (ex. Harvard Law School, Cambridge, MA).
        purpose: Purpose of the reimbursement (ex. Baseball announcer).
        items_paid_or_provided: Items reimbursed (ex. Room, Airfare).
        redacted: Does the reimbursement contain redaction(s)?

spouse_incomes:
        id: ID of the record
        date_created: The moment when the item was created.
        date_modified: The last moment when the item was modified. A value in year 1750 indicates the value is unknown
        source_type: Source and type of income of judicial spouse (ex. Salary from Bank job).
        redacted: Does the spousal-income row contain redaction(s)?
        date_raw: Date of spousal income (ex. 2011).


=============
Person Fields
=============


fjc_id: The ID of a judge as assigned by the Federal Judicial Center.
Date of Birth: The date of birth for the person
name_last: The last name of this person
political_affiliations: Political affiliations for the judge. Variable length so combined by a comma
Death Country: The country where the person died.
Birth City: The city where the person was born.
name_suffix: Any suffixes that this person's name may have
aba_ratings: American Bar Association Ratings. Variable length so combined by a comma
name_first: The first name of this person.
Death State: The state where the person died.
sources: Sources about the person. Variable length so combined with a newline
Birth Country: The country where the person was born.
cl_id: A unique identifier for judge, also indicating source of data.
gender: The person's gender
name_middle: The middle name or names of this person
ftm_eid: The ID of a judge as assigned by the Follow the Money database.
Death City: The city where the person died.
positions: Positions of person. Variable length so combined with a newline
ftm_total_received: The amount of money received by this person and logged by Follow the Money.
Date of Death: The date of death for the person
religion: The religion of a person
educations: Educations of the person. Variable length so combined by a comma
bachelor school: Name of the school from which they got their Bachelor's degree, and/or Bachelor's of Law degree. Variable length so combined by a comma
juris doctor school: name of the school from which they got their jusris doctor degree. their Bachelor's degree, and/or Bachelor's of Law degree. Variable length so combined by a comma
race: Race of the person. Variable length so combined by a comma
Birth State: The state where the person was born.


Owner
Ali Rastegar
Hi
Ali Rastegar
Python For Finance Cookbook - Code Repository

Python For Finance Cookbook - Code Repository

Packt 544 Dec 25, 2022
Variable Transformer Calculator

✠ VASCO - VAriable tranSformer CalculatOr Software que calcula informações de transformadores feita para a matéria de "Conversão Eletromecânica de Ene

Arthur Cordeiro Andrade 2 Feb 12, 2022
A comprehensive and FREE Online Python Development tutorial going step-by-step into the world of Python.

FREE Reverse Engineering Self-Study Course HERE Fundamental Python The book and code repo for the FREE Fundamental Python book by Kevin Thomas. FREE B

Kevin Thomas 7 Mar 19, 2022
A simple flask application to collect annotations for the Turing Change Point Dataset, a benchmark dataset for change point detection algorithms

AnnotateChange Welcome to the repository of the "AnnotateChange" application. This application was created to collect annotations of time series data

The Alan Turing Institute 16 Jul 21, 2022
Valentine-with-Python - A Python program generates an animation of a heart with cool texts of your loved one

Valentine with Python Valentines with Python is a mini fun project I have coded.

Niraj Tiwari 4 Dec 31, 2022
Obmovies - A short guide on setting up the system and environment dependencies required for ob's Movies database

Obmovies - A short guide on setting up the system and environment dependencies required for ob's Movies database

1 Jan 04, 2022
Types that make coding in Python quick and safe.

Type[T] Types that make coding in Python quick and safe. Type[T] works best with Python 3.6 or later. Prior to 3.6, object types must use comment type

Contains 17 Aug 01, 2022
Code for our SIGIR 2022 accepted paper : P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning

P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas

14 Jan 04, 2023
A tool that allows for versioning sites built with mkdocs

mkdocs-versioning mkdocs-versioning is a plugin for mkdocs, a tool designed to create static websites usually for generating project documentation. mk

Zayd Patel 38 Feb 26, 2022
A Python library for setting up projects using tabular data.

A Python library for setting up projects using tabular data. It can create project folders, standardize delimiters, and convert files to CSV from either individual files or a directory.

0 Dec 13, 2022
✨ Real-life Data Analysis and Model Training Workshop by Global AI Hub.

🎓 Data Analysis and Model Training Course by Global AI Hub Syllabus: Day 1 What is Data? Multimedia Structured and Unstructured Data Data Types Data

Global AI Hub 71 Oct 28, 2022
Manage your WordPress installation directly from SublimeText SideBar and Command Palette.

WordpressPluginManager Manage your WordPress installation directly from SublimeText SideBar and Command Palette. Installation Dependencies You will ne

Art-i desenvolvimento 1 Dec 14, 2021
SCTYMN is a GitHub repository that includes some simple scripts(currently only python scripts) that can be useful.

Simple Codes That You Might Need SCTYMN is a GitHub repository that includes some simple scripts(currently only python scripts) that can be useful. In

CodeWriter21 2 Jan 21, 2022
Swagger Documentation Generator for Django REST Framework: deprecated

Django REST Swagger: deprecated (2019-06-04) This project is no longer being maintained. Please consider drf-yasg as an alternative/successor. I haven

Marc Gibbons 2.6k Jan 03, 2023
A Python validator for SHACL

pySHACL A Python validator for SHACL. This is a pure Python module which allows for the validation of RDF graphs against Shapes Constraint Language (S

RDFLib 187 Dec 29, 2022
A clean customizable documentation theme for Sphinx

A clean customizable documentation theme for Sphinx

Pradyun Gedam 1.5k Jan 06, 2023
A complete kickstart devcontainer repository for python3

A complete kickstart devcontainer repository for python3

Viktor Freiman 3 Dec 23, 2022
Speed up Sphinx builds by selectively removing toctrees from some pages

Remove toctrees from Sphinx pages Improve your Sphinx build time by selectively removing TocTree objects from pages. This is useful if your documentat

Executable Books 8 Jan 04, 2023
Żmija is a simple universal code generation tool.

Żmija Żmija is a simple universal code generation tool. It is intended to be used as a means to generate code that is both efficient and easily mainta

Adrian Samoticha 2 Nov 23, 2021
Sphinx-performance - CLI tool to measure the build time of different, free configurable Sphinx-Projects

CLI tool to measure the build time of different, free configurable Sphinx-Projec

useblocks 11 Nov 25, 2022