Skip to main content

Chainladder Package - P&C Loss Reserving package

Project description

PyPI version Python versions License Downloads Build Status codecov io Documentation Status

chainladder: Property and Casualty Loss Reserving in Python

Welcome! The chainladder package was built to be able to handle all of your actuarial needs in python. It consists of popular actuarial tools, such as triangle data manipulation, link ratios calculation, and IBNR estimates with both deterministic and stochastic models. We build this package so you no longer have to rely on outdated softwares and tools when performing actuarial pricing or reserving indications.

This package strives to be minimalistic in needing its own API. The syntax mimics popular packages pandas for data manipulation and scikit-learn for model construction. An actuary that is already familiar with these tools will be able to pick up this package with ease. You will be able to save your mental energy for actual actuarial work.

Chainladder is built by a group of volunteers, and we need YOUR help!

This package is written in Python, if you are looking for a similar package written in R, please visit chainladder.

Dedicated Documentation Site

We have a dedicated documentation website, where you can find installation instructions, tutorials, example galleries, sample datasets, API references, change log history, and more.

Visit Chainladder-Python on Read the Docs.

Contributors Working Group

We also have a Contributors Working Group that meets for one hour approximately every two weeks. We are part of the CAS volunteer groups and are supported by the CAS. If you are interested, you are welcome to join us through the Open-Source Projects Working Group.

We currently meet on Fridays 11:00am - Noon ET, but we periodically adjust meeting times to accommodate contributors across time zones around the globe. Our meetings are relaxed and collaborative, with discussions around milestones, package design ideas, open issues, and other behind-the-scenes work on GitHub.

We welcome contributors of all skill levels, including CAS members, its affiliate members, industry researchers, educators, students, and CAS candidates. To join us, you may respond to the CAS annual Volunteer Interest and Participation (VIP) Survey, reach out to a CAS staff persons (Heather Davis <hdavis@casact.org>, Elizabeth Smith <esmith@casact.org>), or the working group chair (Kenneth Hsu <kennethshsu@gmail.com>), and we will be happy to welcome you into the group.

Licenses

This package is released under Mozilla Public License 2.0.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

chainladder-0.9.2.tar.gz (1.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

chainladder-0.9.2-py3-none-any.whl (1.4 MB view details)

Uploaded Python 3

File details

Details for the file chainladder-0.9.2.tar.gz.

File metadata

  • Download URL: chainladder-0.9.2.tar.gz
  • Upload date:
  • Size: 1.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for chainladder-0.9.2.tar.gz
Algorithm Hash digest
SHA256 4ad774e7bcdbb407c13bcb34364c607c7ff780c0dfa53a31ced8ab4ade81441b
MD5 f09b6ce88760809636b12b9dcb0e45c6
BLAKE2b-256 04cc073e278fc91f4cf138b1416c5675b5e76317f627900bd991f3070e2667eb

See more details on using hashes here.

Provenance

The following attestation bundles were made for chainladder-0.9.2.tar.gz:

Publisher: pythonpublish.yml on casact/chainladder-python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file chainladder-0.9.2-py3-none-any.whl.

File metadata

  • Download URL: chainladder-0.9.2-py3-none-any.whl
  • Upload date:
  • Size: 1.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for chainladder-0.9.2-py3-none-any.whl
Algorithm Hash digest
SHA256 b685a9b848a1c0378a7b612464074e23adcb08a4b71f8cbe66c2ce91395d66d0
MD5 3d1259c03512f6f274ef8694dcfc143b
BLAKE2b-256 4e78038d5f224f47917c27d2e7f18df84e886462b585392cd126195a90d42fdc

See more details on using hashes here.

Provenance

The following attestation bundles were made for chainladder-0.9.2-py3-none-any.whl:

Publisher: pythonpublish.yml on casact/chainladder-python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page