Skip to main content

No project description provided

Project description

This package has two methods as specified below. The methods both calculate expected loss, one for single calculations and the other for full dataframes.

expectedloss_single Calculates Expected Loss for single values and takes: PD, LGD and EAD as parameters.

expectedloss_dataframe Calculates Expected Loss for a whole dataframe. The expected parameter is a dataframe. For the calculation to be successfull the dataframe needs to contain “pd”, “lgd” and “ead” as column names.

Please try and any feedback is very welcome for future releases!

Project details


Release history Release notifications | RSS feed

This version

1.1

Download files

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

Source Distribution

StevesExpectedLoss-1.1.tar.gz (13.5 kB view details)

Uploaded Source

Built Distribution

StevesExpectedLoss-1.1-py3-none-any.whl (13.6 kB view details)

Uploaded Python 3

File details

Details for the file StevesExpectedLoss-1.1.tar.gz.

File metadata

  • Download URL: StevesExpectedLoss-1.1.tar.gz
  • Upload date:
  • Size: 13.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.1

File hashes

Hashes for StevesExpectedLoss-1.1.tar.gz
Algorithm Hash digest
SHA256 21244e3b22c5159b5d5466738c5cf4458c9da809bb2e56e95e8c889b2f4492a2
MD5 b7794df58f6a347cde83aeb91fe3c881
BLAKE2b-256 ccb5c1953fda476a4d7fa000b0d612a82a73f954c1eb53abc90560b6d2e10d29

See more details on using hashes here.

File details

Details for the file StevesExpectedLoss-1.1-py3-none-any.whl.

File metadata

  • Download URL: StevesExpectedLoss-1.1-py3-none-any.whl
  • Upload date:
  • Size: 13.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.1

File hashes

Hashes for StevesExpectedLoss-1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 55e74249d369d377713e6743d13a1d1f406b7def7610f631d1d3ddd1f67458cd
MD5 241dfb62dc2f8663b40cb49b9fd1d50a
BLAKE2b-256 e8c97c0c02406812dbcb1591a5c4e15f1061dc3d86e27ad4acedf95efb8b8d52

See more details on using hashes here.

Supported by

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