Skip to main content

Leverage the power of Python for corporate finance and accounting functions.

Project description

pyfpa

[beta version 0.0.1]

This project provides basic Financial, Planning & Analysis functions in Python. It allows collecting data from Excel sheets and combining them into a multidimensional dataframe for easy slicing and dicing large amounts of data. The goal is to make an easier introduction into Python for analysts in corporate FP&A, accounting, investment banking, hedge fund and private equity.

While overpowered for most FP&A functions (Excel is a great tool), this package looks to leverage that power to address the challenges FP&A such as being able to keep all the verions of your data in one place, handling large data and data structures that's getting to big for excel (including consolidation and variance analysis), and not worrying about link problems.

The this project will allow you to:

  • Collect data from Excel files to build your own high dimensional data cube
  • Combine periodic reports to search for trends
  • Gather snapshots of data at different times to track changes
  • Map custom budget or actual reports to capture data and dimensions
  • Create a Golden Source repository for financial, operational, sales or any kind of data
  • Source and version control to keep track of which files are the basis for data
  • Easy slicing and dicing of data based on dimensions you define
  • Changing table data into record data for pivot tables
  • Dimension management to accomodate changes
  • Consolidation based on dimesions
  • Variance analysis
  • Pasting or saving back into Excel
  • Providing a basis to use all of Python's data science tools

Python, and especially Pandas, can be daunting for uses in FP&A, but does provide advantages:

  • Can handle and store large data and associated calculations
  • Faster calculation
  • Data will not mysteriously change due to links
  • No incorrect links
  • API connections to almost every database and software
  • Access to a greater amount of data science tools (statistical, AI)
  • Access to high-end charting and visualization tools
  • And all for free

Project details


Download files

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

Source Distribution

pyfpa-0.0.4.tar.gz (16.9 kB view details)

Uploaded Source

Built Distribution

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

pyfpa-0.0.4-py3-none-any.whl (16.6 kB view details)

Uploaded Python 3

File details

Details for the file pyfpa-0.0.4.tar.gz.

File metadata

  • Download URL: pyfpa-0.0.4.tar.gz
  • Upload date:
  • Size: 16.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.0 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5

File hashes

Hashes for pyfpa-0.0.4.tar.gz
Algorithm Hash digest
SHA256 ad8cacb795f885b251f0083cde84354422dfc319879ddb68fe3dd111de2eaf90
MD5 df936fecb8928cd28e98939ceb7c9d50
BLAKE2b-256 fe51aecc94137882cae5f89acc8e035962efe0246a078fb2da30210a1e7d9591

See more details on using hashes here.

File details

Details for the file pyfpa-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: pyfpa-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 16.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.0 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5

File hashes

Hashes for pyfpa-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 cbd21bfb7b281b75288105c1b7c8d28b9b4fa3558318859aa9e5a6c0412bcabe
MD5 f7202c268f415d75d93a6805cc9894f4
BLAKE2b-256 d73e6a836b15c461c9d45fffceee3910344ba471f318c8b65a267673b138c711

See more details on using hashes here.

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