Skip to main content

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

Project description

pyfpa

This project provides essential 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.

pyfpa leverages python's speed and power to address the challenges FP&A such as being able to keep all the versions of your data in one place, handling large data and data structures that are getting to big for excel (including consolidation and variance analysis), and not worrying about Excel link stability.

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
  • HTML interactive graphs
  • 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-0.0.9.tar.gz (18.6 kB view details)

Uploaded Source

Built Distribution

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

pyfpa-0.0.9-py3-none-any.whl (18.4 kB view details)

Uploaded Python 3

File details

Details for the file pyfpa-0.0.9.tar.gz.

File metadata

  • Download URL: pyfpa-0.0.9.tar.gz
  • Upload date:
  • Size: 18.6 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-0.0.9.tar.gz
Algorithm Hash digest
SHA256 8922f34de97fbe638f8f855a8b7824f309cd95de7206514e664ebeccf9ad3ea3
MD5 965371f8cd1ac93b1ea494ad7a67829b
BLAKE2b-256 6c393e93ddfb7dd82688cc320467baa0abcf94c42daa80e444f1089591fc051f

See more details on using hashes here.

File details

Details for the file pyfpa-0.0.9-py3-none-any.whl.

File metadata

  • Download URL: pyfpa-0.0.9-py3-none-any.whl
  • Upload date:
  • Size: 18.4 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-0.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 4a74c62ab0b410a461d05464e3623d8d2279a4e23e2a81947720552fadd0db7c
MD5 148baf86cd99385b8c034b93586cbdb9
BLAKE2b-256 26b0f12d90d962f63a93a40860f368339c08bdc423df111a961143bca442fe62

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