Metadata-Version: 2.1
Name: moneypandas
Version: 0.9.4
Summary: Money type for pandas
Home-page: https://github.com/flaxandteal/moneypandas
Author: Phil Weir (moneypandas tweaks), Tom Augspurger (cyberpandas)
Author-email: phil.weir@flaxandteal.co.uk
License: BSD
Description: # Moneypandas
        
        Moneypandas is a prototype fork of Cyberpandas for currency, using the `money` library. Even this README is shamelessly purloigned, with thanks to Tom Augspurger and the ContinuumIO team.
        
        This package provides support for storing currency data inside a pandas DataFrame using pandas' [Extension Array Interface](http://pandas-docs.github.io/pandas-docs-travis/extending.html#extension-types)
        
        
        ## Set Up Dev Environment
        
        Run `pipenv shell` or another Python3 virtual envirnonment.
        
        Run `python3 setup.py develop`
        
        The env should be set up. Run `python3 examples/three_currency.py` to check.
        
        ## Contributing (For new open source contributers!)
        
        Clone this repo using `SSH` or `HTTPS`
        
        For any changes, do `git checkout -b [feature/bug][description-of-issue]` to create a new branch.
        
        Once your changes are made, `git add [file-name]`. Add each file individually.
        
        Run `git status` to make sure all the files you want are added to this commit.
        
        Do `git commit -m "A message describing what changes you made, and why, possible bugs, and what you want to do"`. This will make it easier to refer back to in future.
        
        Run `git push -u origin [branch-name]`. If there have been no issues then a pull request should be open. Follow the link that was returned in the console to complete the PR.
        
        
        ___
        
        ## Example
        
        ```python
        In [1]: from moneypandas import MoneyArray
        
        In [2]: import pandas as pd
        
        In [3]: df = pd.DataFrame({"money": MoneyArray(['1284 EUR', '121 EUR', '€14'])})
        
        In [4]: df
        Out[4]:
                  money
        0  EUR 1,284.00
        1    EUR 121.00
        2     EUR 14.00
        ```
        
        For more examples, including summing and converting mixed-currency columns, see the `examples` folder.
        
        (note: not yet tested with Conda, only setuptools/pipenv)
        
        To efficiently perform operations, aggregation is done per currency first, and then XMoney used to do necessary operations on the output aggregates.
        
        Currency conversion of a Series only uses XMoney and conversion where currencies mismatch, so converting a column mostly of BBBs, with a few AAAs, should scale according to the number of AAAs.
        
        ## TODO
        
        * implement more reduce functions
        * testing for arithmetic
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
