Python package to translate between gdx (GAMS data) and pandas.

Install | Use | Uninstall

There are two main ways to use gdxpds. The first use case is the one that was initially supported: direct conversion between GDX files on disk and pandas DataFrames or a csv version thereof. The Version 1.0.0 rewrite intoduces a second style of use, that is, interfacing with GDX files and symbols via the gdxpds.gdx.GdxFile and gdxpds.gdx.GdxSymbol classes.

Direct Conversion | Backend Classes

The two primary points of reference for the direct conversion utilities are GDX files on disk and python dicts of {symbol_name: pandas.DataFrame}, where each pandas.DataFrame contains data for a single set, parameter, equation, or variable. For sets and parameters, the last column of the DataFrame is assumed to contain the value of the element, which for sets should be True, and for parameters should be a float (or one of the gdxpds.gdx.NUMPY_SPECIAL_VALUES). Equations and variables have additional 'value' columns, in particular a level, a marginal value, a lower bound, an upper bound, and a scale, as enumerated in gdxpds.gdx.GamsValueType. These values are all assumed to be found in the last five columns of the DataFrame, also see gdxpds.gdx.GAMS_VALUE_COLS_MAP.

The basic interface to convert from GDX to DataFrames is:

import gdxpds

gdx_file = 'C:\path_to_my_gdx\data.gdx'
dataframes = gdxpds.to_dataframes(gdx_file)
for symbol_name, df in dataframes.items():
    print("Doing work with {}.".format(symbol_name))

And vice-versa:

import gdxpds

# assume we have a DataFrame df with last column 'value'
data_ready_for_GAMS = { 'symbol_name': df }

gdx_file = 'C:\path_to_my_output_gdx\data_to_send_to_gams.gdx'
gdx = gdxpds.to_gdx(data_ready_for_GAMS, gdx_file)

Note that providing a gdx_file is optional, and the returned gdx is an object of type gdxpds.gdx.GdxFile.

Additional functions include:

• gdxpds.list_symbols
• gdxpds.to_dataframe (If the call to this method includes old_interface=False, then the return value will be a plain DataFrame, not a {'symbol_name': df} dict.)

The package also includes command line utilities for converting between GDX and CSV, see

python C:\your_python_path\Scripts\gdx_to_csv.py --help
python C:\your_python_path\Scripts\csv_to_gdx.py --help

The basic functionalities described above can also be achieved with direct use of the backend classes now available in gdxpds.gdx. To duplicate the GDX read functionality shown above one would write:

import gdxpds

gdx_file = 'C:\path_to_my_gdx\data.gdx'
with gdxpds.gdx.GdxFile(lazy_load=False) as f:
    f.read(gdx_file)
    for symbol in f:
        symbol_name = symbol.name
        df = symbol.dataframe
        print("Doing work with {}:\n{}".format(symbol_name,df.head()))

The backend especially gives more control over creating new data in GDX format. For example:

import gdxpds

out_file = 'my_new_gdx_data.gdx'
with gdxpds.gdx.GdxFile() as gdx:
    # Create a new set with one dimension
    gdx.append(gdxpds.gdx.GdxSymbol('my_set',gdxpds.gdx.GamsDataType.Set,dims=['u']))
    data = pds.DataFrame([['u' + str(i)] for i in range(1,11)])
    data['Value'] = True
    gdx[-1].dataframe = data
    # Create a new parameter with one dimension
    gdx.append(gdxpds.gdx.GdxSymbol('my_parameter',gdxpds.gdx.GamsDataType.Parameter,dims=['u']))
    data = pds.DataFrame([['u' + str(i), i*100] for i in range(1,11)],
                         columns=(gdx[-1].dims + gdx[-1].value_col_names))
    gdx[-1].dataframe = data
    gdx.write(out_file)

• Python 2.6 or higher 2.X; Python 3.4 or higher 3.X
• pandas (In general you will want the SciPy stack. Anaconda comes with it, or see my notes for Windows.)
• For Python versions < 3.4, enum34. Also uninstall the enum package if it is installed.
• psutil (optional--for monitoring memory use)
• pytest (optional--for running tests)
• GAMS Python bindings

  • See GAMS/win64/XX.X/apifiles/readme.txt on Windows, GAMS/gamsXX.X_osx_x64_64_sfx/apifiles/readme.txt on Mac, or /opt/gams/gamsXX.X_linux_x64_64_sfx/apifiles/readme.txt on Linux

  • Run the following for the correct version of the Python bindings

    python setup.py install

    or

    python setup.py build --build-base=/path/to/somwhere/you/have/write/access install

    with the latter being for the case when you can install packages into Python but don't have GAMS directory write access.

  • .../apifiles/Python/api/setup.py works for Python 2.7

  • For other versions of Python, especially 3.X, use .../apifiles/Python/api_XX/setup.py. For Python 3.X in particular you will need GAMS version >= 24.5.1 (Python 3.4, Windows and Linux), 24.7.4 (Python 3.4, Mac OS X), or >= 24.8.4 (Python 3.6)

pip install git+https://github.com/NREL/gdx-pandas.git@master

or

pip install git+https://github.com/NREL/[email protected]

Versions are listed at https://github.com/NREL/gdx-pandas/releases.

After installation, you can test the package using pytest:

pytest --pyargs gdxpds

If the tests fail due to permission IOErrors, apply chmod g+x and chmod a+x to the gdx-pandas/gdxpds/test folder.

pip uninstall gdxpds