Scientific Literature

aircraftdetective.processing.literature ¶

overwrite_with_literature_data ¶

overwrite_with_literature_data(df)

ABC

Source code in aircraftdetective/processing/literature.py

def overwrite_with_literature_data(
    df: pd.DataFrame
) -> pd.DataFrame:
    r"""
    ABC
    """
    return

process_data_babikian_figures ¶

process_data_babikian_figures(
    path_xlsx_babikian=PATH_ZENODO_BABIKIAN_FILE,
)

Processes the Babikian et al. (2002) aircraft efficiency data from the provided Excel file.

Notes

With no parameters passed, the function will download the relevant Excel file from the relevant Zenodo repository.

References

Babikian et al. (2002)

Parameters:

Name	Type	Description	Default
`path_xlsx_babikian`	`str`	The path or URL to the Excel file containing the Babikian et al. (2002) aircraft efficiency data. Default is the Zenodo URL.	`PATH_ZENODO_BABIKIAN_FILE`

Returns:

Type	Description
`DataFrame`	`pint-pandas` DataFrame containing the Babikian et al. (2002) aircraft efficiency data.

Source code in aircraftdetective/processing/literature.py

def process_data_babikian_figures(
    path_xlsx_babikian: str = PATH_ZENODO_BABIKIAN_FILE,
) -> pd.DataFrame:
    r"""
    Processes the Babikian et al. (2002) aircraft efficiency data from the provided Excel file.

    Notes
    -----
    With no parameters passed, the function will download the relevant Excel file 
    from the relevant [Zenodo repository](https://doi.org/10.5281/zenodo.14560913).


    See Also
    --------
    [Figure data from Babikian et al. (2002) in Excel format on Zenodo](https://doi.org/10.5281/zenodo.14560913)

    References
    -----------
    [Babikian et al. (2002)](https://doi.org/10.1016/S0969-6997(02)00020-0)

    Parameters
    ----------
    path_xlsx_babikian : str, optional
        The path or URL to the Excel file containing the Babikian et al. (2002) aircraft efficiency data. Default is the Zenodo URL.

    Returns
    -------
    pd.DataFrame
        [`pint-pandas`](https://pint-pandas.readthedocs.io/en/latest/) DataFrame containing the Babikian et al. (2002) aircraft efficiency data.
    """
    df = pd.read_excel(
        io=path_xlsx_babikian,
        sheet_name='Data (Figure 2)',
        header=[0,1],
        index_col=None,
        engine='openpyxl',
    )
    df = df.pint.quantify(level=-1)
    df = df[df['Aircraft Designation'].notna() & (df['Aircraft Designation'] != '???')]
    df.drop(
        columns=
        [
            'Year',
            'Aircraft Type',
            'Source',
            'Source Section',
            'Comment'
        ],
    inplace=True)
    return df

process_data_weinold_database ¶

process_data_weinold_database(
    sheet_name="Raw Data",
    path_xlsx_acftdb=PATH_ZENODO_AIRCRAFT_DATABASE_FILE,
)

Processes the Weinold (2023) aircraft database from the provided Excel file.

Notes

With no parameters passed, the function will download the relevant Excel file from the relevant Zenodo repository.

Parameters:

Name	Type	Description	Default
`sheet_name`	`str`	The sheet name to read from the Excel file. Options are 'Raw Data' or 'Literature Data'. Default is 'Raw Data'.	`'Raw Data'`
`path_xlsx_acftdb`	`str`	The path or URL to the Excel file containing the aircraft database. Default is the Zenodo URL.	`PATH_ZENODO_AIRCRAFT_DATABASE_FILE`

Returns:

Type	Description
`DataFrame`	`pint-pandas` DataFrame containing the Weinold (2023) aircraft database.

Source code in aircraftdetective/processing/literature.py

def process_data_weinold_database(
    sheet_name: str = 'Raw Data',
    path_xlsx_acftdb: str = PATH_ZENODO_AIRCRAFT_DATABASE_FILE,
) -> pd.DataFrame:
    r"""
    Processes the Weinold (2023) aircraft database from the provided Excel file.

    Notes
    -----
    With no parameters passed, the function will download the relevant Excel file 
    from the relevant [Zenodo repository](https://doi.org/10.5281/zenodo.14382100).

    See Also
    --------
    [Weinold (2023) aircraft database in Excel format on Zenodo](https://doi.org/10.5281/zenodo.14382100)

    Parameters
    ----------
    sheet_name : str, optional
        The sheet name to read from the Excel file. Options are 'Raw Data' or 'Literature Data'. Default is 'Raw Data'.
    path_xlsx_acftdb : str, optional
        The path or URL to the Excel file containing the aircraft database. Default is the Zenodo URL.

    Returns
    -------
    pd.DataFrame
        [`pint-pandas`](https://pint-pandas.readthedocs.io/en/latest/) DataFrame containing the Weinold (2023) aircraft database.
    """
    if sheet_name not in ['Raw Data', 'Literature Data']:
        raise NotImplementedError("Only 'Raw Data' and 'Literature Data' sheets areavailable.")

    df = pd.read_excel(
        io=path_xlsx_acftdb,
        sheet_name=sheet_name,
        header=[0,1],
        engine='openpyxl'
    )
    df = df.pint.quantify(level=-1)
    return df