def send_request(**kwargs):
    """Return a data frame from a web service request to cBio portal.

    Sends a web service requrest to the cBio portal with arguments given in
    the dictionary data and returns a Pandas data frame on success.

    More information about the service here:
    http://www.cbioportal.org/web_api.jsp

    Parameters
    ----------
    kwargs : dict
        A dict of parameters for the query. Entries map directly to web service
        calls with the exception of the optional 'skiprows' entry, whose value
        is used as the number of rows to skip when reading the result data
        frame.

    Returns
    -------
    df : pandas.DataFrame
        Response from cBioPortal as a Pandas DataFrame.
    """
    skiprows = kwargs.pop('skiprows', None)
    res = requests.get(cbio_url, params=kwargs)
    if res.status_code == 200:
        # Adaptively skip rows based on number of comment lines
        if skiprows == -1:
            lines = res.text.split('\n')
            skiprows = 0
            for line in lines:
                if line.startswith('#'):
                    skiprows += 1
                else:
                    break
        csv_StringIO = StringIO(res.text)
        df = pandas.read_csv(csv_StringIO, sep='\t', skiprows=skiprows)
        return df
    else:
        logger.error('Request returned with code %d' % res.status_code)
Return a data frame from a web service request to cBio portal.

    Sends a web service requrest to the cBio portal with arguments given in
    the dictionary data and returns a Pandas data frame on success.

    More information about the service here:
    http://www.cbioportal.org/web_api.jsp

    Parameters
    ----------
    kwargs : dict
        A dict of parameters for the query. Entries map directly to web service
        calls with the exception of the optional 'skiprows' entry, whose value
        is used as the number of rows to skip when reading the result data
        frame.

    Returns
    -------
    df : pandas.DataFrame
        Response from cBioPortal as a Pandas DataFrame.