def METHOD_NAME(*, resp, year, **_):
    """
    Convert response for calling url to pandas dataframe, begin parsing
    df into FBA format
    :param url: string, url
    :param resp: df, response from url call
    :param args: dictionary, arguments specified when running
        flowbyactivity.py ('year' and 'source')
    :return: pandas dataframe of original source data
    """
    df_legend = pd.io.excel.read_excel(io.BytesIO(resp.content),
                                       sheet_name='Legend')
    if year == '2002':
        df_raw = pd.io.excel.read_excel(io.BytesIO(resp.content),
                                        sheet_name='2002')
    elif year == '2007':
        df_raw = pd.io.excel.read_excel(io.BytesIO(resp.content),
                                        sheet_name='2007')
    else:
        df_raw = pd.io.excel.read_excel(io.BytesIO(resp.content),
                                        sheet_name='2012')
    for col_name in df_raw.columns:
        for i in range(len(df_legend)):
            if '_20' in df_legend.loc[i, "HUC8_1"]:
                legend_str = str(df_legend.loc[i, "HUC_8"])
                list = legend_str.split('_20')
                df_legend.loc[i, "HUC8_1"] = list[0]
            if col_name == df_legend.loc[i, "HUC8_1"]:
                df_raw = df_raw.rename(
                    columns={col_name: df_legend.loc[i, "HUC8 CODE"]})
    # use "melt" fxn to convert colummns into rows
    df = df_raw.melt(id_vars=["HUC8_1"],
                     var_name="name",
                     value_name="FlowAmount")
    df = df.rename(columns={"HUC8_1": "Location"})
    df_legend = df_legend.rename(columns={"HUC8 CODE": "name"})
    df_legend = name_and_unit_split(df_legend)
    df = pd.merge(df, df_legend, on="name")
    df = df.drop(columns=["HUC8_1", "name"])
    return df