def from_custom_file(data_file, learn_options):
    # use semantics of when we load V2 data
    print "Loading inputs to predict from %s" % data_file
    data = pandas.read_csv(data_file)

    mandatory_columns = ['30mer', 'Target gene', 'Percent Peptide', 'Amino Acid Cut position']
    for col in mandatory_columns:
        assert col in data.columns, "inputs for prediction must include these columns: %s" % mandatory_columns

    Xdf = pandas.DataFrame(data)
    Xdf['30mercopy'] = Xdf['30mer']
    Xdf = Xdf.set_index(['30mer', 'Target gene'])
    Xdf['30mer'] = Xdf['30mercopy']
    Xdf.index.names = ['Sequence', 'Target']
    Xdf['drug']= [i % 'dummydrug%s' for i in range(Xdf.shape[0])]
    Xdf = Xdf.set_index('drug', append=True)

    Y = None
    gene_position = Xdf[['Percent Peptide', 'Amino Acid Cut position']]
    target_genes =  np.unique(Xdf.index.levels[1])

    learn_options = set_V2_target_names(learn_options)

    return Xdf, Y, gene_position, target_genes
dataset/ETHPy150Open MicrosoftResearch/Azimuth/azimuth/load_data.py/from_custom_file/swapped operands of `%`