def create_norm_peptide_column_if_needed(row_meta_df, gcp_normalization_peptide_field, gcp_normalization_peptide_id):
    """If it doesn't already exist, create a new column indicating the norm
    peptide for each probe.

    Modifies row_meta_df in-place.

    Args:
        row_meta_df (pandas df):
        gcp_normalization_peptide_field (string): metadata field in
            GCT that indicates which norm peptide to use for each probe
        gcp_normalization_peptide_id (string): if
            gcp_normalization_peptide_field not in the GCT, a new column will
            be created and filled with just this peptide_id

    Returns:
        None

    """
    # If gcp_normalization_peptide_field is already in the row metadata, we'll
    # just use it
    if gcp_normalization_peptide_field not in row_meta_df.columns.values:

        assert gcp_normalization_peptide_id is not None, (
            "gcp_normalization_peptide_field not present in metadata headers, " +
            "so gcp_normalization_peptide_id must not be None. " +
            "gcp_normalization_peptide_field: {}, " +
            "gcp_normalization_peptide_id: {}").format(
            gcp_normalization_peptide_field, gcp_normalization_peptide_id)

        # Otherwise, create a new column and fill it with gcp_normalization_peptide_id
        row_meta_df[gcp_normalization_peptide_field] = gcp_normalization_peptide_id

    return None