def _download_study_clin(pdc_study_id):
    'Download PDC clinical data for a particular study.'
    clinical_query = (('\n    query {\n        clinicalPerStudy(pdc_study_id: "' + pdc_study_id) + '", acceptDUA: true) {\n            age_at_diagnosis, ajcc_clinical_m, ajcc_clinical_n, ajcc_clinical_stage, ajcc_clinical_t, ajcc_pathologic_m,\n            ajcc_pathologic_n, ajcc_pathologic_stage, ajcc_pathologic_t, ann_arbor_b_symptoms, ann_arbor_clinical_stage,\n            ann_arbor_extranodal_involvement, ann_arbor_pathologic_stage, best_overall_response, burkitt_lymphoma_clinical_variant,\n            case_id, case_submitter_id, cause_of_death, circumferential_resection_margin, classification_of_tumor, colon_polyps_history,\n            days_to_best_overall_response, days_to_birth, days_to_death, days_to_diagnosis, days_to_hiv_diagnosis, days_to_last_follow_up,\n            days_to_last_known_disease_status, days_to_new_event, days_to_recurrence, demographic_id, demographic_submitter_id,\n            diagnosis_id, diagnosis_submitter_id, disease_type, ethnicity, figo_stage, gender, hiv_positive, hpv_positive_type, hpv_status,\n            icd_10_code, iss_stage, last_known_disease_status, laterality, ldh_level_at_diagnosis, ldh_normal_range_upper,\n            lymphatic_invasion_present, lymph_nodes_positive, method_of_diagnosis, morphology, new_event_anatomic_site, new_event_type,\n            overall_survival, perineural_invasion_present, primary_diagnosis, primary_site, prior_malignancy, prior_treatment,\n            progression_free_survival, progression_free_survival_event, progression_or_recurrence, race, residual_disease,\n            site_of_resection_or_biopsy, status, synchronous_malignancy, tissue_or_organ_of_origin, tumor_cell_content, tumor_grade,\n            tumor_stage, vascular_invasion_present, vital_status, year_of_birth, year_of_death, year_of_diagnosis\n        }\n    }\n    ')
    result_json = _query_pdc(clinical_query)
    result_df = pd.DataFrame(result_json['data']['clinicalPerStudy'])
    return result_df
Download PDC clinical data for a particular study.
def _download_study_clin(pdc_study_id):
    
    clinical_query = (('\n    query {\n        clinicalPerStudy(pdc_study_id: "' + pdc_study_id) + '", acceptDUA: true) {\n            age_at_diagnosis, ajcc_clinical_m, ajcc_clinical_n, ajcc_clinical_stage, ajcc_clinical_t, ajcc_pathologic_m,\n            ajcc_pathologic_n, ajcc_pathologic_stage, ajcc_pathologic_t, ann_arbor_b_symptoms, ann_arbor_clinical_stage,\n            ann_arbor_extranodal_involvement, ann_arbor_pathologic_stage, best_overall_response, burkitt_lymphoma_clinical_variant,\n            case_id, case_submitter_id, cause_of_death, circumferential_resection_margin, classification_of_tumor, colon_polyps_history,\n            days_to_best_overall_response, days_to_birth, days_to_death, days_to_diagnosis, days_to_hiv_diagnosis, days_to_last_follow_up,\n            days_to_last_known_disease_status, days_to_new_event, days_to_recurrence, demographic_id, demographic_submitter_id,\n            diagnosis_id, diagnosis_submitter_id, disease_type, ethnicity, figo_stage, gender, hiv_positive, hpv_positive_type, hpv_status,\n            icd_10_code, iss_stage, last_known_disease_status, laterality, ldh_level_at_diagnosis, ldh_normal_range_upper,\n            lymphatic_invasion_present, lymph_nodes_positive, method_of_diagnosis, morphology, new_event_anatomic_site, new_event_type,\n            overall_survival, perineural_invasion_present, primary_diagnosis, primary_site, prior_malignancy, prior_treatment,\n            progression_free_survival, progression_free_survival_event, progression_or_recurrence, race, residual_disease,\n            site_of_resection_or_biopsy, status, synchronous_malignancy, tissue_or_organ_of_origin, tumor_cell_content, tumor_grade,\n            tumor_stage, vascular_invasion_present, vital_status, year_of_birth, year_of_death, year_of_diagnosis\n        }\n    }\n    ')
    result_json = _query_pdc(clinical_query)
    result_df = pd.DataFrame(result_json['data']['clinicalPerStudy'])
    return result_df