Here are some examples (taken from sample BRCA data):
# Get all summaries in one pass
# NOTE: Currently, this is not paginated. Use `SummaryItemCounts` for the paginated, individual version.
phc.SummaryCounts.get_data_frame().info()
# Data columns (total 15 columns):
# # Column Non-Null Count Dtype
# --- ------ -------------- -----
# 0 summary 372 non-null object
# 1 code 160 non-null object
# 2 display 155 non-null object
# 3 patient_count 169 non-null float64
# 4 system 160 non-null object
# 5 count 368 non-null float64
# 6 media_type 4 non-null object
# 7 media_type_count 4 non-null float64
# 8 clinvar_significance 100 non-null object
# 9 gene 200 non-null object
# 10 population_pct 203 non-null float64
# 11 population_sample_count 203 non-null float64
# 12 sample_count 203 non-null float64
# 13 status 3 non-null object
# 14 test_type 3 non-null object
phc.SummaryOmicsCounts.get_data_frame()
# summary clinvar_significance gene population_pct population_sample_count sample_count status patient_count test_type
# 0 clinvar_significance Pathogenic PIK3CA 0.238384 990.0 236.0 NaN NaN NaN
# 1 clinvar_significance Pathogenic TP53 0.118182 990.0 117.0 NaN NaN NaN
# 2 copynumber_status NaN NaN 1.000000 2.0 2.0 amplification NaN NaN
# 3 copynumber_status NaN NaN 0.500000 2.0 1.0 loss NaN NaN
# 4 gene_variant NaN TP53 0.346465 990.0 343.0 NaN NaN NaN
# 5 gene_variant NaN PIK3CA 0.332323 990.0 329.0 NaN NaN NaN
# 6 sequence NaN NaN NaN NaN NaN NaN 1097.0 NaN
# 7 sequence NaN NaN NaN NaN NaN NaN 1.0 NaN
# 8 test NaN NaN NaN NaN NaN NaN 1090.0 TCGA RNAseq
# 9 test NaN NaN NaN NaN NaN NaN 1.0 GEM ExTra
phc.SummaryClinicalCounts.get_data_frame(match="fuzzy", system=["snomed.info", "loinc.org"])
# summary code display patient_count system count media_type media_type_count
# 0 procedure 406505007 modified radical mastectomy 322.0 http://snomed.info/sct 322.0 NaN NaN
# 1 procedure 392090004 other 272.0 http://snomed.info/sct 272.0 NaN NaN
# 2 observation 21975-8 Date of Last Contact 1094.0 http://loinc.org 1094.0 NaN NaN
# 3 medication 387420009 cytoxan 514.0 http://snomed.info/sct 523.0 NaN NaN
# 4 medication 372817009 doxorubicin+cyclophosphamid 364.0 http://snomed.info/sct 371.0 NaN NaN
# 5 condition 254837009 None 1086.0 http://snomed.info/sct 1086.0 NaN NaN
# 6 condition 82711006 Infiltrating duct carcinoma, NOS 778.0 http://snomed.info/sct 778.0 NaN NaN
# NOTE: Can also just pass "condition" here like other options in the SDK
phc.SummaryItemCounts.get_data_frame(summary=phc.Option.SummaryClinicalType.CONDITION)
# code code_count display patient_count system
# 0 254837009 1086 None 1086 http://snomed.info/sct
# 1 82711006 778 Infiltrating duct carcinoma, NOS 778 http://snomed.info/sct
# 2 89740008 201 Lobular carcinoma, NOS 201 http://snomed.info/sct
# The summary version of `get_codes` is available on Observation, Condition, and Procedure.
# Otherwise, it uses the FHIR search service implementation.
phc.Observation.get_codes(query="receptor")
# code code_count display patient_count system
# 0 85337-4 1048 Estrogen Receptor Status 1048 http://loinc.org
# 1 85339-0 1047 Progesterone Receptor Status 1047 http://loinc.org
# 2 49683-6 919 HER2/neu receptor status 919 http://loinc.org
Here are some examples (taken from sample BRCA data):