adds great expectations metabolomics example and data

gx_metabolomics.py

@@ -0,0 +1,94 @@
+import great_expectations as gx
+from great_expectations.data_context import FileDataContext
+
+context = FileDataContext.create(project_root_dir="great_expectations")
+
+from expectations.expect_column_values_to_have_list_length import (
+    ExpectColumnValuesToHaveListLength,
+)
+
+test_dataset = "./metabolomics.json"
+context = gx.get_context()
+validator = context.sources.pandas_default.read_json(test_dataset)
+
+# ad_diagnosis_p_value
+validator.expect_column_values_to_be_of_type("ad_diagnosis_p_value", "list")
+validator.expect_column_values_to_not_be_null("ad_diagnosis_p_value")
+# for custom and experimental expectations you have to pass args as kwargs
+validator.expect_column_values_to_have_list_length(
+    column="ad_diagnosis_p_value", list_length=1
+)
+
+# associated gene name
+validator.expect_column_values_to_be_of_type("associated_gene_name", "str")
+validator.expect_column_values_to_not_be_null("associated_gene_name")
+validator.expect_column_value_lengths_to_be_between(
+    "associated_gene_name", min_value=1, max_value=25
+)
+# allows all alphanumeric characters, underscores, periods, and dashes
+validator.expect_column_values_to_match_regex(
+    "associated_gene_name", "^[A-Za-z0-9_.-]+$"
+)
+
+# association p
+validator.expect_column_values_to_be_of_type("association_p", "float")
+validator.expect_column_values_to_not_be_null("association_p")
+validator.expect_column_values_to_be_between("association_p", min_value=0, max_value=1)
+
+# ensembl gene id
+validator.expect_column_values_to_be_of_type("ensembl_gene_id", "str")
+validator.expect_column_values_to_not_be_null("ensembl_gene_id")
+validator.expect_column_value_lengths_to_equal("ensembl_gene_id", 15)
+# checks format and allowed chatacters
+validator.expect_column_values_to_match_regex("ensembl_gene_id", "^ENSG\d{11}$")
+validator.expect_column_values_to_be_unique("ensembl_gene_id")
+
+# gene_wide_p_threshold_1kgp
+validator.expect_column_values_to_be_of_type("gene_wide_p_threshold_1kgp", "float")
+validator.expect_column_values_to_not_be_null("gene_wide_p_threshold_1kgp")
+validator.expect_column_values_to_be_between(
+    "gene_wide_p_threshold_1kgp", min_value=0, max_value=0.05
+)
+
+# metabolite full name
+validator.expect_column_values_to_be_of_type("metabolite_full_name", "str")
+validator.expect_column_values_to_not_be_null("metabolite_full_name")
+validator.expect_column_value_lengths_to_be_between(
+    "metabolite_full_name", min_value=1, max_value=25
+)
+# allows all alphanumeric characters, dashes, parentheses, hyphens and spaces
+validator.expect_column_values_to_match_regex(
+    "metabolite_full_name", "^[A-Za-z0-9\s\-:.()+]+$"
+)
+
+# metabolite ID
+validator.expect_column_values_to_be_of_type("metabolite_id", "str")
+validator.expect_column_values_to_not_be_null("metabolite_id")
+validator.expect_column_value_lengths_to_be_between(
+    "metabolite_id", min_value=1, max_value=15
+)
+# allows all alphanumeric characters and periods
+validator.expect_column_values_to_match_regex("metabolite_id", "^[A-Za-z0-9.]+$")
+
+# n_per_group
+validator.expect_column_values_to_be_of_type("n_per_group", "list")
+validator.expect_column_values_to_not_be_null("n_per_group")
+validator.expect_column_values_to_have_list_length(column="n_per_group", list_length=2)
+
+# transposed_boxplot_stats
+validator.expect_column_values_to_be_of_type("transposed_boxplot_stats", "list")
+validator.expect_column_values_to_not_be_null("transposed_boxplot_stats")
+validator.expect_column_values_to_have_list_length(
+    column="transposed_boxplot_stats", list_length=2
+)
+
+# save expectation suite and run checkpoint
+validator.save_expectation_suite()
+checkpoint = context.add_or_update_checkpoint(
+    name="agora-test-checkpoint",
+    validator=validator,
+)
+checkpoint_result = checkpoint.run()
+
+# generate and open report
+context.view_validation_result(checkpoint_result)