Update app.py

app.py

@@ -111,7 +111,7 @@ def generate_breast_cancer_data(num_patients):
         treatment.append(treat)
 
     breast_cancer_data = {
-        "Patient ID": primary_keys,
+        "PRIMARY_PERSON_KEY": primary_keys,
         "Age": ages,
         "Menopausal Status": menopausal_status,
         "Tumor Size (cm)": tumor_sizes,
@@ -134,8 +134,8 @@ def generate_breast_cancer_data(num_patients):
 # Function to generate Members from BreastCancer
 def generate_members_from_breast_cancer(breast_cancer_df):
     return pd.DataFrame({
-        "MEMBER_ID": breast_cancer_df["Patient ID"],
-        "PRIMARY_PERSON_KEY": breast_cancer_df["Patient ID"],
+        "MEMBER_ID": breast_cancer_df["PRIMARY_PERSON_KEY"],
+        "PRIMARY_PERSON_KEY": breast_cancer_df["PRIMARY_PERSON_KEY"],
         "MEM_GENDER": ["F"] * len(breast_cancer_df),
         "MEM_ETHNICITY": np.random.choice(["Hispanic", "Non-Hispanic", None], len(breast_cancer_df)),
         "MEM_RACE": np.random.choice(["White", "Black", "Asian", None], len(breast_cancer_df)),
@@ -146,7 +146,7 @@ def generate_members_from_breast_cancer(breast_cancer_df):
 # Function to generate Enrollments from BreastCancer
 def generate_enrollments_from_breast_cancer(breast_cancer_df):
     return pd.DataFrame({
-        "PRIMARY_PERSON_KEY": breast_cancer_df["Patient ID"],
+        "PRIMARY_PERSON_KEY": breast_cancer_df["PRIMARY_PERSON_KEY"],
         "MEM_STAT": np.random.choice(["ACTIVE", "INACTIVE"], len(breast_cancer_df)),
         "PAYER_LOB": np.random.choice(["MEDICAID", "COMMERCIAL", "MEDICARE"], len(breast_cancer_df)),
         "PAYER_TYPE": np.random.choice(["PPO", "HMO"], len(breast_cancer_df)),
@@ -177,7 +177,7 @@ if st.button("Generate Data"):
     breast_cancer_df = generate_breast_cancer_data(num_patients)
     members_df = generate_members_from_breast_cancer(breast_cancer_df)
     enrollments_df = generate_enrollments_from_breast_cancer(breast_cancer_df)
-    services_df = generate_services(num_services, breast_cancer_df["Patient ID"].tolist())
+    services_df = generate_services(num_services, breast_cancer_df["PRIMARY_PERSON_KEY"].tolist())
 
     # Display and download data
     st.subheader("Breast Cancer Data")