add

make_data.py

@@ -153,8 +153,8 @@ def hospital():
     result = cursor.fetchall()
     db.close()
     tmp = pd.DataFrame(list(result))
-    name = ["merchant_id", "doctor_ad_money_30_days", "expand_rechange_amount_30", "service_pv_30",
-            "mexpert_pv_30", "organization_pv_30","doctor_discount_30_days"]
+    name = ["merchant_id", "doctor_ad_money_30_days","service_pv_30","mexpert_pv_30","organization_pv_30",
+            "doctor_discount_30_days"]
     tmp = tmp.rename(columns=dict(zip(list(range(len(name))), name)))
     print(tmp.head(6))
 
@@ -163,9 +163,9 @@ def hospital():
     df = pd.merge(df, tmp, on='merchant_id')
 
     for i in ["hospital_exposure_pv_30","service_exposure_pv_30","expert_exposure_pv_30",
-              "service_ctr_30","hospital_ctr_30","expert_ctr_30",
-              "doctor_ad_money_30_days", "service_pv_30",
-              "mexpert_pv_30", "organization_pv_30", "budan_payment_30_days","doctor_discount_30_days"]:
+              "service_ctr_30","hospital_ctr_30","expert_ctr_30","budan_payment_30_days",
+              "doctor_ad_money_30_days","service_pv_30","mexpert_pv_30","organization_pv_30",
+              "doctor_discount_30_days"]:
         df[i] = df[i].astype("float")
 
     df["all_exposure"] = df["hospital_exposure_pv_30"] + df["service_exposure_pv_30"] + df["expert_exposure_pv_30"]