add

make_data.py

@@ -93,12 +93,10 @@ def hospital():
     sql = "select api.id," \
           "h.hospital_id,h.hospital_exposure_pv_30,h.service_exposure_pv_30,h.expert_exposure_pv_30," \
           "h.service_ctr_30,h.hospital_ctr_30,h.expert_ctr_30," \
-          "b.merchant_id,budan.budan_payment_30_days " \
+          "b.merchant_id " \
           "from api_doctor api left join statistic_hospital_rank_factor h on api.hospital_id = h.hospital_id " \
           "left join hippo_merchantrelevance b on api.id = b.doctor_id " \
-          "left join al_meigou_service_smart_rank_budan_payment budan on b.merchant_id = budan.merchant_id " \
-          "where api.doctor_type = 1 and h.date = '{}' " \
-          "and budan.stat_date = '{}';".format(date_str, date_tmp)
+          "where api.doctor_type = 1 and h.date = '{}';".format(date_str)
 
     db = pymysql.connect(host='172.16.30.143', port=3306, user='work', passwd='BJQaT9VzDcuPBqkd', db='zhengxing')
     cursor = db.cursor()
@@ -106,8 +104,7 @@ def hospital():
     result = cursor.fetchall()
     df = pd.DataFrame(list(result))
     name = ["doctor_id","hospital_id","hospital_exposure_pv_30","service_exposure_pv_30",
-            "expert_exposure_pv_30","service_ctr_30","hospital_ctr_30","expert_ctr_30","merchant_id",
-            "budan_payment_30_days"]
+            "expert_exposure_pv_30","service_ctr_30","hospital_ctr_30","expert_ctr_30","merchant_id"]
 
     df = df.rename(columns=dict(zip(list(range(len(name))), name)))
 
@@ -130,7 +127,7 @@ 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","budan_payment_30_days",
+              "service_ctr_30","hospital_ctr_30","expert_ctr_30",
               "doctor_discount_30_days","service_pv_30","mexpert_pv_30","organization_pv_30",
               "expand_rechange_amount_30"]:
         df[i] = df[i].astype("float")
@@ -163,7 +160,7 @@ def hospital():
 
     columns = ["doctor_id","score","ctr","commission","cpt","hospital_id","hospital_exposure_pv_30",
                "service_exposure_pv_30","expert_exposure_pv_30",
-              "service_ctr_30","hospital_ctr_30","expert_ctr_30","merchant_id","budan_payment_30_days",
+              "service_ctr_30","hospital_ctr_30","expert_ctr_30","merchant_id",
               "doctor_discount_30_days","service_pv_30","mexpert_pv_30","organization_pv_30",
               "expand_rechange_amount_30"]
     data = df.loc[:, columns]