add

make_data.py

@@ -4,8 +4,10 @@ import pandas as pd
 
 
 def doctor():
-    date_str = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y%m%d")
-    date_tmp = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y-%m-%d")
+    date_str = "20200101"
+    date_tmp = "2020-01-01"
+    # date_str = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y%m%d")
+    # date_tmp = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y-%m-%d")
 
     sql = "select d.doctor_id,d.service_exposure_pv_30,d.service_ctr_30,d.expert_exposure_pv_30,d.expert_pv_30," \
     "b.merchant_id,budan.budan_payment_30_days " \
@@ -56,10 +58,10 @@ def doctor():
                 df["expert_exposure_pv_30"]/df["all_exposure"] * (df["expert_pv_30"] / df["expert_exposure_pv_30"])
 
     df.loc[df["doctor_discount_30_days"] < 0, ["doctor_discount_30_days"]] = 0
-    df.loc[df["budan_payment_30_days"] < 0, ["budan_payment_30_days"]] = 0
+    # df.loc[df["budan_payment_30_days"] < 0, ["budan_payment_30_days"]] = 0
     df.loc[df["expand_rechange_amount_30"] < 0, ["expand_rechange_amount_30"]] = 0
 
-    df["commission"] = (df["doctor_discount_30_days"] + df["budan_payment_30_days"])/df["tmp"]
+    df["commission"] = df["doctor_discount_30_days"]/df["tmp"]
     df["pv_ad"] = df["expand_rechange_amount_30"]/df["tmp"]
 
     df.loc[df["all_exposure"] <= 1500, ["ctr"]] = 0.01
@@ -79,13 +81,15 @@ def doctor():
     data = df.loc[:, columns]
 
     data = data.drop_duplicates()
-    data.to_csv('/tmp/6_doctor.csv',index=False)
+    data.to_csv('/tmp/1_doctor.csv',index=False)
     print("doctor end")
 
 
 def hospital():
-    date_str = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y%m%d")
-    date_tmp = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y-%m-%d")
+    date_str = "20200101"
+    date_tmp = "2020-01-01"
+    # date_str = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y%m%d")
+    # date_tmp = (datetime.datetime.now() - datetime.timedelta(days=1)).strftime("%Y-%m-%d")
 
     sql = "select api.id," \
           "h.hospital_id,h.hospital_exposure_pv_30,h.service_exposure_pv_30,h.expert_exposure_pv_30," \
@@ -142,10 +146,10 @@ def hospital():
                 df["expert_exposure_pv_30"]/df["all_exposure"] * df["expert_ctr_30"]
 
     df.loc[df["doctor_discount_30_days"] < 0, ["doctor_discount_30_days"]] = 0
-    df.loc[df["budan_payment_30_days"] < 0, ["budan_payment_30_days"]] = 0
+    # df.loc[df["budan_payment_30_days"] < 0, ["budan_payment_30_days"]] = 0
     df.loc[df["expand_rechange_amount_30"] < 0, ["expand_rechange_amount_30"]] = 0
 
-    df["commission"] = (df["doctor_discount_30_days"] + df["budan_payment_30_days"])/df["tmp"]
+    df["commission"] = df["doctor_discount_30_days"]/df["tmp"]
     df["cpt"] = df["expand_rechange_amount_30"]/df["tmp"]
 
     df.loc[df["all_exposure"] <= 1500, ["ctr"]] = 0.01
@@ -168,7 +172,7 @@ def hospital():
     data = data.drop_duplicates()
 
     print(data.head(6))
-    data.to_csv('/tmp/6_hospital.csv',index=False)
+    data.to_csv('/tmp/1_hospital.csv',index=False)
 
 
 if __name__ == "__main__":