test

eda/esmm/Model_pipline/predict.py

@@ -233,7 +233,7 @@ if __name__ == "__main__":
         df2 = df.groupby(by=["uid1", "city1"]).apply(lambda x: x.sort_values(by="pctcvr", ascending=False)) \
             .reset_index(drop=True).groupby(by=["uid1", "city1"]).agg({'cid_id1': set_join}).reset_index(drop=False)
         df2.columns = ["device_id", "city_id", "nearby_queue"]
-        df2[time] = "2019-06-25"
+        df2["time"] = "2019-06-25"
 
 
         #update or insert