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ffm-baseline
Commit 46f27a5c authored by 张彦钊's avatar 张彦钊
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修改文件写入路径

parent 7086c675
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Showing with 3 additions and 3 deletions
tensnsorflow/es/to_database.py
View file @ 46f27a5c
...@@ -40,7 +40,7 @@ def main(): ...@@ -40,7 +40,7 @@ def main():
df2 = pd.read_csv('/data/esmm/native.csv') df2 = pd.read_csv('/data/esmm/native.csv')
df2['cid_id'] = df2['cid_id'].astype(str) df2['cid_id'] = df2['cid_id'].astype(str)
df1 = pd.read_csv("/home/gmuser/esmm_data/native/pred.txt",sep='\t',header=None,names=["ctr","cvr","ctcvr"]) df1 = pd.read_csv("/data/esmm/native/pred.txt",sep='\t',header=None,names=["ctr","cvr","ctcvr"])
df2["ctr"],df2["cvr"],df2["ctcvr"] = df1["ctr"],df1["cvr"],df1["ctcvr"] df2["ctr"],df2["cvr"],df2["ctcvr"] = df1["ctr"],df1["cvr"],df1["ctcvr"]
df3 = df2.groupby(by=["uid","city"]).apply(lambda x: x.sort_values(by="ctcvr",ascending=False)).reset_index(drop=True).groupby(by=["uid","city"]).agg({'cid_id':native_set_join}).reset_index(drop=False) df3 = df2.groupby(by=["uid","city"]).apply(lambda x: x.sort_values(by="ctcvr",ascending=False)).reset_index(drop=True).groupby(by=["uid","city"]).agg({'cid_id':native_set_join}).reset_index(drop=False)
df3.columns = ["device_id","city_id","native_queue"] df3.columns = ["device_id","city_id","native_queue"]
...@@ -48,10 +48,10 @@ def main(): ...@@ -48,10 +48,10 @@ def main():
# nearby queue # nearby queue
df2 = pd.read_csv('/home/gmuser/esmm_data/nearby.csv') df2 = pd.read_csv('/data/esmm/nearby.csv')
df2['cid_id'] = df2['cid_id'].astype(str) df2['cid_id'] = df2['cid_id'].astype(str)
df1 = pd.read_csv("/home/gmuser/esmm_data/nearby/pred.txt",sep='\t',header=None,names=["ctr","cvr","ctcvr"]) df1 = pd.read_csv("/data/esmm/nearby/pred.txt",sep='\t',header=None,names=["ctr","cvr","ctcvr"])
df2["ctr"], df2["cvr"], df2["ctcvr"] = df1["ctr"], df1["cvr"], df1["ctcvr"] df2["ctr"], df2["cvr"], df2["ctcvr"] = df1["ctr"], df1["cvr"], df1["ctcvr"]
df4 = df2.groupby(by=["uid","city"]).apply(lambda x: x.sort_values(by="ctcvr",ascending=False)).reset_index(drop=True).groupby(by=["uid","city"]).agg({'cid_id':nearby_set_join}).reset_index(drop=False) df4 = df2.groupby(by=["uid","city"]).apply(lambda x: x.sort_values(by="ctcvr",ascending=False)).reset_index(drop=True).groupby(by=["uid","city"]).agg({'cid_id':nearby_set_join}).reset_index(drop=False)
df4.columns = ["device_id","city_id","nearby_queue"] df4.columns = ["device_id","city_id","nearby_queue"]
......
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