增加保存到csv

tensnsorflow/ffm.py

@@ -53,7 +53,7 @@ def get_data():
 
 def transform(df,table):
     model = multiFFMFormatPandas()
-    df = model.fit_transform(df, y="y", n=50000, processes=20)
+    df = model.fit_transform(df, y="y", n=80000, processes=20)
     df = pd.DataFrame(df)
     df["device_id"] = df[0].apply(lambda x: x.split(",")[0])
     df["city_id"] = df[0].apply(lambda x: x.split(",")[1])
@@ -62,7 +62,7 @@ def transform(df,table):
     df["seq"] = list(range(df.shape[0]))
     df["seq"] = df["seq"].astype("str")
     df["ffm"] = df[0].apply(lambda x: x.split(",")[3:])
-    df["ffm"] = df["seq"].str.cat(df["ffm"], sep=",")
+    df["ffm"] = df["seq"].str.cat([df["ffm"].values.tolist()], sep=",")
     df["random"] = np.random.randint(1, 2147483647, df.shape[0])
     df = df.drop(0, axis=1).drop("seq",axis=1)
     print("size")