diff --git a/scripts/dataset/assistment.ipynb b/scripts/dataset/assistment2009.ipynb
similarity index 91%
rename from scripts/dataset/assistment.ipynb
rename to scripts/dataset/assistment2009.ipynb
index 030683d..06ce919 100644
--- a/scripts/dataset/assistment.ipynb
+++ b/scripts/dataset/assistment2009.ipynb
@@ -26,8 +26,10 @@
     "        print('Total length: {}'.format(len(data)))\n",
     "    elif isinstance(key, str):\n",
     "        print('Number of unique {}: {}'.format(key, len(data[key].unique())))\n",
+    "        return len(data[key].unique())\n",
     "    elif isinstance(key, list):\n",
-    "        print('Number of unique [{}]: {}'.format(','.join(key), len(data.drop_duplicates(key, keep='first'))))"
+    "        print('Number of unique [{}]: {}'.format(','.join(key), len(data.drop_duplicates(key, keep='first'))))\n",
+    "        return len(data.drop_duplicates(key, keep='first'))"
    ]
   },
   {
@@ -251,8 +253,7 @@
     }
    ],
    "source": [
-    "data_path ='../../data/assistment/'\n",
-    "raw_data = pd.read_csv('../../data/assistment/assistment.csv', encoding = 'utf-8', dtype={'skill_id': str})\n",
+    "raw_data = pd.read_csv('../../data/assistment/assistment2009.csv', encoding = 'utf-8', dtype={'skill_id': str})\n",
     "raw_data.head()"
    ]
   },
@@ -289,12 +290,10 @@
    ],
    "source": [
     "stat_unique(all_data, None)\n",
-    "stat_unique(all_data, ['student_id', 'question_id'])\n",
-    "stat_unique(all_data, 'student_id')\n",
-    "stat_unique(all_data, 'question_id')\n",
-    "stat_unique(all_data, 'knowledge_id')\n",
-    "ques_num = len(all_data['question_id'].unique())\n",
-    "know_num = len(all_data['knowledge_id'].unique())"
+    "a=stat_unique(all_data, ['student_id', 'question_id'])\n",
+    "b=stat_unique(all_data, 'student_id')\n",
+    "c=stat_unique(all_data, 'question_id')\n",
+    "d=stat_unique(all_data, 'knowledge_id')"
    ]
   },
   {
@@ -343,14 +342,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "filter 1471 students\n"
+      "filter 2120 students\n"
      ]
     }
    ],
    "source": [
     "# filter students\n",
     "n_questions = selected_data.groupby('student_id')['question_id'].count()\n",
-    "student_filter = n_questions[n_questions < 10].index.tolist()\n",
+    "student_filter = n_questions[n_questions < 20].index.tolist()\n",
     "print(f'filter {len(student_filter)} students')\n",
     "selected_data = selected_data[~selected_data['student_id'].isin(student_filter)]"
    ]
@@ -366,7 +365,7 @@
     "table = selected_data.loc[:, ['question_id', 'knowledge_id']].drop_duplicates()\n",
     "for i, row in table.iterrows():\n",
     "    q = row['question_id']\n",
-    "    q2k[q] = set(map(int, str(row['knowledge_id']).split('_')))\n",
+    "    q2k[q] = set(map(int, str(int(float(row['knowledge_id']))).split('_')))\n",
     "    \n",
     "# get knowledge to question map\n",
     "k2q = {}\n",
@@ -391,6 +390,7 @@
    ],
    "source": [
     "# filter knowledges\n",
+    "#selected_knowledges = { k for k, q in k2q.items()}\n",
     "selected_knowledges = { k for k, q in k2q.items() if len(q) >= 10}\n",
     "print(f'filter {len(k2q) - len(selected_knowledges)} knowledges')"
    ]
@@ -463,10 +463,10 @@
     "cnt = 0\n",
     "for i, row in selected_data.iterrows():\n",
     "    for k in str(row.knowledge_id).split('_'):\n",
-    "        if int(k) not in k2n:\n",
-    "            k2n[int(k)] = cnt\n",
+    "        if int(float(k)) not in k2n:\n",
+    "            k2n[int(float(k))] = cnt\n",
     "            cnt += 1\n",
-    "selected_data.loc[:, 'knowledge_id'] = selected_data.loc[:, 'knowledge_id'].apply(lambda x: '_'.join(map(lambda y: str(k2n[int(y)]), str(x).split('_'))))\n"
+    "selected_data.loc[:, 'knowledge_id'] = selected_data.loc[:, 'knowledge_id'].apply(lambda x: '_'.join(map(lambda y: str(k2n[int(float(y))]), str(x).split('_'))))\n"
    ]
   },
   {
@@ -478,9 +478,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Total length: 110398\n",
-      "Number of unique [student_id,question_id]: 78747\n",
-      "Number of unique student_id: 1940\n",
+      "Total length: 101470\n",
+      "Number of unique [student_id,question_id]: 71515\n",
+      "Number of unique student_id: 1291\n",
       "Number of unique question_id: 1485\n",
       "Number of unique knowledge_id: 35\n",
       "Average #questions per knowledge: 59.4\n"
@@ -489,10 +489,10 @@
    ],
    "source": [
     "stat_unique(selected_data, None)\n",
-    "stat_unique(selected_data, ['student_id', 'question_id'])\n",
-    "stat_unique(selected_data, 'student_id')\n",
-    "stat_unique(selected_data, 'question_id')\n",
-    "stat_unique(selected_data, 'knowledge_id')\n",
+    "a=stat_unique(selected_data, ['student_id', 'question_id'])\n",
+    "b=stat_unique(selected_data, 'student_id')\n",
+    "c=stat_unique(selected_data, 'question_id')\n",
+    "d=stat_unique(selected_data, 'knowledge_id')\n",
     "print('Average #questions per knowledge: {}'.format((len(q2k) / len(k2q))))"
    ]
   },
@@ -502,8 +502,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# save selected data\n",
-    "selected_data.to_csv(data_path+'selected_data.csv', index=False)"
+    "selected_data.to_csv('selected_data.csv', index=False)"
    ]
   },
   {
@@ -653,9 +652,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "train records length: 60393\n",
+      "train records length: 51465\n",
       "test records length: 50005\n",
-      "all records length: 110398\n"
+      "all records length: 101470\n"
      ]
     }
    ],
@@ -694,9 +693,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "save_to_csv(train_data, data_path+'train_triples.csv')\n",
-    "save_to_csv(test_data, data_path+'test_triples.csv')\n",
-    "save_to_csv(all_data, data_path+'triples.csv')"
+    "save_to_csv(train_data, 'train_triples.csv')\n",
+    "save_to_csv(test_data, 'test_triples.csv')\n",
+    "save_to_csv(all_data, 'triples.csv')"
    ]
   },
   {
@@ -706,8 +705,8 @@
    "outputs": [],
    "source": [
     "metadata = {\"num_students\": n_students, \n",
-    "            \"num_questions\": ques_num,\n",
-    "            \"num_concepts\": know_num, \n",
+    "            \"num_questions\": c,\n",
+    "            \"num_concepts\": d, \n",
     "            \"num_records\": len(all_data), \n",
     "            \"num_train_students\": n_students - len(test_students), \n",
     "            \"num_test_students\": len(test_students)}"
@@ -719,14 +718,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "with open(data_path+'metadata.json', 'w') as f:\n",
+    "with open('metadata.json', 'w') as f:\n",
     "    json.dump(metadata, f)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Basenv",
    "language": "python",
    "name": "python3"
   },