diff --git a/tensorflow/notebooks/leo/LSTM_All_Crypto_01.ipynb b/tensorflow/notebooks/leo/LSTM_All_Crypto_01.ipynb
index 6e18e1c..fa93227 100644
--- a/tensorflow/notebooks/leo/LSTM_All_Crypto_01.ipynb
+++ b/tensorflow/notebooks/leo/LSTM_All_Crypto_01.ipynb
@@ -344,16 +344,108 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 143,
    "id": "a7c8b332-cd4a-455f-b7cf-381aec15c456",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    date  close_ltc  volume_ltc  vwap_ltc\n",
+      "0  1-0-0     0.8317  110.056253  0.831662\n",
+      "1  1-0-1     0.8312  176.868598  0.831441\n",
+      "2  1-0-2     0.8315   52.367396  0.831319\n"
+     ]
+    }
+   ],
+   "source": [
+    "# LTC\n",
+    "df_concat_ltc = df_concat[df_concat['instrument_id'] == 'PAIR-LTC-USD']\n",
+    "\n",
+    "# Reset Index\n",
+    "df_concat_ltc = df_concat_ltc.reset_index(drop = True)\n",
+    "\n",
+    "# Rename Vars\n",
+    "df_concat_ltc['close_ltc'] = df_concat_ltc['close']/100.00\n",
+    "df_concat_ltc['volume_ltc'] = df_concat_ltc['volume']\n",
+    "df_concat_ltc['vwap_ltc'] = df_concat_ltc['vwap']/100.00\n",
+    "\n",
+    "df_concat_ltc = df_concat_ltc.drop('close', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('volume', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('vwap', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('instrument_id', axis = 1)\n",
+    "\n",
+    "print (df_concat_ltc.head(3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "0a27972a-f457-4ca5-8530-d6c87c7d9d91",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    date  close_eth  volume_eth  vwap_eth\n",
+      "0  1-0-0   0.376204   37.497964  0.376108\n",
+      "1  1-0-1   0.375942   11.703305  0.376013\n",
+      "2  1-0-2   0.376096  145.335061  0.376016\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ETH\n",
+    "df_concat_eth = df_concat[df_concat['instrument_id'] == 'PAIR-ETH-USD']\n",
+    "\n",
+    "# Reset Index\n",
+    "df_concat_eth = df_concat_eth.reset_index(drop = True)\n",
+    "\n",
+    "# Rename Vars\n",
+    "df_concat_eth['close_eth'] = df_concat_eth['close']/10000.00\n",
+    "df_concat_eth['volume_eth'] = df_concat_eth['volume']\n",
+    "df_concat_eth['vwap_eth'] = df_concat_eth['vwap']/10000.00\n",
+    "\n",
+    "df_concat_eth = df_concat_eth.drop('close', axis = 1)\n",
+    "df_concat_eth = df_concat_eth.drop('volume', axis = 1)\n",
+    "df_concat_eth = df_concat_eth.drop('vwap', axis = 1)\n",
+    "df_concat_eth = df_concat_eth.drop('instrument_id', axis = 1)\n",
+    "\n",
+    "print (df_concat_eth.head(3))"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0a27972a-f457-4ca5-8530-d6c87c7d9d91",
+   "id": "e94efeb3-eeeb-467b-9493-b305a3bf1a52",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# XRP\n",
+    "df_concat_ltc = df_concat[df_concat['instrument_id'] == 'PAIR-LTC-USD']\n",
+    "\n",
+    "# Reset Index\n",
+    "df_concat_ltc = df_concat_ltc.reset_index(drop = True)\n",
+    "\n",
+    "# Rename Vars\n",
+    "df_concat_ltc['close_ltc'] = df_concat_ltc['close']/100.00\n",
+    "df_concat_ltc['volume_ltc'] = df_concat_ltc['volume']\n",
+    "df_concat_ltc['vwap_ltc'] = df_concat_ltc['vwap']/100.00\n",
+    "\n",
+    "df_concat_ltc = df_concat_ltc.drop('close', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('volume', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('vwap', axis = 1)\n",
+    "df_concat_ltc = df_concat_ltc.drop('instrument_id', axis = 1)\n",
+    "\n",
+    "print (df_concat_ltc.head(3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "97a4fe65-b999-4459-b21e-8c1f0c20a25e",
    "metadata": {},
    "outputs": [],
    "source": []