diff --git a/compareDBs.ipynb b/compareDBs.ipynb
index c46b0f5..4f0ba45 100644
--- a/compareDBs.ipynb
+++ b/compareDBs.ipynb
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 18,
    "id": "ab6c6c81-6ac1-4668-a79b-a9a0341fb35a",
    "metadata": {
     "tags": []
@@ -59,7 +59,7 @@
        "False"
       ]
      },
-     "execution_count": 74,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -68,8 +68,11 @@
     "import configparser\n",
     "from datetime import datetime\n",
     "\n",
+    "import duckdb\n",
     "import influxdb_client\n",
     "import pandas as pd\n",
+    "\n",
+    "# import pymongo\n",
     "from clickhouse_driver import Client\n",
     "from dotenv import load_dotenv\n",
     "from minio import Minio\n",
@@ -77,41 +80,12 @@
     "from pytz import timezone\n",
     "from sqlalchemy import create_engine\n",
     "\n",
-    "load_dotenv()\n",
-    "\n",
-    "\n",
-    "# import io\n",
-    "# import time\n",
-    "# import numpy as np\n",
-    "# import clickhouse_connect\n",
-    "# pip install python-dotenv\n",
-    "# import psycopg2\n",
-    "# import os\n",
-    "# import pyarrow as pa\n",
-    "# import pyarrow.parquet as pq\n",
-    "# import s3fs\n",
-    "# from friendly.jupyter import Friendly\n",
-    "# from minio.error import S3Error\n",
-    "# from pyarrow import Table\n",
-    "# import os\n",
-    "# from influxdb_client import InfluxDBClient, Point, WritePrecision\n",
-    "# from influxdb_client.client.write_api import SYNCHRONOUS\n",
-    "# Friendly.dark()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "01d88282-32a1-404f-92da-488a23302fd0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# teset"
+    "load_dotenv()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "55c3cd57-0996-4723-beb5-8f3196c96009",
    "metadata": {
     "tags": []
@@ -124,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "968403e3-2e5e-4834-b969-be4600e2963a",
    "metadata": {
     "tags": []
@@ -196,6 +170,7 @@
    "cell_type": "markdown",
    "id": "274cc026-2f48-4e38-b80f-b1a9ff982060",
    "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -220,6 +195,7 @@
    "cell_type": "markdown",
    "id": "4a8d5703-9bc9-4d38-83ff-457159304d58",
    "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -297,14 +273,15 @@
    },
    "outputs": [],
    "source": [
-    "%%time\n",
-    "df = pd.DataFrame(client.query_dataframe(\"SELECT * FROM default.{}\".format(dbname)))"
+    "# %%time\n",
+    "# df = pd.DataFrame(client.query_dataframe(\"SELECT * FROM default.{}\".format(dbname)))"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "1d389546-911f-43f7-aad1-49f7bcc83503",
    "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -468,6 +445,7 @@
    "cell_type": "markdown",
    "id": "f9e0393d-7d1d-406a-a068-9dbf4968e977",
    "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -476,7 +454,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": null,
    "id": "60a990e2-4607-4654-84ec-17d4985adae2",
    "metadata": {
     "tags": []
@@ -515,36 +493,257 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": null,
    "id": "390918c8-c88f-404a-96c4-685d578fdad0",
    "metadata": {
     "tags": []
    },
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "df.to_parquet(\"data/data.parquet\")\n",
+    "if __name__ == \"__main__\":\n",
+    "    try:\n",
+    "        main()\n",
+    "    except S3Error as exc:\n",
+    "        print(\"error occurred.\", exc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a9e07143-8c11-4b68-a869-c3922cda9092",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pq = pd.read_parquet(\"data/data.parquet\", engine=\"pyarrow\")\n",
+    "pq.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "50d1fc58-89a7-4507-aff0-6e943656cfe0",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "### MongoDB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "d104d9af-fa34-4261-8478-329a28ee4f2e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Load csv dataset\n",
+    "data = pd.read_csv(\"out.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "0af8f72c-5b58-4dfc-af36-c5b4bc79f127",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Connect to MongoDB\n",
+    "client = MongoClient(\n",
+    "    # \"mongodb://192.168.1.133:27017\"\n",
+    "    \"mongodb://{}:{}@{}/EURUSDtest?retryWrites=true&w=majority\".format(\n",
+    "        MongoUser, MongoKey, MongoUrl\n",
+    "    ),\n",
+    "    authSource=\"admin\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "f1b20d15-f5af-463c-813f-ffae61119de1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "db = client[\"EUROUSDtest\"]\n",
+    "collection = db[\"finance\"]\n",
+    "# data.reset_index(inplace=True)\n",
+    "data_dict = data.to_dict(\"records\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "70674d23-f375-4659-87ec-c745dec96d54",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Bucket 'data' already exists\n",
-      "CPU times: user 610 ms, sys: 133 ms, total: 743 ms\n",
-      "Wall time: 4.05 s\n"
+      "CPU times: user 19.2 s, sys: 269 ms, total: 19.5 s\n",
+      "Wall time: 50.1 s\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<pymongo.results.InsertManyResult at 0x7f8e39c991e0>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "%%time\n",
-    "df.to_parquet(\"data/data.parquet\")\n",
-    "if __name__ == \"__main__\":\n",
-    "    try:\n",
-    "        main()\n",
-    "    except S3Error as exc:\n",
-    "        print(\"error occurred.\", exc)"
+    "# Insert collection\n",
+    "collection.insert_many(data_dict)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
-   "id": "a9e07143-8c11-4b68-a869-c3922cda9092",
+   "execution_count": null,
+   "id": "81a4a33d-5914-45d8-af4e-2b0aabd2ac38",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# read"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97405e42-61dc-42c7-8220-237a312c0ec7",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "### DuckDB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "bbcdb883-d6dc-46db-88db-4c90b84522ba",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(42,)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "cursor = duckdb.connect()\n",
+    "print(cursor.execute(\"SELECT 42\").fetchall())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "35025a6e-9dc7-46cf-a792-76b3d84f1ac0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1.53 s, sys: 63.6 ms, total: 1.59 s\n",
+      "Wall time: 1.59 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<duckdb.DuckDBPyConnection at 0x7f8e3b2261b0>"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "conn = duckdb.connect()\n",
+    "data = pd.read_csv(\"out.csv\")\n",
+    "conn.register(\"EURUSDtest\", data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "c6abdaaa-3ac2-425b-9208-d6cb79afe966",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [name]\n",
+       "Index: []"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(conn.execute(\"SHOW TABLES\").df())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "2acce0f3-f0b2-47d0-8e0d-f9e9687efc18",
    "metadata": {
     "tags": []
    },
@@ -572,6 +771,7 @@
        "      <th></th>\n",
        "      <th>Unnamed: 0</th>\n",
        "      <th>id</th>\n",
+       "      <th>from</th>\n",
        "      <th>at</th>\n",
        "      <th>to</th>\n",
        "      <th>open</th>\n",
@@ -580,24 +780,13 @@
        "      <th>max</th>\n",
        "      <th>volume</th>\n",
        "    </tr>\n",
-       "    <tr>\n",
-       "      <th>from</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>2023-01-02 15:58:45</th>\n",
+       "      <th>0</th>\n",
        "      <td>0</td>\n",
        "      <td>7730801</td>\n",
+       "      <td>2023-01-02 15:58:45</td>\n",
        "      <td>1672675140000000000</td>\n",
        "      <td>2023-01-02 15:59:00</td>\n",
        "      <td>1.065995</td>\n",
@@ -607,9 +796,10 @@
        "      <td>57</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2023-01-02 15:59:00</th>\n",
+       "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>7730802</td>\n",
+       "      <td>2023-01-02 15:59:00</td>\n",
        "      <td>1672675155000000000</td>\n",
        "      <td>2023-01-02 15:59:15</td>\n",
        "      <td>1.066055</td>\n",
@@ -619,9 +809,10 @@
        "      <td>52</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2023-01-02 15:59:15</th>\n",
+       "      <th>2</th>\n",
        "      <td>2</td>\n",
        "      <td>7730803</td>\n",
+       "      <td>2023-01-02 15:59:15</td>\n",
        "      <td>1672675170000000000</td>\n",
        "      <td>2023-01-02 15:59:30</td>\n",
        "      <td>1.066080</td>\n",
@@ -631,9 +822,10 @@
        "      <td>57</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2023-01-02 15:59:30</th>\n",
+       "      <th>3</th>\n",
        "      <td>3</td>\n",
        "      <td>7730804</td>\n",
+       "      <td>2023-01-02 15:59:30</td>\n",
        "      <td>1672675185000000000</td>\n",
        "      <td>2023-01-02 15:59:45</td>\n",
        "      <td>1.065980</td>\n",
@@ -643,9 +835,10 @@
        "      <td>64</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2023-01-02 15:59:45</th>\n",
+       "      <th>4</th>\n",
        "      <td>4</td>\n",
        "      <td>7730805</td>\n",
+       "      <td>2023-01-02 15:59:45</td>\n",
        "      <td>1672675200000000000</td>\n",
        "      <td>2023-01-02 16:00:00</td>\n",
        "      <td>1.065975</td>\n",
@@ -654,130 +847,368 @@
        "      <td>1.066055</td>\n",
        "      <td>50</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999995</th>\n",
+       "      <td>999995</td>\n",
+       "      <td>7984748</td>\n",
+       "      <td>2023-03-03 18:13:30</td>\n",
+       "      <td>1677867225000000000</td>\n",
+       "      <td>2023-03-03 18:13:45</td>\n",
+       "      <td>1.062695</td>\n",
+       "      <td>1.062635</td>\n",
+       "      <td>1.062630</td>\n",
+       "      <td>1.062700</td>\n",
+       "      <td>64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999996</th>\n",
+       "      <td>999996</td>\n",
+       "      <td>7984749</td>\n",
+       "      <td>2023-03-03 18:13:45</td>\n",
+       "      <td>1677867240000000000</td>\n",
+       "      <td>2023-03-03 18:14:00</td>\n",
+       "      <td>1.062645</td>\n",
+       "      <td>1.062650</td>\n",
+       "      <td>1.062625</td>\n",
+       "      <td>1.062650</td>\n",
+       "      <td>43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999997</th>\n",
+       "      <td>999997</td>\n",
+       "      <td>7984750</td>\n",
+       "      <td>2023-03-03 18:14:00</td>\n",
+       "      <td>1677867255000000000</td>\n",
+       "      <td>2023-03-03 18:14:15</td>\n",
+       "      <td>1.062640</td>\n",
+       "      <td>1.062625</td>\n",
+       "      <td>1.062620</td>\n",
+       "      <td>1.062665</td>\n",
+       "      <td>47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999998</th>\n",
+       "      <td>999998</td>\n",
+       "      <td>7984751</td>\n",
+       "      <td>2023-03-03 18:14:15</td>\n",
+       "      <td>1677867270000000000</td>\n",
+       "      <td>2023-03-03 18:14:30</td>\n",
+       "      <td>1.062625</td>\n",
+       "      <td>1.062535</td>\n",
+       "      <td>1.062535</td>\n",
+       "      <td>1.062645</td>\n",
+       "      <td>43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999999</th>\n",
+       "      <td>999999</td>\n",
+       "      <td>7984752</td>\n",
+       "      <td>2023-03-03 18:14:30</td>\n",
+       "      <td>1677867285000000000</td>\n",
+       "      <td>2023-03-03 18:14:45</td>\n",
+       "      <td>1.062535</td>\n",
+       "      <td>1.062520</td>\n",
+       "      <td>1.062520</td>\n",
+       "      <td>1.062580</td>\n",
+       "      <td>59</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>1000000 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                     Unnamed: 0       id                   at   \n",
-       "from                                                            \n",
-       "2023-01-02 15:58:45           0  7730801  1672675140000000000  \\\n",
-       "2023-01-02 15:59:00           1  7730802  1672675155000000000   \n",
-       "2023-01-02 15:59:15           2  7730803  1672675170000000000   \n",
-       "2023-01-02 15:59:30           3  7730804  1672675185000000000   \n",
-       "2023-01-02 15:59:45           4  7730805  1672675200000000000   \n",
+       "        Unnamed: 0       id                 from                   at   \n",
+       "0                0  7730801  2023-01-02 15:58:45  1672675140000000000  \\\n",
+       "1                1  7730802  2023-01-02 15:59:00  1672675155000000000   \n",
+       "2                2  7730803  2023-01-02 15:59:15  1672675170000000000   \n",
+       "3                3  7730804  2023-01-02 15:59:30  1672675185000000000   \n",
+       "4                4  7730805  2023-01-02 15:59:45  1672675200000000000   \n",
+       "...            ...      ...                  ...                  ...   \n",
+       "999995      999995  7984748  2023-03-03 18:13:30  1677867225000000000   \n",
+       "999996      999996  7984749  2023-03-03 18:13:45  1677867240000000000   \n",
+       "999997      999997  7984750  2023-03-03 18:14:00  1677867255000000000   \n",
+       "999998      999998  7984751  2023-03-03 18:14:15  1677867270000000000   \n",
+       "999999      999999  7984752  2023-03-03 18:14:30  1677867285000000000   \n",
        "\n",
-       "                                      to      open     close       min   \n",
-       "from                                                                     \n",
-       "2023-01-02 15:58:45  2023-01-02 15:59:00  1.065995  1.066035  1.065930  \\\n",
-       "2023-01-02 15:59:00  2023-01-02 15:59:15  1.066055  1.066085  1.066005   \n",
-       "2023-01-02 15:59:15  2023-01-02 15:59:30  1.066080  1.066025  1.066025   \n",
-       "2023-01-02 15:59:30  2023-01-02 15:59:45  1.065980  1.065985  1.065885   \n",
-       "2023-01-02 15:59:45  2023-01-02 16:00:00  1.065975  1.066055  1.065830   \n",
+       "                         to      open     close       min       max  volume  \n",
+       "0       2023-01-02 15:59:00  1.065995  1.066035  1.065930  1.066070      57  \n",
+       "1       2023-01-02 15:59:15  1.066055  1.066085  1.066005  1.066115      52  \n",
+       "2       2023-01-02 15:59:30  1.066080  1.066025  1.066025  1.066110      57  \n",
+       "3       2023-01-02 15:59:45  1.065980  1.065985  1.065885  1.066045      64  \n",
+       "4       2023-01-02 16:00:00  1.065975  1.066055  1.065830  1.066055      50  \n",
+       "...                     ...       ...       ...       ...       ...     ...  \n",
+       "999995  2023-03-03 18:13:45  1.062695  1.062635  1.062630  1.062700      64  \n",
+       "999996  2023-03-03 18:14:00  1.062645  1.062650  1.062625  1.062650      43  \n",
+       "999997  2023-03-03 18:14:15  1.062640  1.062625  1.062620  1.062665      47  \n",
+       "999998  2023-03-03 18:14:30  1.062625  1.062535  1.062535  1.062645      43  \n",
+       "999999  2023-03-03 18:14:45  1.062535  1.062520  1.062520  1.062580      59  \n",
        "\n",
-       "                          max  volume  \n",
-       "from                                   \n",
-       "2023-01-02 15:58:45  1.066070      57  \n",
-       "2023-01-02 15:59:00  1.066115      52  \n",
-       "2023-01-02 15:59:15  1.066110      57  \n",
-       "2023-01-02 15:59:30  1.066045      64  \n",
-       "2023-01-02 15:59:45  1.066055      50  "
+       "[1000000 rows x 10 columns]"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pq = pd.read_parquet(\"data/data.parquet\", engine=\"pyarrow\")\n",
-    "pq.head()"
+    "%%time\n",
+    "df = conn.execute(\"SELECT * FROM EURUSDtest\").df()\n",
+    "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "50d1fc58-89a7-4507-aff0-6e943656cfe0",
+   "id": "4409cc89-ed14-4313-ac89-65b826038533",
    "metadata": {},
    "source": [
-    "### MongoDB"
+    "### Kdb+"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "81a4a33d-5914-45d8-af4e-2b0aabd2ac38",
+   "execution_count": 66,
+   "id": "14f63810-1943-4e28-9bce-2148be6be02d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "np.bool = np.bool_\n",
+    "from qpython import qconnection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "8ff6c090-7e02-435a-a179-f2aab81da972",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# read csv\n",
+    "data = pd.read_csv(\"out.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "b4eb8ab9-81e8-4732-8cf7-51f0981d3d57",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "client = MongoClient(MongoUrl);"
+    "# open connection\n",
+    "q = qconnection.QConnection(host=\"localhost\", port=5001)\n",
+    "q.open()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "3e634d34-ad62-432e-aa0c-07cd4b7556e2",
+   "execution_count": 51,
+   "id": "97cb6b5b-65a5-46a0-a4ee-e5c535a716ab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 837 ms, sys: 40 ms, total: 877 ms\n",
+      "Wall time: 1.16 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "# send df to kd+ in memory bank\n",
+    "%%time\n",
+    "q.sendSync(\"{t::x}\", data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "c2ed2d51-bc8e-4207-892a-35fc55d43570",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "b':/home/sandman/q/tab1'"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# write to on disk table\n",
+    "q.sendSync(\"`:/home/sandman/q/tab1 set t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "9c055a95-f73f-43a3-8fbd-61e42235117e",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1.78 ms, sys: 2 µs, total: 1.79 ms\n",
+      "Wall time: 329 ms\n"
+     ]
+    }
+   ],
    "source": [
-    "DB = client[\"collection_name\"]"
+    "%%time\n",
+    "# read from on disk table\n",
+    "df2 = q.sendSync(\"tab2: get `:/home/sandman/q/tab1\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "dd871028-41c3-4f0d-aefc-f2ea4ee866e7",
+   "execution_count": 54,
+   "id": "9760de38-9f04-4322-bfff-c7ee12d5dee5",
    "metadata": {
-    "scrolled": true,
     "tags": []
    },
    "outputs": [],
    "source": [
-    "db = client[\"test\"]"
+    "# print(df2)"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "97405e42-61dc-42c7-8220-237a312c0ec7",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "c06c9222-c69d-4872-9d21-052281a013e2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 957 ms, sys: 87.9 ms, total: 1.05 s\n",
+      "Wall time: 1.13 s\n"
+     ]
+    }
+   ],
    "source": [
-    "### DuckDB"
+    "%%time\n",
+    "# load to variable df2\n",
+    "df2 = q.sendSync(\"tab2\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "bbcdb883-d6dc-46db-88db-4c90b84522ba",
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "execution_count": 58,
+   "id": "8815f01c-fd0a-4f94-ab7f-f8ede84ba4e7",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "'QTable' object is not callable",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[58], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mdf2\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mTypeError\u001b[0m: 'QTable' object is not callable"
+     ]
+    }
+   ],
+   "source": [
+    "# df2(type)"
+   ]
   },
   {
-   "cell_type": "markdown",
-   "id": "4409cc89-ed14-4313-ac89-65b826038533",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "e6ed3927-4395-45cd-9a28-88c5db01f2e5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'bool' object has no attribute 'to_numpy'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "File \u001b[0;32m<timed exec>:2\u001b[0m\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qconnection.py:385\u001b[0m, in \u001b[0;36mQConnection.__call__\u001b[0;34m(self, *parameters, **options)\u001b[0m\n\u001b[1;32m    384\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39mparameters, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions):\n\u001b[0;32m--> 385\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msendSync\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qconnection.py:303\u001b[0m, in \u001b[0;36mQConnection.sendSync\u001b[0;34m(self, query, *parameters, **options)\u001b[0m\n\u001b[1;32m    249\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m'''Performs a synchronous query against a q service and returns parsed \u001b[39;00m\n\u001b[1;32m    250\u001b[0m \u001b[38;5;124;03mdata.\u001b[39;00m\n\u001b[1;32m    251\u001b[0m \u001b[38;5;124;03m\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    300\u001b[0m \u001b[38;5;124;03m         :class:`.QReaderException`\u001b[39;00m\n\u001b[1;32m    301\u001b[0m \u001b[38;5;124;03m'''\u001b[39;00m\n\u001b[1;32m    302\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mquery(MessageType\u001b[38;5;241m.\u001b[39mSYNC, query, \u001b[38;5;241m*\u001b[39mparameters, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions)\n\u001b[0;32m--> 303\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreceive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata_only\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m response\u001b[38;5;241m.\u001b[39mtype \u001b[38;5;241m==\u001b[39m MessageType\u001b[38;5;241m.\u001b[39mRESPONSE:\n\u001b[1;32m    306\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m response\u001b[38;5;241m.\u001b[39mdata\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qconnection.py:380\u001b[0m, in \u001b[0;36mQConnection.receive\u001b[0;34m(self, data_only, **options)\u001b[0m\n\u001b[1;32m    341\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mreceive\u001b[39m(\u001b[38;5;28mself\u001b[39m, data_only \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions):\n\u001b[1;32m    342\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m'''Reads and (optionally) parses the response from a q service.\u001b[39;00m\n\u001b[1;32m    343\u001b[0m \u001b[38;5;124;03m    \u001b[39;00m\n\u001b[1;32m    344\u001b[0m \u001b[38;5;124;03m    Retrieves query result along with meta-information:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    378\u001b[0m \u001b[38;5;124;03m    :raises: :class:`.QReaderException`\u001b[39;00m\n\u001b[1;32m    379\u001b[0m \u001b[38;5;124;03m    '''\u001b[39;00m\n\u001b[0;32m--> 380\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_reader\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_options\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munion_dict\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    381\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;28;01mif\u001b[39;00m data_only \u001b[38;5;28;01melse\u001b[39;00m result\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:139\u001b[0m, in \u001b[0;36mQReader.read\u001b[0;34m(self, source, **options)\u001b[0m\n\u001b[1;32m    120\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m'''\u001b[39;00m\n\u001b[1;32m    121\u001b[0m \u001b[38;5;124;03mReads and optionally parses a single message.\u001b[39;00m\n\u001b[1;32m    122\u001b[0m \u001b[38;5;124;03m\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    136\u001b[0m \u001b[38;5;124;03m          with meta information\u001b[39;00m\n\u001b[1;32m    137\u001b[0m \u001b[38;5;124;03m'''\u001b[39;00m\n\u001b[1;32m    138\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mread_header(source)\n\u001b[0;32m--> 139\u001b[0m message\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msize\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_compressed\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    141\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m message\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:216\u001b[0m, in \u001b[0;36mQReader.read_data\u001b[0;34m(self, message_size, is_compressed, **options)\u001b[0m\n\u001b[1;32m    213\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_stream \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_options\u001b[38;5;241m.\u001b[39mraw:\n\u001b[1;32m    214\u001b[0m     raw_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mraw(message_size \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m8\u001b[39m)\n\u001b[0;32m--> 216\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m raw_data \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_options\u001b[38;5;241m.\u001b[39mraw \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_object\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:225\u001b[0m, in \u001b[0;36mQReader._read_object\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    222\u001b[0m reader \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_reader(qtype)\n\u001b[1;32m    224\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m reader:\n\u001b[0;32m--> 225\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mreader\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    226\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m qtype \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m QBOOL_LIST \u001b[38;5;129;01mand\u001b[39;00m qtype \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m QTIME_LIST:\n\u001b[1;32m    227\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_read_list(qtype)\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/_pandas.py:76\u001b[0m, in \u001b[0;36mPandasQReader._read_table\u001b[0;34m(self, qtype)\u001b[0m\n\u001b[1;32m     74\u001b[0m columns \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_read_object()\n\u001b[1;32m     75\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mskip() \u001b[38;5;66;03m# ignore generic list type indicator\u001b[39;00m\n\u001b[0;32m---> 76\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mQReader\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_general_list\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     78\u001b[0m odict \u001b[38;5;241m=\u001b[39m OrderedDict()\n\u001b[1;32m     79\u001b[0m meta \u001b[38;5;241m=\u001b[39m MetaData(qtype \u001b[38;5;241m=\u001b[39m QTABLE)\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:338\u001b[0m, in \u001b[0;36mQReader._read_general_list\u001b[0;34m(self, qtype)\u001b[0m\n\u001b[1;32m    335\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mskip()  \u001b[38;5;66;03m# ignore attributes\u001b[39;00m\n\u001b[1;32m    336\u001b[0m length \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mget_int()\n\u001b[0;32m--> 338\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_read_object() \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(length)]\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:338\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    335\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mskip()  \u001b[38;5;66;03m# ignore attributes\u001b[39;00m\n\u001b[1;32m    336\u001b[0m length \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer\u001b[38;5;241m.\u001b[39mget_int()\n\u001b[0;32m--> 338\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_object\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(length)]\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/qreader.py:227\u001b[0m, in \u001b[0;36mQReader._read_object\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    225\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m reader(\u001b[38;5;28mself\u001b[39m, qtype)\n\u001b[1;32m    226\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m qtype \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m QBOOL_LIST \u001b[38;5;129;01mand\u001b[39;00m qtype \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m QTIME_LIST:\n\u001b[0;32m--> 227\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_list\u001b[49m\u001b[43m(\u001b[49m\u001b[43mqtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    228\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m qtype \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m QBOOL \u001b[38;5;129;01mand\u001b[39;00m qtype \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m QTIME:\n\u001b[1;32m    229\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_read_atom(qtype)\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/qpython/_pandas.py:116\u001b[0m, in \u001b[0;36mPandasQReader._read_list\u001b[0;34m(self, qtype)\u001b[0m\n\u001b[1;32m    114\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;28mabs\u001b[39m(qtype) \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m [QMONTH, QDATE, QDATETIME, QMINUTE, QSECOND, QTIME, QTIMESTAMP, QTIMESPAN, QSYMBOL]:\n\u001b[1;32m    115\u001b[0m     null \u001b[38;5;241m=\u001b[39m QNULLMAP[\u001b[38;5;241m-\u001b[39m\u001b[38;5;28mabs\u001b[39m(qtype)][\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m--> 116\u001b[0m     ps \u001b[38;5;241m=\u001b[39m \u001b[43mpandas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mSeries\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mqlist\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnull\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumpy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mNaN\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    118\u001b[0m     ps \u001b[38;5;241m=\u001b[39m pandas\u001b[38;5;241m.\u001b[39mSeries(data \u001b[38;5;241m=\u001b[39m qlist)\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/series.py:5219\u001b[0m, in \u001b[0;36mSeries.replace\u001b[0;34m(self, to_replace, value, inplace, limit, regex, method)\u001b[0m\n\u001b[1;32m   5203\u001b[0m \u001b[38;5;129m@doc\u001b[39m(\n\u001b[1;32m   5204\u001b[0m     NDFrame\u001b[38;5;241m.\u001b[39mreplace,\n\u001b[1;32m   5205\u001b[0m     klass\u001b[38;5;241m=\u001b[39m_shared_doc_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mklass\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   5217\u001b[0m     method: Literal[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpad\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mffill\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbfill\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m|\u001b[39m lib\u001b[38;5;241m.\u001b[39mNoDefault \u001b[38;5;241m=\u001b[39m lib\u001b[38;5;241m.\u001b[39mno_default,\n\u001b[1;32m   5218\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Series \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 5219\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   5220\u001b[0m \u001b[43m        \u001b[49m\u001b[43mto_replace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mto_replace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5221\u001b[0m \u001b[43m        \u001b[49m\u001b[43mvalue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5222\u001b[0m \u001b[43m        \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minplace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5223\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlimit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlimit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5224\u001b[0m \u001b[43m        \u001b[49m\u001b[43mregex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mregex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5225\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5226\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/generic.py:7389\u001b[0m, in \u001b[0;36mNDFrame.replace\u001b[0;34m(self, to_replace, value, inplace, limit, regex, method)\u001b[0m\n\u001b[1;32m   7383\u001b[0m         new_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mgr\u001b[38;5;241m.\u001b[39mreplace_regex(\n\u001b[1;32m   7384\u001b[0m             to_replace\u001b[38;5;241m=\u001b[39mto_replace,\n\u001b[1;32m   7385\u001b[0m             value\u001b[38;5;241m=\u001b[39mvalue,\n\u001b[1;32m   7386\u001b[0m             inplace\u001b[38;5;241m=\u001b[39minplace,\n\u001b[1;32m   7387\u001b[0m         )\n\u001b[1;32m   7388\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 7389\u001b[0m         new_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_mgr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   7390\u001b[0m \u001b[43m            \u001b[49m\u001b[43mto_replace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mto_replace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minplace\u001b[49m\n\u001b[1;32m   7391\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   7392\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   7393\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m   7394\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mInvalid \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mto_replace\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m type: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mrepr\u001b[39m(\u001b[38;5;28mtype\u001b[39m(to_replace)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m   7395\u001b[0m     )\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/internals/managers.py:475\u001b[0m, in \u001b[0;36mBaseBlockManager.replace\u001b[0;34m(self, to_replace, value, inplace)\u001b[0m\n\u001b[1;32m    473\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_list_like(to_replace)\n\u001b[1;32m    474\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_list_like(value)\n\u001b[0;32m--> 475\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    476\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mreplace\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    477\u001b[0m \u001b[43m    \u001b[49m\u001b[43mto_replace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mto_replace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    478\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvalue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    479\u001b[0m \u001b[43m    \u001b[49m\u001b[43minplace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minplace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    480\u001b[0m \u001b[43m    \u001b[49m\u001b[43musing_cow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43musing_copy_on_write\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    481\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/internals/managers.py:352\u001b[0m, in \u001b[0;36mBaseBlockManager.apply\u001b[0;34m(self, f, align_keys, **kwargs)\u001b[0m\n\u001b[1;32m    350\u001b[0m         applied \u001b[38;5;241m=\u001b[39m b\u001b[38;5;241m.\u001b[39mapply(f, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    351\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 352\u001b[0m         applied \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    353\u001b[0m     result_blocks \u001b[38;5;241m=\u001b[39m extend_blocks(applied, result_blocks)\n\u001b[1;32m    355\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39mfrom_blocks(result_blocks, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxes)\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/internals/blocks.py:593\u001b[0m, in \u001b[0;36mBlock.replace\u001b[0;34m(self, to_replace, value, inplace, mask, using_cow)\u001b[0m\n\u001b[1;32m    590\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[38;5;28mself\u001b[39m] \u001b[38;5;28;01mif\u001b[39;00m inplace \u001b[38;5;28;01melse\u001b[39;00m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcopy()]\n\u001b[1;32m    592\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mask \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 593\u001b[0m     mask \u001b[38;5;241m=\u001b[39m \u001b[43mmissing\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmask_missing\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mto_replace\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    594\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m mask\u001b[38;5;241m.\u001b[39many():\n\u001b[1;32m    595\u001b[0m     \u001b[38;5;66;03m# Note: we get here with test_replace_extension_other incorrectly\u001b[39;00m\n\u001b[1;32m    596\u001b[0m     \u001b[38;5;66;03m#  bc _can_hold_element is incorrect.\u001b[39;00m\n\u001b[1;32m    597\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m using_cow:\n",
+      "File \u001b[0;32m~/dev/pipenv/lib/python3.10/site-packages/pandas/core/missing.py:112\u001b[0m, in \u001b[0;36mmask_missing\u001b[0;34m(arr, values_to_mask)\u001b[0m\n\u001b[1;32m    108\u001b[0m             new_mask \u001b[38;5;241m=\u001b[39m arr \u001b[38;5;241m==\u001b[39m x\n\u001b[1;32m    110\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(new_mask, np\u001b[38;5;241m.\u001b[39mndarray):\n\u001b[1;32m    111\u001b[0m                 \u001b[38;5;66;03m# usually BooleanArray\u001b[39;00m\n\u001b[0;32m--> 112\u001b[0m                 new_mask \u001b[38;5;241m=\u001b[39m \u001b[43mnew_mask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_numpy\u001b[49m(dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mbool\u001b[39m, na_value\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m    113\u001b[0m         mask \u001b[38;5;241m|\u001b[39m\u001b[38;5;241m=\u001b[39m new_mask\n\u001b[1;32m    115\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m na_mask\u001b[38;5;241m.\u001b[39many():\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'bool' object has no attribute 'to_numpy'"
+     ]
+    }
+   ],
    "source": [
-    "### Kdb+"
+    "%%time\n",
+    "# converto to dataframe\n",
+    "df = pd.DataFrame(q(\"t\", pandas=True))\n",
+    "df.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "14f63810-1943-4e28-9bce-2148be6be02d",
-   "metadata": {},
+   "execution_count": 19,
+   "id": "0fc7f16b-6c39-4ebe-88d2-ff857e30ab62",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
-   "source": []
+   "source": [
+    "%%time\n",
+    "# select\n",
+    "df3 = q.sendSync(\"select from t\")"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3bf5e29b-fd38-4ec6-b583-f53e504073ab",
+   "id": "c88646ca-3d25-4a85-80b5-f9e559f568dd",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "q.close()"
+   ]
   }
  ],
  "metadata": {