diff --git a/playground.ipynb b/playground.ipynb
deleted file mode 100644
index f398ba1..0000000
--- a/playground.ipynb
+++ /dev/null
@@ -1,215 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import duckdb\n",
-    "import pandas as pd\n",
-    "import pyarrow.parquet as pq\n",
-    "from itertools import islice, tee\n",
-    "\n",
-    "# from src.core import Data, Reader"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "d = \"/home/anadirov/Documents/big.parquet\"\n",
-    "d2 = \"/home/anadirov/Documents/local_dwh/mp_all_offers_prod.parquet\"\n",
-    "# pd_df = pd.read_parquet(d)\n",
-    "\n",
-    "# q = f\"\"\"\n",
-    "#     create table data as select * from \"{d}\"\n",
-    "# \"\"\".strip()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = duckdb.read_parquet(d)\n",
-    "df2 = duckdb.read_parquet(d2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# parquet_file = pq.ParquetFile(d)\n",
-    "# gen = parquet_file.iter_batches(batch_size=1000)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def nth_item(generator, n):\n",
-    "    return next(islice(generator, n, n+1), None)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def count_items(generator):\n",
-    "    return sum(1 for _ in generator)\n",
-    "\n",
-    "def count_and_copy(generator):\n",
-    "    gen_copy, gen_count = tee(generator)\n",
-    "    count = sum(1 for _ in gen_count)\n",
-    "    return gen_copy, count\n",
-    "\n",
-    "\n",
-    "# count_and_copy(gen)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# r = df.query(\"data\", \"select * from data limit 10000\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# bats = r.to_arrow_table().to_batches(10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# big = Data(path = d, \n",
-    "#            virtual_table_name = \"data\", \n",
-    "#            query = \"select item_id, __index_level_0__ from data order by __index_level_0__\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from io import StringIO\n",
-    "import sys, os\n",
-    "\n",
-    "def render_df_info(duckdf: duckdb.DuckDBPyRelation) -> str:\n",
-    "    \"\"\" returns md like formatted df.info \"\"\"\n",
-    "    shape = duckdf.shape\n",
-    "\n",
-    "    output_buffer = StringIO()\n",
-    "    sys.stdout = output_buffer\n",
-    "    duckdf.describe().show(max_width=10**19)\n",
-    "    sys.stdout = sys.__stdout__\n",
-    "    descr = output_buffer.getvalue()\n",
-    "\n",
-    "    h = f\"### Rows: {shape[0]}, Columns: {shape[1]}\\n{'-'*50}\\n\"\n",
-    "    try:\n",
-    "        lines = descr.strip().split(\"\\n\")\n",
-    "        headers = lines[1].strip(\"│\").split(\"│\")\n",
-    "        headers = [header.strip() for header in headers]\n",
-    "        types = lines[2].strip(\"│\").split(\"│\")\n",
-    "        types = [t.strip() for t in types]\n",
-    "        data_lines = lines[4:-1]\n",
-    "        data = []\n",
-    "        for line in data_lines:\n",
-    "            row = line.strip(\"│\").split(\"│\")\n",
-    "            row = [item.strip() for item in row]\n",
-    "            data.append(row)\n",
-    "\n",
-    "        # Build the markdown table\n",
-    "        markdown_table = \"| \" + \" | \".join(headers) + \" |\\n\"\n",
-    "        markdown_table += \"|-\" + \"-|-\".join([\"-\" * len(header) for header in headers]) + \"-|\\n\"\n",
-    "        markdown_table += \"| \" + \" | \".join(types) + \" |\\n\"\n",
-    "        for row in data:\n",
-    "            markdown_table += \"| \" + \" | \".join(row) + \" |\\n\"\n",
-    "\n",
-    "        return h + markdown_table\n",
-    "    \n",
-    "    except Exception as e:\n",
-    "        return h\n",
-    "\n",
-    "\n",
-    "r = render_df_info(df2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": ".venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}