diff --git a/notebooks/example.ipynb b/notebooks/example.ipynb
index 0d5c9cc..98a69a2 100644
--- a/notebooks/example.ipynb
+++ b/notebooks/example.ipynb
@@ -2,15 +2,31 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading SB\n",
+      "Length of SB: 16559\n",
+      "Reading AFIB\n",
+      "Length of AFIB: 9839\n",
+      "Reading GSVT\n",
+      "Length of GSVT: 948\n",
+      "Reading SR\n",
+      "Length of SR: 9720\n"
+     ]
+    }
+   ],
    "source": [
     "import pickle\n",
     "# read pickle files and check len and print first record and first record keys\n",
     "\n",
+    "path = \"C:/Studium/dsa/data\"\n",
     "\n",
-    "categories = {\n",
+    "categories_dict = {\n",
     "'SB':    [426177001],\n",
     "'AFIB':  [164889003, 164890007],\n",
     "'GSVT':  [426761007, 713422000, 233896004, 233897008, 713422000],\n",
@@ -19,18 +35,81 @@
     "\n",
     "\n",
     "data = {}\n",
-    "for cat_name in categories.keys():\n",
+    "for cat_name in categories_dict.keys():\n",
     "    print(f\"Reading {cat_name}\")\n",
-    "    with open(f'{cat_name}.pkl', 'rb') as f:\n",
+    "    with open(f'{path}/{cat_name}.pkl', 'rb') as f:\n",
     "        records = pickle.load(f)\n",
     "        data[cat_name] = records\n",
     "        print(f\"Length of {cat_name}: {len(records)}\")"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Keys of first record of SB: dict_keys(['record_name', 'n_sig', 'fs', 'counter_freq', 'base_counter', 'sig_len', 'base_time', 'base_date', 'comments', 'sig_name', 'p_signal', 'd_signal', 'e_p_signal', 'e_d_signal', 'file_name', 'fmt', 'samps_per_frame', 'skew', 'byte_offset', 'adc_gain', 'baseline', 'units', 'adc_res', 'adc_zero', 'init_value', 'checksum', 'block_size'])\n",
+      "Number of records with p_signal: 9720\n",
+      "Number of records with e_p_signal: 0\n",
+      "Number of records with d_signal: 0\n",
+      "Number of records with e_d_signal: 0\n",
+      "{'record_name': 'JS00002', 'n_sig': 12, 'fs': 500, 'counter_freq': None, 'base_counter': None, 'sig_len': 5000, 'base_time': None, 'base_date': None, 'comments': ['Age: 59', 'Sex: Female', 'Dx: 426177001,164934002', 'Rx: Unknown', 'Hx: Unknown', 'Sx: Unknown'], 'sig_name': ['I', 'II', 'III', 'aVR', 'aVL', 'aVF', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6'], 'p_signal': array([[-0.01 ,  0.01 ,  0.02 , ...,  0.054,  0.049,  0.   ],\n",
+      "       [-0.024, -0.02 ,  0.005, ...,  0.034,  0.034, -0.015],\n",
+      "       [-0.02 , -0.02 ,  0.   , ...,  0.034,  0.034, -0.01 ],\n",
+      "       ...,\n",
+      "       [ 0.015,  0.01 , -0.005, ..., -0.015, -0.02 ,  0.005],\n",
+      "       [ 0.01 ,  0.01 ,  0.   , ..., -0.02 , -0.024,  0.   ],\n",
+      "       [ 0.01 ,  0.01 ,  0.   , ..., -0.024, -0.029, -0.005]]), 'd_signal': None, 'e_p_signal': None, 'e_d_signal': None, 'file_name': ['JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat', 'JS00002.mat'], 'fmt': ['16', '16', '16', '16', '16', '16', '16', '16', '16', '16', '16', '16'], 'samps_per_frame': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 'skew': [None, None, None, None, None, None, None, None, None, None, None, None], 'byte_offset': [24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24], 'adc_gain': [1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0], 'baseline': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'units': ['mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV', 'mV'], 'adc_res': [16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16], 'adc_zero': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'init_value': [-10, 10, 20, 0, -15, 15, -10, -54, 63, 54, 49, 0], 'checksum': [12346, 26962, 14528, -13537, -6991, 14569, -383, 16468, -29512, -7548, -22267, 31542], 'block_size': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# print keys of first record\n",
+    "print(f\"Keys of first record of SB: {data['SB'][0].__dict__.keys()}\")\n",
+    "\n",
+    "counter_p = 0\n",
+    "counter_e_p = 0\n",
+    "counter_d = 0\n",
+    "counter_e_d = 0\n",
+    "for record in data['SR']:\n",
+    "    if record.p_signal is not None:\n",
+    "        counter_p += 1\n",
+    "    if record.e_p_signal is not None:\n",
+    "        counter_e_p += 1\n",
+    "    if record.d_signal is not None:\n",
+    "        counter_d += 1\n",
+    "\n",
+    "print(f\"Number of records with p_signal: {counter_p}\")\n",
+    "print(f\"Number of records with e_p_signal: {counter_e_p}\")\n",
+    "print(f\"Number of records with d_signal: {counter_d}\")\n",
+    "print(f\"Number of records with e_d_signal: {counter_e_d}\")\n",
+    "\n",
+    "\n",
+    "print(data['SB'][0].__dict__)"
+   ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
   }
  },
  "nbformat": 4,