diff --git a/csv_string.csv b/csv_string.csv
new file mode 100644
index 0000000..4410112
--- /dev/null
+++ b/csv_string.csv
@@ -0,0 +1,12 @@
+metric , key , value 
+count, login , 3
+count, logout , 2
+count, purchase , 2
+count, video_play , 2
+count, share , 1
+avg, login , 3
+avg, logout , 4
+avg, purchase , 4
+avg, video_play , 4
+avg, share , 4
+unique_users,total , 10
\ No newline at end of file
diff --git a/m1-01-ipython-python-basics-lab.ipynb b/m1-01-ipython-python-basics-lab.ipynb
new file mode 100644
index 0000000..c0c98c1
--- /dev/null
+++ b/m1-01-ipython-python-basics-lab.ipynb
@@ -0,0 +1,370 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "id": "cb2e5530-130e-4a76-b935-e74e96acc37b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "0a58bdde-7bf1-4157-99d7-5df96dcfbf1b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " type of list object is : <class 'list'>\n",
+      " type of integer object is : <class 'int'>\n",
+      " type of float object is : <class 'float'>\n",
+      " type of dictionary object is : <class 'dict'>\n",
+      " type of string object is : <class 'str'>\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ----- TASK 1 -----\n",
+    "\n",
+    "list_object = [1,2,3]\n",
+    "integer_object = 12\n",
+    "float_object = 12.5\n",
+    "dictionary_object = {\"Name\" : \"Firuddin\" , \"Surname\" : \"Rzayev\"}\n",
+    "string_object = \"Firuddin\"\n",
+    "\n",
+    "print(f\" type of list object is : {type(list_object)}\")\n",
+    "print(f\" type of integer object is : {type(integer_object)}\")\n",
+    "print(f\" type of float object is : {type(float_object)}\")\n",
+    "print(f\" type of dictionary object is : {type(dictionary_object)}\")\n",
+    "print(f\" type of string object is : {type(string_object)}\")\n",
+    "\n",
+    "# list_object.append?\n",
+    "# Signature: list_object.append(object, /)\n",
+    "# Docstring: Append object to the end of the list.\n",
+    "# Type:      builtin_function_or_method\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "abe025a2-ecc8-45cb-949a-df1371e6d798",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " values : [1, 2, 3, 4]\n",
+      " alias : [1, 2, 3, 4]\n",
+      " values_copy : [1, 2, 3, 4, 4]\n",
+      " ------------- \n",
+      " record : [1, 2, 3, 4]\n",
+      " alias : {'Name': 'Firuddin', 'Surname': 'Rzayev'}\n",
+      " record_copy : [1, 2, 3, 4, 4]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ----- TASK 2 -----\n",
+    "\n",
+    "values = [1,2,3]\n",
+    "alias = values\n",
+    "values_copy = values.copy()\n",
+    "\n",
+    "alias.append(4)\n",
+    "values_copy.append(4)\n",
+    "values_copy.append(4)\n",
+    "\n",
+    "print(f\" values : {values}\")\n",
+    "print(f\" alias : {alias}\")\n",
+    "print(f\" values_copy : {values_copy}\")\n",
+    "\n",
+    "print(\" ------------- \" )\n",
+    "\n",
+    "record = {\"Name\" : \"Firuddin\"}\n",
+    "alias = record\n",
+    "record_copy = record.copy()\n",
+    "\n",
+    "alias.setdefault(\"Surname\",\"Rzayev\")\n",
+    "record_copy.setdefault(\"Surname\",\"Rzayev\")\n",
+    "record_copy.setdefault(\"Age\",20)\n",
+    "\n",
+    "print(f\" record : {values}\")\n",
+    "print(f\" alias : {alias}\")\n",
+    "print(f\" record_copy : {values_copy}\")\n",
+    "\n",
+    "# if we assign new value to the previous one, we will get exactly the same two variables. In contrast, copy() method creates different variable with same value or values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "1b158113-f569-414b-8156-be527d787456",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# --- TASK 4 ---\n",
+    "\n",
+    "events = [\n",
+    "    {\"user_id\" : 1 , \"event_type\" : \"login\" , \"duration_seconds\" : 100},\n",
+    "    {\"user_id\" : 2 , \"event_type\" : \"video_play\" , \"duration_seconds\" : -120},\n",
+    "     {\"user_id\" : 3 , \"event_type\" : \"logout\" , \"duration_seconds\" : 140},\n",
+    "     {\"user_id\" : 4 , \"event_type\" : \"purchase\" , \"duration_seconds\" : 160},\n",
+    "     {\"user_id\" : 5 , \"event_type\" : \"login\" , \"duration_seconds\" : 180},\n",
+    "     {\"user_id\" : 6 , \"event_type\" : \"video_play\" , \"duration_seconds\" : 200},\n",
+    "     {\"user_id\" : 7 , \"event_type\" : \"comment\" , \"duration_seconds\" : \"abc\"},\n",
+    "     {\"user_id\" : 8 , \"event_type\" : \"share\" , \"duration_seconds\" : 240},\n",
+    "     {\"user_id\" : 9 , \"event_type\" : \"video_play\" , \"duration_seconds\" : 260},\n",
+    "     {\"user_id\" : 10 , \"event_type\" : \"login\" , \"duration_seconds\" : 280},\n",
+    "     {\"user_id\" : 11 , \"event_type\" : \"logout\" , \"duration_seconds\" : 300},\n",
+    "     {\"user_id\" : 12 , \"event_type\" : \"purchase\" , \"duration_seconds\" : 320}\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "id": "a326a933-662d-49b4-a949-fe06c3d41de0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[{'user_id': 1, 'event_type': 'login', 'duration_seconds': 100, 'duration_minutes': 1.6666666666666667}, {'user_id': 3, 'event_type': 'logout', 'duration_seconds': 140, 'duration_minutes': 2.3333333333333335}, {'user_id': 4, 'event_type': 'purchase', 'duration_seconds': 160, 'duration_minutes': 2.6666666666666665}, {'user_id': 5, 'event_type': 'login', 'duration_seconds': 180, 'duration_minutes': 3.0}, {'user_id': 6, 'event_type': 'video_play', 'duration_seconds': 200, 'duration_minutes': 3.3333333333333335}, {'user_id': 8, 'event_type': 'share', 'duration_seconds': 240, 'duration_minutes': 4.0}, {'user_id': 9, 'event_type': 'video_play', 'duration_seconds': 260, 'duration_minutes': 4.333333333333333}, {'user_id': 10, 'event_type': 'login', 'duration_seconds': 280, 'duration_minutes': 4.666666666666667}, {'user_id': 11, 'event_type': 'logout', 'duration_seconds': 300, 'duration_minutes': 5.0}, {'user_id': 12, 'event_type': 'purchase', 'duration_seconds': 320, 'duration_minutes': 5.333333333333333}]\n"
+     ]
+    }
+   ],
+   "source": [
+    "cleaned_events = []\n",
+    "for i in events:\n",
+    "    if type(i[\"duration_seconds\"]) == int:\n",
+    "        if i[\"duration_seconds\"] > 0:\n",
+    "            cleaned_events.append(i)\n",
+    "\n",
+    "for i in cleaned_events:\n",
+    "    i[\"duration_minutes\"] = i[\"duration_seconds\"] / 60\n",
+    "print(cleaned_events)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "id": "6197570a-5c89-4612-b15d-cac22452fdd0",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'user_id': 1,\n",
+       "  'event_type': 'login',\n",
+       "  'duration_seconds': 100,\n",
+       "  'duration_minutes': 1.6666666666666667},\n",
+       " {'user_id': 3,\n",
+       "  'event_type': 'logout',\n",
+       "  'duration_seconds': 140,\n",
+       "  'duration_minutes': 2.3333333333333335},\n",
+       " {'user_id': 4,\n",
+       "  'event_type': 'purchase',\n",
+       "  'duration_seconds': 160,\n",
+       "  'duration_minutes': 2.6666666666666665},\n",
+       " {'user_id': 5,\n",
+       "  'event_type': 'login',\n",
+       "  'duration_seconds': 180,\n",
+       "  'duration_minutes': 3.0},\n",
+       " {'user_id': 6,\n",
+       "  'event_type': 'video_play',\n",
+       "  'duration_seconds': 200,\n",
+       "  'duration_minutes': 3.3333333333333335},\n",
+       " {'user_id': 8,\n",
+       "  'event_type': 'share',\n",
+       "  'duration_seconds': 240,\n",
+       "  'duration_minutes': 4.0},\n",
+       " {'user_id': 9,\n",
+       "  'event_type': 'video_play',\n",
+       "  'duration_seconds': 260,\n",
+       "  'duration_minutes': 4.333333333333333},\n",
+       " {'user_id': 10,\n",
+       "  'event_type': 'login',\n",
+       "  'duration_seconds': 280,\n",
+       "  'duration_minutes': 4.666666666666667},\n",
+       " {'user_id': 11,\n",
+       "  'event_type': 'logout',\n",
+       "  'duration_seconds': 300,\n",
+       "  'duration_minutes': 5.0},\n",
+       " {'user_id': 12,\n",
+       "  'event_type': 'purchase',\n",
+       "  'duration_seconds': 320,\n",
+       "  'duration_minutes': 5.333333333333333}]"
+      ]
+     },
+     "execution_count": 137,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cleaned_events"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
+   "id": "2a8c7546-de0c-43b6-8a4a-f6a27cdbf6fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'login': 3, 'logout': 2, 'purchase': 2, 'video_play': 2, 'share': 1}"
+      ]
+     },
+     "execution_count": 138,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "event_counts = {}\n",
+    "for event in cleaned_events:\n",
+    "    etype = event['event_type']\n",
+    "    event_counts[etype] = event_counts.get(etype, 0) + 1\n",
+    "event_counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "40f4ca86-bb48-4f5c-9967-a3df5431c2e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'login': 3, 'logout': 4, 'purchase': 4, 'video_play': 4, 'share': 4}\n"
+     ]
+    }
+   ],
+   "source": [
+    "duration_sums = {}\n",
+    "duration_counts = {}\n",
+    "for i in cleaned_events:\n",
+    "    i_type = i[\"event_type\"]\n",
+    "    duration = float(i[\"duration_minutes\"])\n",
+    "    duration_sums[i_type] = duration_sums.get(i_type,0) + duration\n",
+    "    duration_counts[i_type] = duration_counts.get(i_type,0) + 1\n",
+    "avg_duration_minutes = {k:round(duration_sums[k]/duration_counts[k]) for k in duration_sums}\n",
+    "print(avg_duration_minutes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "112ecf29-c8cf-4d4d-b5fc-9040fe70bcaa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "unique_users = {i[\"user_id\"] for i in cleaned_events}\n",
+    "len_unique_users = len(unique_users)\n",
+    "len_unique_users"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "d3f431d4-7019-43ec-a8ed-0ffdbbefbb57",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "metric , key , value \n",
+      "count, login , 3\n",
+      "count, logout , 2\n",
+      "count, purchase , 2\n",
+      "count, video_play , 2\n",
+      "count, share , 1\n",
+      "avg, login , 3\n",
+      "avg, logout , 4\n",
+      "avg, purchase , 4\n",
+      "avg, video_play , 4\n",
+      "avg, share , 4\n",
+      "unique_users,total , 10\n"
+     ]
+    }
+   ],
+   "source": [
+    "csv_columns = [\"metric \" , \" key \" , \" value \"]\n",
+    "header = \",\".join(csv_columns)\n",
+    "\n",
+    "final_rows = [header]\n",
+    "\n",
+    "for i_type, count in event_counts.items():\n",
+    "    final_rows.append(f\"count, {i_type} , {count}\")\n",
+    "\n",
+    "for i_type, avg in avg_duration_minutes.items():\n",
+    "    final_rows.append(f\"avg, {i_type} , {avg}\")\n",
+    "\n",
+    "final_rows.append(f\"unique_users,total , {len_unique_users}\")\n",
+    "\n",
+    "csv_string = \"\\n\".join(final_rows)\n",
+    "\n",
+    "print(csv_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "id": "04f1e672-d591-4cc6-a8e8-96d28867f13f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# csv_string dəyişənini \"summary_report.csv\" adlı fayla yazırıq\n",
+    "with open(\"csv_string.csv\", \"w\", encoding=\"utf-8\") as f:\n",
+    "    f.write(csv_string)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.13.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/m1-01-task-3-functions.py b/m1-01-task-3-functions.py
new file mode 100644
index 0000000..2966922
--- /dev/null
+++ b/m1-01-task-3-functions.py
@@ -0,0 +1,79 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0065aa78-7883-4b71-8606-9a0847876041",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.0, 2.0, 3.0, 4.0, 5.0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def lower_strip(a):\n",
+    "    b = []\n",
+    "    for x in a:\n",
+    "        if x.isdigit() == True:\n",
+    "            x = float(x)\n",
+    "            b.append(x)\n",
+    "        else:\n",
+    "            return \"None\"\n",
+    "    return b  \n",
+    "a = [\"1\",\"2\",\"3\",\"4\",\"5\"]\n",
+    "print(lower_strip(a))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "aa95bf2e-5cc6-40a4-96d8-ad95fe4f47df",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['a', 'b', 'c', 'd', 'e']\n"
+     ]
+    }
+   ],
+   "source": [
+    "def lower_strip(a):\n",
+    "    b = []\n",
+    "    for x in a:\n",
+    "        c = x.lower().strip()\n",
+    "        b.append(c)\n",
+    "    return b  \n",
+    "\n",
+    "a = [\"A \",\"B \",\"C \",\" D \",\" E\"]\n",
+    "print(lower_strip(a))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.13.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}