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Solved m1-01 lab #11

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12 changes: 12 additions & 0 deletions csv_string.csv
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Original file line number Diff line number Diff line change
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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
370 changes: 370 additions & 0 deletions m1-01-ipython-python-basics-lab.ipynb
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Original file line number Diff line number Diff line change
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{
"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
}
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