{
"cells": [
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"lang": "sl"
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"source": [
"## Priprava podatkov, osnovne statistike in vizualizacija\n",
"\n",
"Podatkovno rudarjenje, naloga, 14. 3. 2025\n",
"**Gašper Dobrovoljc**"
]
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"Neizogiben del vsakega projekta na področju podatkovnega rudarjenja je iskanje,\n",
"urejanje in priprava podatkov. V tej nalogi boste spoznali primer podatkovne\n",
"zbirke in uporabili postopke za pretvorbo podatkov v ustrezno obliko ter pregled in\n",
"prikaz osnovnih statistik."
]
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"### Podatki\n",
"\n",
"V nalogi boste pregledali in pripravili podatke gledanosti Hollywoodskih filmov\n",
"zbirke [MovieLens](https://grouplens.org/datasets/movielens/) v obdobju **1995-2016**.\n",
"\n",
"Iste podatke boste uporabili v vseh nalogah, zato jih dodobra spoznajte. Gre za podatkovno zbirko za\n",
"vrednotenje priporočilnih sistemov, ki vsebuje gledalce ter njihove ocene za posamezni film na lestvici 1 do 5. \n",
"Poleg osnovne matrike uporabnikov in ocen vsebuje še dodatne podatke o filmih (npr. žanr, datum, oznake,\n",
"igralci).\n",
"\n",
"Podatki so v mapi `./podatki/ml-latest-small`. Podatkovna zbirka vsebuje naslednje datoteke:\n",
"\n",
"* ratings.csv: podatki o uporabnikih in ocenah,\n",
"* movies.csv: podatki o žanrih filmov,\n",
"* cast.csv: podatki o igralcih,\n",
"* tags.csv: podatki o oznakah (ang. \\emph{tags}),\n",
"* links.csv: povezave na sorodne podatkovne zbirke.\n",
"\n",
"\n",
"Pred pričetkom reševanja naloge si dobro oglejte podatke in datoteko **README.txt**. Podrobnosti o zbirki lahko preberete na [spletni strani](http://files.grouplens.org/datasets/movielens/ml-latest-small-README.html).\n",
"\n",
"Pripravite metode za nalaganje podatkov v ustrezne podatkovne strukture. Te vam bodo prišle\n",
"prav tudi pri nadaljnjih nalogah.\n",
"Bodite pozorni na velikost podatkov."
]
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"Zapišite kodo za branje datotek in pripravo ustreznih matrik (in drugih struktur) podatkov, ki jih boste uporabi pri odgovarjanju na spodnja vprašanja.\n",
"\n",
"Kodo lahko razdelite v več celic."
]
},
{
"metadata": {
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"end_time": "2025-04-05T14:29:28.566485Z",
"start_time": "2025-04-05T14:29:27.852608Z"
}
},
"cell_type": "code",
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"\n",
"ratings = pd.read_csv('./podatki/ml-latest-small/ratings.csv')\n",
"movies = pd.read_csv('./podatki/ml-latest-small/movies.csv')\n",
"cast = pd.read_csv('./podatki/ml-latest-small/cast.csv')\n",
"\n",
"ratings['timestamp'] = pd.to_datetime(ratings['timestamp'], unit='s')"
],
"outputs": [],
"execution_count": 1
},
{
"metadata": {
"lang": "sl"
},
"cell_type": "markdown",
"source": [
"### Vprašanja\n",
"\n",
"Glavni namen podatkovnega rudarjenja je *odkrivanje znanj iz podatkov*,\n",
"torej odgovarjanje na vprašanja z uporabo računskih postopkov.\n",
"\n",
"Z uporabo principov, ki ste jih spoznali na vajah in predavanjih, odgovorite na\n",
"spodnja vprašanja. Pri vsakem vprašanju dobro premislite, na kakšen način boste\n",
"najbolje podali, prikazali oz. utemeljili odgovor. Bistven del so odgovori na\n",
"vprašanja in ne implementacija vaše rešitve."
]
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"#### 1. vprašanje (15%):\n",
"Kateri filmi so v povprečju najbolje ocenjeni? Pripravite seznam\n",
"filmov ter njihovih povprečnih ocen in izpišite 10 filmov z vrha seznama.\n",
"Opazite pri takem ocenjevanju kakšno težavo? Kako bi jo lahko rešili? Kakšni so\n",
"rezultati tedaj?\n",
"\n",
"Kodo lahko razdelite v več celic."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-05T14:29:28.595228Z",
"start_time": "2025-04-05T14:29:28.575470Z"
}
},
"source": [
"average_ratings = ratings.groupby(['movieId'])['rating'].mean().reset_index()\n",
"\n",
"sorted_ratings = average_ratings.sort_values(by='rating', ascending=False)\n",
"\n",
"sorted_ratings.merge(movies, on='movieId').head(10)"
],
"outputs": [
{
"data": {
"text/plain": [
" movieId rating title \\\n",
"0 163949 5.0 The Beatles: Eight Days a Week - The Touring Y... \n",
"1 71180 5.0 Padre padrone (1977) \n",
"2 51471 5.0 Amazing Grace (2006) \n",
"3 52617 5.0 Woman on the Beach (Haebyeonui yeoin) (2006) \n",
"4 53887 5.0 O Lucky Man! (1973) \n",
"5 54251 5.0 Dorian Blues (2004) \n",
"6 54328 5.0 My Best Friend (Mon meilleur ami) (2006) \n",
"7 55555 5.0 Edge of Heaven, The (Auf der anderen Seite) (2... \n",
"8 56869 5.0 Drained (O cheiro do Ralo) (2006) \n",
"9 57038 5.0 To the Left of the Father (Lavoura Arcaica) (2... \n",
"\n",
" genres \n",
"0 Documentary \n",
"1 Drama \n",
"2 Drama|Romance \n",
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"4 Comedy|Drama|Fantasy|Musical \n",
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{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": "Odgovor: **Izpisani so filmi z oceno 5.0, ki imajo zelo malo ocen. To lahko rešimo s filtrom, ki ne upošteva filmov s premalo ocenami. Po uporabi filtra so filmi, ki so izpisani dobro poznani.**"
},
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"end_time": "2025-04-05T14:29:28.781014Z",
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},
"cell_type": "code",
"source": [
"minimum_ratings = 50\n",
"\n",
"ratings_count = ratings.groupby('movieId')['rating'].count().reset_index()\n",
"\n",
"popular_ratings = ratings_count[ratings_count['rating'] >= minimum_ratings]\n",
"\n",
"filtered_ratings = ratings[ratings['movieId'].isin(popular_ratings['movieId'])]\n",
"\n",
"average_ratings = filtered_ratings.groupby(['movieId'])['rating'].mean().reset_index()\n",
"\n",
"sorted_ratings = average_ratings.sort_values(by='rating', ascending=False)\n",
"\n",
"sorted_ratings.merge(movies, on='movieId').head(10)"
],
"outputs": [
{
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" movieId rating title \\\n",
"0 858 4.487500 Godfather, The (1972) \n",
"1 318 4.487138 Shawshank Redemption, The (1994) \n",
"2 969 4.420000 African Queen, The (1951) \n",
"3 913 4.387097 Maltese Falcon, The (1941) \n",
"4 1221 4.385185 Godfather: Part II, The (1974) \n",
"5 50 4.370647 Usual Suspects, The (1995) \n",
"6 1228 4.350000 Raging Bull (1980) \n",
"7 1252 4.335526 Chinatown (1974) \n",
"8 904 4.315217 Rear Window (1954) \n",
"9 1203 4.304054 12 Angry Men (1957) \n",
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{
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"metadata": {},
"source": [
"#### 2. vprašanje (15%):\n",
"Posamezni film pripada enemu ali več žanrom. \n",
"Koliko je vseh žanrov? Prikaži porazdelitev žanrov z uporabo ustrezne\n",
"vizualizacije.\n",
"\n",
"Kodo lahko razdelite v več celic."
]
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-05T14:29:29.076125Z",
"start_time": "2025-04-05T14:29:28.895988Z"
}
},
"cell_type": "code",
"source": [
"genres = movies['genres'].str.split('|').explode()\n",
"genre_counts = genres.value_counts()\n",
"\n",
"genre_counts.plot.bar(\n",
" title='Porazdelitev žanrov filmov',\n",
" xlabel='Žanr',\n",
" ylabel='Število filmov',\n",
")"
],
"outputs": [
{
"data": {
"text/plain": [
""
]
},
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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 4
},
{
"metadata": {},
"cell_type": "markdown",
"source": "Odgovor: **Vseh žanrov je 19.**"
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"#### 3. vprašanje (20%):\n",
"Število ocen (ogledov) se za posamezni film razlikuje. Ali\n",
"obstaja povezava med gledanostjo in povprečno oceno filma? Opišite postopek, ki\n",
"ste ga uporabili pri odgovarjanju na vprašanje.\n",
"\n",
"Kodo lahko razdelite v več celic."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-05T14:29:29.298337Z",
"start_time": "2025-04-05T14:29:29.159887Z"
}
},
"source": [
"average_ratings = ratings.groupby('movieId').agg(\n",
" count=('movieId', 'count'),\n",
" rating=('rating', 'mean'),\n",
")\n",
"\n",
"average_ratings.plot.scatter(\n",
" 'rating', 'count',\n",
" title='Povezava med številom ocen in povprečno oceno filma',\n",
" xlabel='Povprečna ocena',\n",
" ylabel='Število ocen',\n",
")\n",
"\n",
"correlation = average_ratings['count'].corr(average_ratings['rating'])\n",
"\n",
"print(f'Korelacija med številom ocen in povprečno oceno je {correlation}')"
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Korelacija med številom ocen in povprečno oceno je 0.13082726621823262\n"
]
},
{
"data": {
"text/plain": [
"
"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 5
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": "Odgovor: **Povezava med gledanostjo in povprečno oceno je zelo šibka. Pri odgovoru sem izračunal Pearsonovo korelacijo med številom ocen in povprečno oceno.**"
},
{
"cell_type": "markdown",
"metadata": {
"lang": "sl"
},
"source": [
"#### 4. vprašanje (30%):\n",
"Vsaka ocena je bila vnešena na določen datum (stolpec\n",
"*timestamp*). Ali se popularnost posameznih filmov s časom spreminja?\n",
"Problem reši tako, da za dani film ocene razporediš po času ter v vsaku časovni\n",
"točki izračunaš povprečje za zadnjih 30, 50, ali 100 ocen. Nariši graf, kako se\n",
"ocena spreminja in ga prikaži za dva zanimiva primera filmov.\n",
"\n",
"Kodo lahko razdelite v več celic."
]
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-05T14:29:29.499045Z",
"start_time": "2025-04-05T14:29:29.348339Z"
}
},
"cell_type": "code",
"source": [
"window_sizes = [30, 50, 100]\n",
"\n",
"def rating_history(movie_id):\n",
" movie_ratings = ratings[ratings['movieId'] == movie_id].sort_values(by='timestamp')\n",
"\n",
" for window in window_sizes:\n",
" plt.plot(\n",
" movie_ratings['timestamp'],\n",
" movie_ratings['rating'].rolling(window=window).mean(),\n",
" label=f'Povprečje zadnjih {window} ocen',\n",
" )\n",
"\n",
" plt.title(movies[movies['movieId'] == movie_id]['title'].values[0])\n",
" plt.xlabel('Datum')\n",
" plt.xticks(rotation=90)\n",
" plt.ylabel('Ocena')\n",
" plt.grid(True)\n",
" plt.legend()\n",
" plt.show()\n",
"\n",
"rating_history(858)\n",
"rating_history(318)"
],
"outputs": [
{
"data": {
"text/plain": [
"