5 - content-based filtering - plot description.ipynb

{
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   "cell_type": "markdown",
   "id": "10240dc1",
   "metadata": {},
   "source": [
    "<center>\n",
    "    <h1 id='content-based-filtering' style='color:#7159c1; font-size:350%'>Content-Based Filtering</h1>\n",
    "    <i style='font-size:125%'>Recommendations of Similar Items by Plot Description</i>\n",
    "</center>\n",
    "\n",
    "> **Topics**\n",
    "\n",
    "```\n",
    "- ✨ Content-Based Filtering\n",
    "- ✨ Word Cloud\n",
    "- ✨ Cosine Similarity\n",
    "- ✨ Bag of Words\n",
    "- ✨ Token and N-Grams\n",
    "- ✨ Stemming and Lemmatization\n",
    "- ✨ Stop Words\n",
    "- ✨ ZIPF's Law\n",
    "- ✨ Term Frequency - Inverse Document Frequency (TF-IDF)\n",
    "- ✨ Hands-on\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a58a5716",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Imports ----\n",
    "import matplotlib.pyplot as plt             # pip install matplotlib\n",
    "import mplcyberpunk                         # pip install mplcyberpunk\n",
    "import numpy as np                          # pip install numpy\n",
    "import pandas as pd                         # pip install pandas\n",
    "import seaborn as sns                       # pip install seaborn\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer  # pip install sklearn\n",
    "from sklearn.metrics.pairwise import linear_kernel           # pip install sklearn\n",
    "import string                               # pip install string\n",
    "from wordcloud import WordCloud             # pip install wordcloud\n",
    "\n",
    "# ---- Pre-Trained Models ----\n",
    "#\n",
    "# pip install -U pip setuptools wheel\n",
    "# pip install -U spacy\n",
    "# python -m spacy download en_core_web_sm >> efficiency (English Model)\n",
    "# python -m spacy download en_core_web_trf >> accuracy (English Model)\n",
    "#\n",
    "import spacy\n",
    "spacy_english_efficiency_model = spacy.load(\"en_core_web_sm\")\n",
    "\n",
    "# ---- Constants ----\n",
    "DATASETS_PATH = ('./datasets')\n",
    "SEED = (20231223)\n",
    "\n",
    "# ---- Settings ----\n",
    "np.random.seed(SEED)\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_colwidth', None)\n",
    "sns.set_style('darkgrid')\n",
    "plt.style.use('cyberpunk')\n",
    "\n",
    "# ---- Functions ----\n",
    "def transform_synopsis(synopsis):\n",
    "    \"\"\"\n",
    "    \\ Description:\n",
    "        - transforms a string into Spacy Document;\n",
    "        - creates a list containing all non-stop words' and non-proper nouns words\n",
    "        lemma from the document;\n",
    "        - returns the list words concatenated.\n",
    "    \n",
    "    \\ Parameters:\n",
    "        - synopsis: string.\n",
    "    \"\"\"\n",
    "    document = spacy_english_efficiency_model(synopsis)\n",
    "    transformed_text = [token.lemma_ for token in document if not token.is_stop and token.pos_ != 'PROPN']\n",
    "    return ' '.join(transformed_text)\n",
    "\n",
    "def transform_duplicated_titles(duplicated_titles_list):\n",
    "    \"\"\"\n",
    "    \\ Description:\n",
    "        - passes through each element from the parameter;\n",
    "        \n",
    "        - if title is into 'title_count' element:\n",
    "            - 'title_count' is increased by 1 for the current title;\n",
    "            - current title is updated by adding a number to the end;\n",
    "            - the number addition starts from 2, that is, from the first repetition of the current title.\n",
    "            \n",
    "        - if title is not into 'title_count':\n",
    "            - title is inserted into 'title_count' with count equals to 1;\n",
    "            - the current title is returned as is;\n",
    "    \n",
    "    \\ Parameters:\n",
    "        - duplicated_titles_list: list of strings.\n",
    "    \"\"\"\n",
    "    title_count = {}\n",
    "    result = []\n",
    "\n",
    "    for title in duplicated_titles_list:\n",
    "        if title in title_count:\n",
    "            title_count[title] += 1\n",
    "            result.append(f'{title} {title_count[title]}')\n",
    "        else:\n",
    "            title_count[title] = 1\n",
    "            result.append(title)\n",
    "    return result\n",
    "\n",
    "def get_recommendations(dataset, title, animes_indices, cosine_similarity, number_recommendations=10):\n",
    "    \"\"\"\n",
    "    \\ Description:\n",
    "        - gets the index of the anime that matches the title;\n",
    "        - gets the pairwise similarity scores of all animes with the chosen anime;\n",
    "        - sort the animes based on the similarity socres on descending order;\n",
    "        - gets the scores of the top 'number_recommendations' animes, excluding the chosen one;\n",
    "        - gets the animes indices;\n",
    "        - returns the recommended animes id, title, score, genre, is hentai flag and image url.\n",
    "    \n",
    "    \\ Parameters:\n",
    "        - dataset: Pandas DataFrame;\n",
    "        - title: string;\n",
    "        - animes_indices: list of integers;\n",
    "        - cosine_similarity: NumPy array of floats;\n",
    "        - number_recommendation: integer.\n",
    "    \"\"\"\n",
    "    index = animes_indices[title]\n",
    "    \n",
    "    similarity_scores = list(enumerate(cosine_similarity[index]))\n",
    "    similarity_scores = sorted(similarity_scores, key=lambda score: score[1], reverse=True)\n",
    "    similarity_scores = similarity_scores[1:number_recommendations+1]\n",
    "    \n",
    "    recommended_animes_indices = [index[0] for index in similarity_scores]\n",
    "    recommended_animes_scores = [index[1] for index in similarity_scores]\n",
    "    \n",
    "    recommendations_df = dataset.iloc[recommended_animes_indices][\n",
    "        ['id', 'title', 'score', 'genres', 'is_hentai', 'image_url']\n",
    "    ].set_index('id')\n",
    "    recommendations_df['cosine_similarity'] = recommended_animes_scores\n",
    "    \n",
    "    return recommendations_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b94bb95f",
   "metadata": {},
   "source": [
    "<h1 id='0-content-based-filtering' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Content-Based Filtering</h1>\n",
    "\n",
    "`Content-Based Filtering` recommends animes that are similar to other animes that a user liked. If you use Netflix, you probably already stumbled upon to some series marked as `Because you added ...`. If that's so, congrats, that is a real-world Content-Based Filtering Recommendation!! To make things even clearer, assume that a user liked Dragon Ball Z on a stream platform and it uses Content-Based Filtering to recommend the animes. Guess what? The platform will probably recommend Dragon Ball Super or Naruto to the very user, because both animes are similar to Dragon Ball Z, that is, both animes are shounen with superpowers.\n",
    "\n",
    "Besides, this Filtering has two modes: 1) `Plot Description Based`, where the synopsis and/or overview are used to identify similar items; and 2) `Metadata Based`, where information about genres, producers, studios, format and so on are used to identify similar items.\n",
    "\n",
    "About the advantages:\n",
    "\n",
    "> **Better Recommendations** - `since it recommends different animes to the users accordingly to similar animes watched by them, it makes better recommendations when compared to Demographic Filtering`;\n",
    "\n",
    "> **Personalized Recommendations** - `each user receives personalized recommendations accordingly to the animes they watched`;\n",
    "\n",
    "> **Variation of Metrics** - `since there are more than one evaluation metric available, the model can be improved just by replacing the metric`.\n",
    "\n",
    "<br />\n",
    "\n",
    "Disadvantages-wise:\n",
    "\n",
    "> **More Data Required** - `in order to recommend similar items, more detailed data about the animes are needed`;\n",
    "\n",
    "> **Only Sequels and Prequels Recommendations** - `when dealing with Plot Description Based, there is a high probability to get only sequels and prequels recommendations, since they have a very similar synopsis`;\n",
    "\n",
    "> **Bubble of Contents** - `when dealing with Metadata Based, there is a high probability to create a Bubble that only recommends animes with an especific genre and topic`.\n",
    "\n",
    "<br />\n",
    "\n",
    "The image below ilustrates how this technique works:\n",
    "\n",
    "<br />\n",
    "\n",
    "<figure style='text-align:center'>\n",
    "    <img style='border-radius:20px' src='./assets/1-content-based-filtering.png' alt='Content-Based Filtering Diagram' />\n",
    "    <figcaption>Figure 1 - Content-Based Filtering Diagram. By <a href='https://medium.com/mlearning-ai/content-based-recommender-system-using-nlp-445ebb777c7a'>Arif Zainurrohman - Content-Based Recommender System Using NLP©</a>.</figcaption>\n",
    "</figure>\n",
    "\n",
    "<br /><br />\n",
    "\n",
    "In this notebook, we are going to dive into Plot Description Based technnique and consider Cosine Similarity as the Evaluation Metric."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f40ea701",
   "metadata": {},
   "source": [
    "<h1 id='1-word-cloud' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Word Cloud</h1>\n",
    "\n",
    "`Word Cloud` is a great technique to stand out the most frequent terms from Sequential Texts. In a simplier way, it shows the most frequent words from a bunch of texts.\n",
    "\n",
    "Since we are dealing with Plot Description Based mode, let's plot the Word Cloud of Animes Synopsis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4ac37932",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Reading Dataset ----\n",
    "animes_df = pd.read_csv(f'{DATASETS_PATH}/anime-transformed-dataset-2023.csv', index_col='id')[\n",
    "    ['title', 'score', 'genres', 'is_hentai', 'synopsis', 'image_url']\n",
    "]\n",
    "\n",
    "# ---- Removing Animes without Synopsis ----\n",
    "animes_df = animes_df.loc[animes_df.synopsis != '-']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1f75df65",
   "metadata": {},
   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ---- Plotting Word Cloud ----\n",
    "synopsis_text = ' '.join(animes_df.synopsis)\n",
    "\n",
    "synopsis_word_cloud = WordCloud(\n",
    "    collocations=False # only consider words as unigrams, example, 'Dragon Ball' is considered as two words: 'Dragon' and 'Ball'\n",
    "    , background_color='black'\n",
    "    , colormap='Purples'\n",
    "    , width=2048\n",
    "    , height=1080\n",
    "    , random_state=SEED\n",
    ").generate(synopsis_text)\n",
    "\n",
    "plt.figure(facecolor='k')\n",
    "plt.imshow(synopsis_word_cloud)\n",
    "plt.tight_layout(pad=0)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cdb4626",
   "metadata": {},
   "source": [
    "The bigger the word font, the more frequent the word is on animes' synopsis. Thus, we can conclude most of synopsis contains words like `world, one, source, girl, school, will, new, year, time...`.\n",
    "\n",
    "Nonetheless, even though Word Clouds are very useful getting an overview about the words frequencies, it is not appropriate on recommendation models. On these ones, we have to use more refined techniques to find similar items. For now, let's explain about the chosen Evaluation Metric: `Cosine Similarity`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df9d38bf",
   "metadata": {},
   "source": [
    "<h1 id='2-cosine-similarity' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Cosine Similarity</h1>\n",
    "\n",
    "`Cosine Similarity` is a perfect metric to measure the similarity between two values of a same feature, especially when dealing with sequential texts. In a nutshell, it works dividing the sum of the multiplication of the frequency of the elements in each items by the product of the squared root of the quadratic appearance of each element into the items 🤯😶‍🌫️. You can be wondering: *What the hell did I just read?*. Do not worry, The example below makes everything clear 🤣\n",
    "\n",
    "Consider these two sentences: `Hello World!` (sentence A) and `Hello!` (sentence B). The first thing to do is to create a table showing the frequency of each word in each sentence:\n",
    "\n",
    "<table style='border-style: solid'>\n",
    "    <caption>Frequency Table of Each Word in Each Sentence</caption>\n",
    "    <tr align='center' style='border-style: solid'>\n",
    "        <th style='border-style: solid'>Word</th>\n",
    "        <th style='border-style: solid'># in A</th>\n",
    "        <th style='border-style: solid'># in B</th>\n",
    "    </tr>\n",
    "    <tr align='center'>\n",
    "        <td style='border-style: solid'><b>Hello</b></td>\n",
    "        <td style='border-style: solid'>1</td>\n",
    "        <td style='border-style: solid'>1</td>\n",
    "    </tr>\n",
    "    <tr align='center'>\n",
    "        <td style='border-style: solid'><b>World</b></td>\n",
    "        <td style='border-style: solid'>1</td>\n",
    "        <td style='border-style: solid'>0</td>\n",
    "    </tr>\n",
    "</table>\n",
    "\n",
    "After that, we: \n",
    "\n",
    "- plot the frequencies using points;\n",
    "- trace two lines across the points, one line for each point; \n",
    "- calculate the angle between the lines;\n",
    "- calculate the cosine of the angle;\n",
    "- the cosine of the angle is the Cosine Similarity Score. It goes from 0 (completely not similar) to 1 (completely similar).\n",
    "\n",
    "In this example, the angle between the lines is `45º` and its cosine is `0.71`, thus we can tell that both sentences are 71% similar. The image below ilustrates the plot and the calculation:\n",
    "\n",
    "<br />\n",
    "\n",
    "<figure style='text-align:center'>\n",
    "    <img style='border-radius:20px' src='./assets/3-cosine-similarity-statquest.png' alt='Cosine Similarity of the Example' />\n",
    "    <figcaption style='text-align: center'>Figure 2 - Cosine Similarity calculation of sentences in the example. By <a href='https://www.youtube.com/watch?v=e9U0QAFbfLI'>StatQuest with Josh Starmer - Cosine Similarity, Clearly Explained!!!©</a>, at 03:34 minutes.</figcaption>\n",
    "</figure>\n",
    "\n",
    "<br /><br />\n",
    "\n",
    "Quite simple and easy to catch, isn't it? You can check out a better explanation about this topic accessing the StatQuest YouTube video here: [StatQuest with Josh Starmer - Cosine Similarity, Clearly Explained!!!](https://www.youtube.com/watch?v=e9U0QAFbfLI).\n",
    "\n",
    "Just one more thing, the frequency does not have influence in the similarity, only the presence or not presence have influence. It means that the sentences `Hello!` and `Hello! Hello! Hello!` have the same Cosine Similarity to `Hello World!`, since the angle between the lines is still 45º. The image below ilustrates it:\n",
    "\n",
    "<br />\n",
    "\n",
    "<figure style='text-align:center'>\n",
    "    <img style='border-radius:20px' src='./assets/4-cosine-similarity-statquest.png' alt='Cosine Similarity of the Example' />\n",
    "    <figcaption style='text-align: center'>Figure 3 - Cosine Similarity calculation of the new example. By <a href='https://www.youtube.com/watch?v=e9U0QAFbfLI'>StatQuest with Josh Starmer - Cosine Similarity, Clearly Explained!!!©</a>, at 04:24 minutes.</figcaption>\n",
    "</figure>\n",
    "\n",
    "<br /><br />\n",
    "\n",
    "When dealing with only two words, there is no problem, we can plot it using two axis: x-axis and y-axis. When dealing with three words, there is no problem too, we can plot it adding a third axis: z-axis. But, with four or more words, this task becomes tough, because we have no idea how to plot four and more dimensional plots. A simple synopsis can have more than a 100 words. Can you imagine how a 100 dimensional plot would look like? I am sure that even the Scientists have no clue about it.\n",
    "\n",
    "Fortunately, we can replace the plot task by applying the Cosine Similarity Equation given below:\n",
    "\n",
    "```python\n",
    "sum(A[i] * B[i]) / (sqrt(sum(A[i]**2)) * sqrt(sum(B[i]**2)))\n",
    "```\n",
    "\n",
    "<br />\n",
    "\n",
    "$$\n",
    "Cosine Similarity = \\frac{\\sum_{i=1}^{n} (A[i] \\cdot B[i] \\cdot C[i])} {\\sqrt{\\sum_{i=1}^{n} (A[i]^2)} \\cdot \\sqrt{\\sum_{i=1}^{n} (B[i]^2)} \\cdot \\sqrt{\\sum_{i=1}^{n} (C[i]^2)}}\n",
    "$$\n",
    "\n",
    "<br />\n",
    "\n",
    "where:\n",
    "\n",
    "- A, B and C: items;\n",
    "- n: number of different elements into the items;\n",
    "- A[i]: number of times the element \"i\" is present into item A;\n",
    "- B[i]: number of times the element \"i\" is present into item B;\n",
    "- C[i]: number of times the element \"i\" is present into item C;\n",
    "- [...];\n",
    "- N[i]: number of times the element \"i\" is present into item N."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d066150e",
   "metadata": {},
   "source": [
    "<h1 id='3-bag-of-words' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Bag of Words</h1>\n",
    "\n",
    "Before applying Cosine Similarity, we first have to create the `Bag of Words`, that is, group all synopsis words together. So, assuming the sentence `Dragon Ball Series is a peak show!` is an anime synopsis, its Bag of Words would look like this:\n",
    "\n",
    "```python\n",
    "synopsis = ['Dragon Ball Series is a peak show!']\n",
    "bag_of_words = ['dragon', 'ball', 'series', 'is', 'a', 'peak', 'show']\n",
    "```\n",
    "\n",
    "Realize that, in this especific example, each word is an element of a list and, if duplicated words are present, the term would appear only once. Besides, it is a best practice removing all punctuations - commas, question marks, exclamation marks and so on - and to lower casing all texts."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d9947c6",
   "metadata": {},
   "source": [
    "<h1 id='4-token-and-n-grams' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ |Token and N-Grams</h1>\n",
    "\n",
    "We have seem earlier that each word is an element of the Bag of Words for that especific example, but there are many of situations that the element can be a combination of n-words or even only a partial slice of the word.\n",
    "\n",
    "Thus, before creating the Bag of Words, we have to define the `Tokens` pattern. Tokens are, literatelly, the proper given name for Bag of Words elements in Natural Language Processing (NLP).\n",
    "\n",
    "Tokens patterns are called `N-Grams`, where each gram identify how many terms compose the token. The main patterns are `Unigram, Bigram and Trigram`, being:\n",
    "\n",
    "<br />\n",
    "\n",
    "> **Unigram** - `token is composed by a single word`;\n",
    "\n",
    "> **Bigram** - `token is composed by a combination of two words`;\n",
    "\n",
    "> **Trigram** - `token is composed by a combination of three words`.\n",
    "\n",
    "<br />\n",
    "\n",
    "So, for `Dragon Ball Series is a peak show!` synopsis, the Bag of Words would look like this for each pattern:\n",
    "\n",
    "\n",
    "```python\n",
    "unigram = ['dragon', 'ball', 'series', 'is', 'a', 'peak', 'show']\n",
    "bigram = ['dragon ball', 'ball series', 'series is', 'is a', 'a peak', 'peak show']\n",
    "trigram = ['dragon ball series', 'ball series is', 'series is a', 'is a peak', 'a peak show']\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74c701c9",
   "metadata": {},
   "source": [
    "<h1 id='5-stemming-and-lemmatization' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Stemming and Lemmatization</h1>\n",
    "\n",
    "In order to reduce the size of Bag of Words, techniques can applied in order to reduce words and consequently, resulting in many words being replaced by a single reduction, a smaller Bag and a smaller computational cost and time over Cosine Similarity calculations. The main techniques of this kind are `Stemming` and `Lemmatization` .\n",
    "\n",
    "`Stemming` is a way to reduce words to their stem - if you remember your English classes on school, you will probably remember the contents about Stemming too -. For example, the words 'programming', 'programmer', and 'programs' can all be reduced down to the common word stem 'program'. In a nutshell, these three words can be represented by only one: 'program'.\n",
    "\n",
    "Advantages:\n",
    "\n",
    "> **Smaller Bag of Words** - `it reduces the number of unique words into the Bag of Words and, consequently, the computational cost and time to calculate the Cosine Similarity`;\n",
    "\n",
    "> **Grouping Similar Words** - `since many words have the same stem, they can be replaced by a single common word`;\n",
    "\n",
    "> **Easy to Understand** - `word stems are easier to understand when compared to word lemmas`.\n",
    "\n",
    "<br />\n",
    "\n",
    "Disadvantages-wise:\n",
    "\n",
    "> **Overstemming or False Positives** - `words with complete different meanings can have the same stem and, consequently, they will be replaced by a single word and interpreted as synonym. For instance, 'universal', 'university' and 'universe' stem is 'univers', even thoug having complete different meanings`;\n",
    "\n",
    "> **Understemming of False Negatives** - `in the other hand, words with similar meanings can have different stem and, consequently, they will be replaced by different words and not interpreted as synonyms. For instance, 'alumnus', 'alumnae' and 'alumni' does not have the same stem, even though having similar meanings`;\n",
    "\n",
    "> **Language Challenges** - `the stemming logic changes for each language, taking the morphology, spelling and character encoding into consideration and, conseequently, demanding more sofisticated algorithms and computations costs`.\n",
    "\n",
    "<br />\n",
    "\n",
    "`Lemmatization` is an alternative for Stemming that, instead of reducing words to their stems, it reduces them to their lemma (dictionary form). Also, it takes the word meaning in the whole sentence and context into consideration to reduce it. For example, 'runs', 'running', and 'ran' would be reduced to their dictionary form 'run'.\n",
    "\n",
    "Advantages:\n",
    "\n",
    "> **Accuracy** - `since it takes the word meaning in the whole sentence and context, the reductions are more accurate for recommendation models`.\n",
    "\n",
    "<br />\n",
    "\n",
    "Disadvantages-wise:\n",
    "\n",
    "> **Hard to Understand** - `word lemmas are harder to understand when compared to word stems`;\n",
    "\n",
    "> **Computational Cost and Time** - `compared to Stemming, Lemmatization is a slow and time-consuming process due to its morphological analysis and word meaning derivation from its dictionary form`.\n",
    "\n",
    "<br />\n",
    "\n",
    "We are going to apply Lemmatization in both notebooks about Content-Based Filtering!!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b2856f1",
   "metadata": {},
   "source": [
    "<h1 id='6-stop-words' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Stop Words</h1>\n",
    "\n",
    "On 'Dragon Ball Series is a peak show!' sentence, the word 'a' does not give so much information about the sentence context, that is, if we remove it, the sentence meaning and context would remain the same.\n",
    "\n",
    "These words that do not affect the sentence meaning and context at all are known as `Stop Words` and they are commonly discarded from Bag of Words and Word Vectors due to their tendency to give noise to the data.\n",
    "\n",
    "Thus, our earlier Bag of Words would look like this after dropping its Stop Words:\n",
    "\n",
    "```python\n",
    "previous_bag_of_words = ['dragon', 'ball', 'series', 'is', 'a', 'peak', 'show']\n",
    "current_bag_of_words = ['dragon', 'ball', 'series', 'is', 'peak', 'show']\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8fa6cad",
   "metadata": {},
   "source": [
    "<h1 id='7-zipfs-law' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | ZIPF's Law</h1>\n",
    "\n",
    "`ZIPF's Law` tells that some things have high frequency and are popular, whereas others does not have high frequencies and are not popular neither, and there is a pattern that shows their frequency and popularity.\n",
    "\n",
    "For our animes synopsis scenario, some words appear a lot of times in different synopsis, so, consequently, they have high frequencies and are popular; in the other side of the coin, some words have low frequencies and are unpopular. Accordingly to ZIPF's Law, the most common word appears around twice as often as the second most common word, three times as often as the third one, and so on.\n",
    "\n",
    "In order to apply this Law for Sequential Texts, we have to use `Term Frequency - Inverse Document Frequency` technique."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cb22537",
   "metadata": {},
   "source": [
    "<h1 id='8-term-frequency-inverse-document-frequency-tf-idf' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Term Frequency - Inverse Document Frequency (TF-IDF)</h1>\n",
    "\n",
    "`Term Frequency - Inverse Document Frequency (TF-IDF)` applies ZIPF's Law on texts affirming that the word importance for a text is influenced by two things:\n",
    "\n",
    "<br />\n",
    "\n",
    "> **The Word Frequency in the Text** - `the more frequent the word is, the higher is its importance for the text`;\n",
    "\n",
    "> **The Word Frequency in other Texts** - `the more texts the word appears, the lower is its importance for an especific text`.\n",
    "\n",
    "<br />\n",
    "\n",
    "Let's dive into a simple example about the usage of TF-IDF where we want to measure the 'fox' word importance in the following two sentences:\n",
    "\n",
    "- A quick brown fox jumps over a lazy dog. What a fox!\n",
    "\n",
    "- A quick brown fox jumps over a lazy fox. What a fox!\n",
    "\n",
    "Steps:\n",
    "\n",
    "1. Calculate the Term Frequency (TF) of 'fox' for each document. The idea is to divide the word frequency by the total number of words in the document:\n",
    "\n",
    "$$\n",
    "\\text{TF('fox', first_sentence)} = \\frac{2}{12} = 0.17\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\text{TF('fox', second_sentence)} = \\frac{3}{12} = 0.25\n",
    "$$\n",
    "\n",
    "<br />\n",
    "\n",
    "2. Calculate the Inverse Document Frequency (IDF) of 'fox' in the whole set of documents. The IDF is a constant for each word in the whole document and it is given by calculating the log of the total number of documents divided by the number of documents that contain the word. The log base can be any value, being 2, 10 and e the most common ones. For this example, let's consider 10 as the log base:\n",
    "\n",
    "$$\n",
    "\\text{IDF('fox', all_documents)} = \\log_{10} \\frac{2}{2} = 0\n",
    "$$\n",
    "\n",
    "3. Calculate the Term Frequency - Inverse Document Frequency (TF-IDF) of 'fox' for each sentence. The TF-IDF is calculated by multiplying the TF by the IDF value:\n",
    "\n",
    "$$\n",
    "\\text{TF-IDF('fox', first_sentence)} = TF \\cdot IDF = 0.17 \\cdot 0 = 0\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\text{TF-IDF('fox', second_sentence)} = TF \\cdot IDF = 0.25 \\cdot 0 = 0\n",
    "$$\n",
    "\n",
    "4. Get the 'fox' importance for the sentences. Since the TF-IDF for the word in both sentences is zero, 'fox' is not so much important to differentiate both sentences!! Besides, considering that the TF-IDF value is the same for both sentences, 'fox' is equally relevant for both documents.\n",
    "\n",
    "<br />\n",
    "\n",
    "The image below illustrates the example:\n",
    "\n",
    "<figure style='text-align:center'>\n",
    "    <img style='border-radius:20px' src='./assets/15-tf-idf.png' alt='Calculation of TF-IDF of two sentences' />\n",
    "    <figcaption style='text-align: center'>Figure 4 - Calculation of TF-IDF of two sentences. By <a href='https://www.youtube.com/watch?v=vZAXpvHhQow'>\n",
    "Data Science Garage - Calculate TF-IDF in NLP (Simple Example)©</a>, at 07:14 minutes.</figcaption>\n",
    "</figure>\n",
    "\n",
    "<br /> <br />"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "354ac04e",
   "metadata": {},
   "source": [
    "<h1 id='9-hands-on' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>✨ | Hands-on</h1>\n",
    "\n",
    "Now that we have all required knowledgments, let's go to the hands-on and create a Recommendation Model using Content-Based Filtering for Plot Description logic. Here, we are going to follow ten steps:\n",
    "\n",
    "1. lower case all synopsis;\n",
    "2. remove all break lines characters (\\n) and other special characters (\\t \\r \\x0b \\x0c) replacing them by spaces;\n",
    "3. remove all punctuations;\n",
    "4. remove all Stop Words and Proper Nouns;\n",
    "5. apply Lemmatization;\n",
    "6. calculate Term Frequency - Inverse Document Frequency with unigrams as tokens pattern;\n",
    "7. calculate Cosine Similarity;\n",
    "8. deal with duplicated titles;\n",
    "9. create a search function to find anime titles with given words;\n",
    "10. testing the recommendation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58775ccf",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Lower Casing, Removing All Break Lines, Removing All Special Characters and Removing All Punctuations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "857a70c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Lower Casing ----\n",
    "animes_df.synopsis = animes_df.synopsis.apply(lambda synopsis: synopsis.lower())\n",
    "\n",
    "# ---- Removing All Break Lines (\\n) and Special Characters (\\t \\t \\x0b \\x0c) ----\n",
    "animes_df.synopsis = animes_df.synopsis.apply(lambda synopsis: ' '.join(synopsis.split()))\n",
    "\n",
    "# Removing All Punctuations ----\n",
    "#\n",
    "# - 'replace' method: replaces a character by another one;\n",
    "# - 'translate' method: replaces a buch of characters by a single one;\n",
    "# - 'str.maketrans' method parameters:\n",
    "#    \\ third parameter: characters to be replaced;\n",
    "#    \\ first parameter: characters that will replace the third parameter;\n",
    "#    \\ second parameter: characters that will replace the first parameter.\n",
    "#\n",
    "animes_df.synopsis = animes_df.synopsis.apply(lambda synopsis: synopsis.translate(str.maketrans('', '', string.punctuation)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8bb9fb1",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Removing Stop Words, Removing Proper Nouns and Lemmatizating**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d2e8bcb3",
   "metadata": {},
   "outputs": [
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       "      <td>0</td>\n",
       "      <td>crime is timeless by the year 2071 humanity has expanded across the galaxy filling the surface of other planets with settlements like those on earth these new societies are plagued by murder drug use and theft and intergalactic outlaws are hunted by a growing number of tough bounty hunters spike spiegel and jet black pursue criminals throughout space to make a humble living beneath his goofy and aloof demeanor spike is haunted by the weight of his violent past meanwhile jet manages his own troubled memories while taking care of spike and the bebop their ship the duo is joined by the beautiful con artist faye valentine odd child edward wong hau pepelu tivrusky iv and ein a bioengineered welsh corgi while developing bonds and working to catch a colorful cast of criminals the bebop crews lives are disrupted by a menace from spikes past as a rivals maniacal plot continues to unravel spike must choose between life with his newfound family or revenge for his old wounds</td>\n",
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       "      <td>another day another bounty—such is the life of the often unlucky crew of the bebop however this routine is interrupted when faye who is chasing a fairly worthless target on mars witnesses an oil tanker suddenly explode causing mass hysteria as casualties mount due to a strange disease spreading through the smoke from the blast a whopping three hundred million woolong price is placed on the head of the supposed perpetrator with lives at stake and a solution to their money problems in sight the bebop crew springs into action spike jet faye and edward followed closely by ein split up to pursue different leads across alba city through their individual investigations they discover a coverup scheme involving a pharmaceutical company revealing a plot that reaches much further than the ragtag team of bounty hunters could have realized</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1439/93480.jpg</td>\n",
       "      <td>day bounty — life unlucky crew bebop routine interrupt faye chase fairly worthless target mar witness oil tanker suddenly explode cause mass hysteria casualty strange disease spread smoke blast whopping million woolong price place head suppose perpetrator life stake solution money problem sight bebop crew spring action spike jet faye edward follow closely split pursue different lead alba city individual investigation discover coverup scheme involve pharmaceutical company reveal plot reach ragtag team bounty hunter realize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>trigun</td>\n",
       "      <td>8.22</td>\n",
       "      <td>adventure, action, sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>vash the stampede is the man with a 60000000000 bounty on his head the reason hes a merciless villain who lays waste to all those that oppose him and flattens entire cities for fun garnering him the title the humanoid typhoon he leaves a trail of death and destruction wherever he goes and anyone can count themselves dead if they so much as make eye contact—or so the rumors say in actuality vash is a huge softie who claims to have never taken a life and avoids violence at all costs with his crazy doughnut obsession and buffoonish attitude in tow vash traverses the wasteland of the planet gunsmoke all the while followed by two insurance agents meryl stryfe and milly thompson who attempt to minimize his impact on the public but soon their misadventures evolve into lifeordeath situations as a group of legendary assassins are summoned to bring about suffering to the trio vashs agonizing past will be unraveled and his morality and principles pushed to the breaking point</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/7/20310.jpg</td>\n",
       "      <td>vash stampede man 60000000000 bounty head reason s merciless villain lay waste oppose flatten entire city fun garner title humanoid typhoon leave trail death destruction go count dead eye contact — rumor actuality vash huge softie claim take life avoid violence cost crazy obsession buffoonish attitude tow vash traverse wasteland planet gunsmoke follow insurance agent meryl stryfe milly thompson attempt minimize impact public soon misadventure evolve lifeordeath situation group legendary assassin summon bring suffer trio agonizing past unravel morality principle push breaking point</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>witch hunter robin</td>\n",
       "      <td>7.25</td>\n",
       "      <td>mystery, supernatural, action, drama</td>\n",
       "      <td>0</td>\n",
       "      <td>robin sena is a powerful craft user drafted into the stnj—a group of specialized hunters that fight deadly beings known as witches though her fire power is great shes got a lot to learn about her powers and working with her cool and aloof partner amon but the truth about the witches and herself will leave robin on an entirely new path that she never expected source funimation</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/10/19969.jpg</td>\n",
       "      <td>powerful craft user draft stnj — group specialized hunter fight deadly being know witch fire power great s get lot learn power work cool aloof partner amon truth witch leave robin entirely new path expect source funimation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>bouken ou beet</td>\n",
       "      <td>6.94</td>\n",
       "      <td>adventure, supernatural, fantasy</td>\n",
       "      <td>0</td>\n",
       "      <td>it is the dark century and the people are suffering under the rule of the devil vandel who is able to manipulate monsters the vandel busters are a group of people who hunt these devils and among them the zenon squad is known to be the strongest busters on the continent a young boy beet dreams of joining the zenon squad however one day as a result of beets fault the zenon squad was defeated by the devil beltose the five dying busters sacrificed their life power into their five weapons saiga after giving their weapons to beet they passed away years have passed since then and the young vandel buster beet begins his adventure to carry out the zenon squads will to put an end to the dark century</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/7/21569.jpg</td>\n",
       "      <td>dark century people suffer rule devil vandel able manipulate monster vandel buster group people hunt devil know strong buster continent young boy beet dream join day result beet fault defeat beltose die buster sacrifice life power weapon saiga give weapon beet pass away year pass young vandel buster beet begin adventure carry zenon squad end dark century</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             title  score  \\\n",
       "id                                          \n",
       "1                     cowboy bebop   8.75   \n",
       "5   cowboy bebop tengoku no tobira   8.38   \n",
       "6                           trigun   8.22   \n",
       "7               witch hunter robin   7.25   \n",
       "8                   bouken ou beet   6.94   \n",
       "\n",
       "                                  genres  is_hentai  \\\n",
       "id                                                    \n",
       "1          award winning, action, sci-fi          0   \n",
       "5                         action, sci-fi          0   \n",
       "6              adventure, action, sci-fi          0   \n",
       "7   mystery, supernatural, action, drama          0   \n",
       "8       adventure, supernatural, fantasy          0   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              synopsis  \\\n",
       "id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
       "1    crime is timeless by the year 2071 humanity has expanded across the galaxy filling the surface of other planets with settlements like those on earth these new societies are plagued by murder drug use and theft and intergalactic outlaws are hunted by a growing number of tough bounty hunters spike spiegel and jet black pursue criminals throughout space to make a humble living beneath his goofy and aloof demeanor spike is haunted by the weight of his violent past meanwhile jet manages his own troubled memories while taking care of spike and the bebop their ship the duo is joined by the beautiful con artist faye valentine odd child edward wong hau pepelu tivrusky iv and ein a bioengineered welsh corgi while developing bonds and working to catch a colorful cast of criminals the bebop crews lives are disrupted by a menace from spikes past as a rivals maniacal plot continues to unravel spike must choose between life with his newfound family or revenge for his old wounds   \n",
       "5                                                                                                                                               another day another bounty—such is the life of the often unlucky crew of the bebop however this routine is interrupted when faye who is chasing a fairly worthless target on mars witnesses an oil tanker suddenly explode causing mass hysteria as casualties mount due to a strange disease spreading through the smoke from the blast a whopping three hundred million woolong price is placed on the head of the supposed perpetrator with lives at stake and a solution to their money problems in sight the bebop crew springs into action spike jet faye and edward followed closely by ein split up to pursue different leads across alba city through their individual investigations they discover a coverup scheme involving a pharmaceutical company revealing a plot that reaches much further than the ragtag team of bounty hunters could have realized   \n",
       "6   vash the stampede is the man with a 60000000000 bounty on his head the reason hes a merciless villain who lays waste to all those that oppose him and flattens entire cities for fun garnering him the title the humanoid typhoon he leaves a trail of death and destruction wherever he goes and anyone can count themselves dead if they so much as make eye contact—or so the rumors say in actuality vash is a huge softie who claims to have never taken a life and avoids violence at all costs with his crazy doughnut obsession and buffoonish attitude in tow vash traverses the wasteland of the planet gunsmoke all the while followed by two insurance agents meryl stryfe and milly thompson who attempt to minimize his impact on the public but soon their misadventures evolve into lifeordeath situations as a group of legendary assassins are summoned to bring about suffering to the trio vashs agonizing past will be unraveled and his morality and principles pushed to the breaking point   \n",
       "7                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           robin sena is a powerful craft user drafted into the stnj—a group of specialized hunters that fight deadly beings known as witches though her fire power is great shes got a lot to learn about her powers and working with her cool and aloof partner amon but the truth about the witches and herself will leave robin on an entirely new path that she never expected source funimation   \n",
       "8                                                                                                                                                                                                                                                                                           it is the dark century and the people are suffering under the rule of the devil vandel who is able to manipulate monsters the vandel busters are a group of people who hunt these devils and among them the zenon squad is known to be the strongest busters on the continent a young boy beet dreams of joining the zenon squad however one day as a result of beets fault the zenon squad was defeated by the devil beltose the five dying busters sacrificed their life power into their five weapons saiga after giving their weapons to beet they passed away years have passed since then and the young vandel buster beet begins his adventure to carry out the zenon squads will to put an end to the dark century   \n",
       "\n",
       "                                                  image_url  \\\n",
       "id                                                            \n",
       "1      https://cdn.myanimelist.net/images/anime/4/19644.jpg   \n",
       "5   https://cdn.myanimelist.net/images/anime/1439/93480.jpg   \n",
       "6      https://cdn.myanimelist.net/images/anime/7/20310.jpg   \n",
       "7     https://cdn.myanimelist.net/images/anime/10/19969.jpg   \n",
       "8      https://cdn.myanimelist.net/images/anime/7/21569.jpg   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           transformed_synopsis  \n",
       "id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
       "1                               crime timeless year 2071 humanity expand galaxy fill surface planet settlement like earth new society plague murder drug use theft intergalactic hunt grow number tough bounty hunter jet black pursue criminal space humble living beneath goofy aloof haunt weight violent past jet manage troubled memory take care bebop ship duo join beautiful con artist odd child bioengineered welsh corgi develop bond work catch colorful cast criminal bebop crew life disrupt menace spike past rival maniacal plot continue unravel choose life newfound family revenge old wound  \n",
       "5                                                               day bounty — life unlucky crew bebop routine interrupt faye chase fairly worthless target mar witness oil tanker suddenly explode cause mass hysteria casualty strange disease spread smoke blast whopping million woolong price place head suppose perpetrator life stake solution money problem sight bebop crew spring action spike jet faye edward follow closely split pursue different lead alba city individual investigation discover coverup scheme involve pharmaceutical company reveal plot reach ragtag team bounty hunter realize  \n",
       "6   vash stampede man 60000000000 bounty head reason s merciless villain lay waste oppose flatten entire city fun garner title humanoid typhoon leave trail death destruction go count dead eye contact — rumor actuality vash huge softie claim take life avoid violence cost crazy obsession buffoonish attitude tow vash traverse wasteland planet gunsmoke follow insurance agent meryl stryfe milly thompson attempt minimize impact public soon misadventure evolve lifeordeath situation group legendary assassin summon bring suffer trio agonizing past unravel morality principle push breaking point  \n",
       "7                                                                                                                                                                                                                                                                                                                                                                                powerful craft user draft stnj — group specialized hunter fight deadly being know witch fire power great s get lot learn power work cool aloof partner amon truth witch leave robin entirely new path expect source funimation  \n",
       "8                                                                                                                                                                                                                                          dark century people suffer rule devil vandel able manipulate monster vandel buster group people hunt devil know strong buster continent young boy beet dream join day result beet fault defeat beltose die buster sacrifice life power weapon saiga give weapon beet pass away year pass young vandel buster beet begin adventure carry zenon squad end dark century  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---- Removing Stop Words and Lemmatizating ----\n",
    "animes_df['transformed_synopsis'] = animes_df.synopsis.apply(lambda synopsis: transform_synopsis(synopsis))\n",
    "animes_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "027bf222",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Calculating Term Frequency - Inverse Document Frequency (TF-IDF)**\n",
    "\n",
    "`Analyzer` parameter defines the token n-gram pattern, being `unigram (word)` the chosen one.\n",
    "\n",
    "`Norm` parameter defines the values normalization, where `l2` makes the sum of the squares of vector elements be equals to 1, and `l1` makes the sum of the absolute values of vector elements be equals to 1. For the model, `l2` is the chosen normalization.\n",
    "\n",
    "Also, we are going to apply stop words remotion again in order to really assure that all stop words gotten removed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "85a6d20e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Number of Animes: 19892\n",
      "- Number of Words to Describe the Animes: 38019\n"
     ]
    }
   ],
   "source": [
    "# ---- Calculating TF-IDF ----\n",
    "tfidf_vectorizer = TfidfVectorizer(analyzer='word', norm='l2', stop_words='english')\n",
    "tfidf_synopsis = tfidf_vectorizer.fit_transform(animes_df.transformed_synopsis)\n",
    "\n",
    "print(f'- Number of Animes: {tfidf_synopsis.shape[0]}')\n",
    "print(f'- Number of Words to Describe the Animes: {tfidf_synopsis.shape[1]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e160c164",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Calculating Cosine Similarity**\n",
    "\n",
    "When `l2` is the chosen normalization for TF-IDF, the Cosine Similarity can be calculated by squaring the TF-IDF results (see [sklearn.feature_extraction.text.TfidfVectorizer - Norm Parameter](https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html). In order to do it efficiently, requiring less computational time and cost, we are going to use sklearn metrics.\n",
    "\n",
    "About the metrics, we have two options: `Cosine Similarity (sklearn.metrics.pairwise.cosine_similarity)` and `Linear Kernel (sklearn.metrics.pairwise.linear_kernel)`. Since the second one is way faster than the first, we are going on with it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c5f42662",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Calculating Cosine Similarity ----\n",
    "cosine_similarity_synopsis = linear_kernel(tfidf_synopsis, tfidf_synopsis)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f8667c5",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Dealing with Duplicated Titles**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "45b99d6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Dealing with Duplicated Titles: Getting Duplicated Titles List ----\n",
    "duplicated_title_indexes = animes_df.title.duplicated(keep=False)\n",
    "duplicated_titles_list = transform_duplicated_titles(\n",
    "    animes_df[duplicated_title_indexes].sort_values(by='title', ascending=True).title.to_list()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "83cf748b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>score</th>\n",
       "      <th>genres</th>\n",
       "      <th>is_hentai</th>\n",
       "      <th>synopsis</th>\n",
       "      <th>image_url</th>\n",
       "      <th>transformed_synopsis</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39783</th>\n",
       "      <td>5-toubun no hanayome</td>\n",
       "      <td>8.08</td>\n",
       "      <td>comedy, romance</td>\n",
       "      <td>0</td>\n",
       "      <td>through their tutor fuutarou uesugis diligent guidance the nakano quintuplets academic performance shows signs of improvement even if their path to graduation is still rocky however as they continue to cause various situations that delay any actual tutoring fuutarou becomes increasingly involved with their personal lives further complicating their relationship with each other on another note fuutarou slowly begins to realize the existence of a possible connection between him and the past he believes to have shared with one of the five girls with everyones feelings beginning to develop and overlap will they be able to keep their bond strictly to that of a teacher and his students—or will it mature into something else entirely</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1775/109514.jpg</td>\n",
       "      <td>tutor fuutarou uesugis guidance quintuplet academic performance show sign improvement path graduation rocky continue cause situation delay actual tutoring fuutarou increasingly involve personal life complicate relationship note fuutarou slowly begin realize existence possible connection past believe share girl everyone feeling begin develop overlap able bond strictly teacher student — mature entirely</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38101</th>\n",
       "      <td>5-toubun no hanayome 2</td>\n",
       "      <td>7.66</td>\n",
       "      <td>comedy, romance</td>\n",
       "      <td>0</td>\n",
       "      <td>fuutarou uesugi is an ace high school student but leads an otherwise tough life his standoffish personality and reclusive nature have left him friendless and his father is debtridden forcing his family to scrape by one day during his lunch break uesugi argues with a female transfer student who has claimed his seat leading both of them to dislike each other that same day he is presented with a golden opportunity to clear his familys debt a private tutoring gig for a wealthy familys daughter with a wage of five times the market price he accepts the proposal but is horrified to discover that the client itsuki nakano is the girl he confronted earlier after unsuccessfully trying to get back on itsukis good side uesugi finds out that his problems dont end there itsuki is actually a quintuplet so in addition to her he must also tutor her sisters—miku yotsuba nino and ichika—who despite the very real threat of flunking want nothing to do with a tutor however his familys livelihood is on the line so uesugi pushes on adamant in his resolve to rid the sisters of their detest for studying and successfully lead them to graduation</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1819/97947.jpg</td>\n",
       "      <td>ace high school student lead tough life standoffish personality reclusive nature leave friendless father force family scrape day lunch break argue female transfer student claim seat lead dislike day present golden opportunity clear family debt private tutoring gig wealthy family daughter wage time market price accept proposal horrified discover girl confront early unsuccessfully try itsukis good uesugi find problem not end itsuki actually quintuplet addition tutor sister — — despite real threat flunking want tutor familys livelihood line uesugi push adamant resolve rid sister det study successfully lead graduation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38328</th>\n",
       "      <td>azur lane</td>\n",
       "      <td>6.28</td>\n",
       "      <td>action, sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>when the sirens an alien force with an arsenal far surpassing the limits of current technology suddenly appeared a divided humanity stood in complete solidarity for the first time four countries—eagle union royal navy sakura empire and iron blood—formed azur lane paving the way for the improvement of modern warfare which led to an initial victory against the common threat however this tenuous union was threatened by opposing ideals dividing the alliance into two sakura empire and iron blood broke away and formed the red axis and humanity became fragmented once again as a seasoned and experienced fighter the grey ghost enterprise shoulders azur lanes hope for ending the war but behind her stoic persona hides a frail girl afraid of the ocean even so she continues to fight as she believes that its the only purpose for her existence meanwhile javelin laffey and unicorn—three ships from the union—stumble upon ayanami a spy from the red axis strange as it may seem they try to befriend her but as enemies their efforts are for naught still they persevere in hopes of succeeding one day amidst the neverending conflict within humankind the keys that could unite a fragmented race might exist a soldier coming to terms with her mysterious personality and camaraderie between those with different ideals</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1106/111620.jpg</td>\n",
       "      <td>siren alien force arsenal far surpass limit current technology suddenly appear divided humanity stand complete solidarity time country — eagle empire iron blood — form lane pave way improvement modern warfare lead initial victory common threat tenuous union threaten oppose ideal divide alliance sakura empire iron blood break away form red axis humanity fragment seasoned experienced fighter ghost enterprise shoulder hope end war stoic persona hide frail girl afraid ocean continue fight believe purpose existence unicorn — ship union — stumble ayanami spy red axis strange try befriend enemy effort naught persevere hope succeed day amidst neverending conflict humankind key unite fragmented race exist soldier come term mysterious personality camaraderie different ideal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55351</th>\n",
       "      <td>azur lane 2</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>slice of life, action</td>\n",
       "      <td>0</td>\n",
       "      <td>assorted commercials for the azur lane mobile game posted on the official youtube channel the animation is unique to these commercials and is not present in the game nor in the tv series</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1421/135967.jpg</td>\n",
       "      <td>assorted commercial game post official youtube channel animation unique commercial present game tv series</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48610</th>\n",
       "      <td>blue reflection ray</td>\n",
       "      <td>5.70</td>\n",
       "      <td>comedy</td>\n",
       "      <td>0</td>\n",
       "      <td>miniseries for blue reflection ray with superdeformed characters posted on the official twitter account and the dmm picture youtube channel</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1680/113838.jpg</td>\n",
       "      <td>miniserie blue reflection ray superdeforme character post official twitter account dmm youtube channel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48365</th>\n",
       "      <td>youkai watch 3</td>\n",
       "      <td>6.21</td>\n",
       "      <td>comedy, supernatural</td>\n",
       "      <td>0</td>\n",
       "      <td>the new show will feature unique and returning yokai the comedy will also center on the original series main characters fifthgrader keita nate in the english version ghost butler whisper and popular yokai like jibanyan and komasan the original cast members for these four characters are returning for this new series source ann</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1682/118273.jpg</td>\n",
       "      <td>new feature unique return yokai comedy center original series main character fifthgrader nate english version ghost butler whisper popular yokai like original cast member character return new series source ann</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12403</th>\n",
       "      <td>yuru yuri</td>\n",
       "      <td>7.82</td>\n",
       "      <td>girls love, comedy</td>\n",
       "      <td>0</td>\n",
       "      <td>the girls of the amusement club return in yuru yuri♪♪ finding new ways to make passing time even more enjoyable their members consist of the always energetic kyouko toshinou calm and sensible yui funami polite but often overlooked akari akaza and chinatsu yoshikawa who stumbled upon the others while looking for the tea ceremony club together they are the amusement club which has the deceptively simple task of keeping its members entertained along with the student council and the odd family member they strive to enjoy their youth to the fullest whether its a trip to a hot spring or finishing overdue homework their lives are never dull and they will always find an excuse to spend time together</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/8/75174.jpg</td>\n",
       "      <td>girl amusement club return ♪ find new way pass time enjoyable member consist energetic calm sensible funami polite overlook akaza chinatsu yoshikawa stumble look tea ceremony club amusement club deceptively simple task keep member entertain student council odd family member strive enjoy youth full trip hot spring finish overdue homework life dull find excuse spend time</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10495</th>\n",
       "      <td>yuru yuri 2</td>\n",
       "      <td>7.57</td>\n",
       "      <td>girls love, comedy, award winning</td>\n",
       "      <td>0</td>\n",
       "      <td>after a year in grade school without her childhood friends first year student akari akaza is finally reunited with second years yui funami and kyouko toshinou at their allgirls middle school during the duos first year yui and kyouko formed the amusement club which occupies the now nonexistent tea clubs room shortly after akari joins one of her fellow classmates chinatsu yoshikawa pays the trio a visit under the impression that they are the tea club it is only once the three girls explain that the tea club has been disbanded that they can convince chinatsu to join the amusement club—a group with no purpose other than to provide entertainment for its members based on the sliceoflife manga by namori yuru yuri is an eccentric comedy about a group of girls who spend their spare time drinking tea and fawning over each other all while completely failing to even notice the supposed main character akari amongst them</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/12/75173.jpg</td>\n",
       "      <td>year grade school childhood friend year student akaza finally reunite second year funami allgirl middle school duos year form amusement club occupy nonexistent tea club room shortly join fellow classmate chinatsu pay trio visit impression tea club girl explain tea club disband convince chinatsu join amusement club — group purpose provide entertainment member base sliceoflife manga eccentric comedy group girl spend spare time drink tea fawn completely fail notice suppose main character akari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23225</th>\n",
       "      <td>yuru yuri nachuyachumi</td>\n",
       "      <td>7.85</td>\n",
       "      <td>girls love, comedy</td>\n",
       "      <td>0</td>\n",
       "      <td>even during summer break the amusement club lives up to its name when akari akaza kyouko toshinou chinatsu yoshikawa and yui funami find a camping tent they decide to put it to good use by spending the weekend outside in the mountains when some student council members catch wind of this they are invited to come along as well after a very long journey the group arrives at their destination and is ready to make the most of their trip they engage in classic camping activities such as outdoor cooking and tests of courage and finish it all off with a visit to the hot springs an extravagant trip like this doesnt happen every day but the amusement club is sure to savor each moment</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/2/73281.jpg</td>\n",
       "      <td>summer break amusement club live funami find camping tent decide good use spend weekend outside mountain student council member catch wind invite come long journey group arrive destination ready trip engage classic camping activity outdoor cooking test courage finish visit hot spring extravagant trip like not happen day amusement club sure savor moment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30902</th>\n",
       "      <td>yuru yuri nachuyachumi 2</td>\n",
       "      <td>7.77</td>\n",
       "      <td>girls love, comedy</td>\n",
       "      <td>0</td>\n",
       "      <td>extra episodes of yuru yuri nachuyachumi summer vacation is drawing to a close but the amusement club members make the most of the last days between outdoor activities in the sun reminiscing on their recent camping trip and a sleepover the members of the amusement club and their classmates in the student council continue to make summer memories</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/2/75992.jpg</td>\n",
       "      <td>extra episode summer vacation draw close amusement club member day outdoor activity sun reminisce recent camping trip sleepover member amusement club classmate student council continue summer memory</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>111 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  score                             genres  \\\n",
       "id                                                                          \n",
       "39783      5-toubun no hanayome   8.08                    comedy, romance   \n",
       "38101    5-toubun no hanayome 2   7.66                    comedy, romance   \n",
       "38328                 azur lane   6.28                     action, sci-fi   \n",
       "55351               azur lane 2  -1.00              slice of life, action   \n",
       "48610       blue reflection ray   5.70                             comedy   \n",
       "...                         ...    ...                                ...   \n",
       "48365            youkai watch 3   6.21               comedy, supernatural   \n",
       "12403                 yuru yuri   7.82                 girls love, comedy   \n",
       "10495               yuru yuri 2   7.57  girls love, comedy, award winning   \n",
       "23225    yuru yuri nachuyachumi   7.85                 girls love, comedy   \n",
       "30902  yuru yuri nachuyachumi 2   7.77                 girls love, comedy   \n",
       "\n",
       "       is_hentai  \\\n",
       "id                 \n",
       "39783          0   \n",
       "38101          0   \n",
       "38328          0   \n",
       "55351          0   \n",
       "48610          0   \n",
       "...          ...   \n",
       "48365          0   \n",
       "12403          0   \n",
       "10495          0   \n",
       "23225          0   \n",
       "30902          0   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           synopsis  \\\n",
       "id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
       "39783                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                through their tutor fuutarou uesugis diligent guidance the nakano quintuplets academic performance shows signs of improvement even if their path to graduation is still rocky however as they continue to cause various situations that delay any actual tutoring fuutarou becomes increasingly involved with their personal lives further complicating their relationship with each other on another note fuutarou slowly begins to realize the existence of a possible connection between him and the past he believes to have shared with one of the five girls with everyones feelings beginning to develop and overlap will they be able to keep their bond strictly to that of a teacher and his students—or will it mature into something else entirely   \n",
       "38101                                                                                                                                                                                fuutarou uesugi is an ace high school student but leads an otherwise tough life his standoffish personality and reclusive nature have left him friendless and his father is debtridden forcing his family to scrape by one day during his lunch break uesugi argues with a female transfer student who has claimed his seat leading both of them to dislike each other that same day he is presented with a golden opportunity to clear his familys debt a private tutoring gig for a wealthy familys daughter with a wage of five times the market price he accepts the proposal but is horrified to discover that the client itsuki nakano is the girl he confronted earlier after unsuccessfully trying to get back on itsukis good side uesugi finds out that his problems dont end there itsuki is actually a quintuplet so in addition to her he must also tutor her sisters—miku yotsuba nino and ichika—who despite the very real threat of flunking want nothing to do with a tutor however his familys livelihood is on the line so uesugi pushes on adamant in his resolve to rid the sisters of their detest for studying and successfully lead them to graduation   \n",
       "38328  when the sirens an alien force with an arsenal far surpassing the limits of current technology suddenly appeared a divided humanity stood in complete solidarity for the first time four countries—eagle union royal navy sakura empire and iron blood—formed azur lane paving the way for the improvement of modern warfare which led to an initial victory against the common threat however this tenuous union was threatened by opposing ideals dividing the alliance into two sakura empire and iron blood broke away and formed the red axis and humanity became fragmented once again as a seasoned and experienced fighter the grey ghost enterprise shoulders azur lanes hope for ending the war but behind her stoic persona hides a frail girl afraid of the ocean even so she continues to fight as she believes that its the only purpose for her existence meanwhile javelin laffey and unicorn—three ships from the union—stumble upon ayanami a spy from the red axis strange as it may seem they try to befriend her but as enemies their efforts are for naught still they persevere in hopes of succeeding one day amidst the neverending conflict within humankind the keys that could unite a fragmented race might exist a soldier coming to terms with her mysterious personality and camaraderie between those with different ideals   \n",
       "55351                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    assorted commercials for the azur lane mobile game posted on the official youtube channel the animation is unique to these commercials and is not present in the game nor in the tv series   \n",
       "48610                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   miniseries for blue reflection ray with superdeformed characters posted on the official twitter account and the dmm picture youtube channel   \n",
       "...                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             ...   \n",
       "48365                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       the new show will feature unique and returning yokai the comedy will also center on the original series main characters fifthgrader keita nate in the english version ghost butler whisper and popular yokai like jibanyan and komasan the original cast members for these four characters are returning for this new series source ann   \n",
       "12403                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  the girls of the amusement club return in yuru yuri♪♪ finding new ways to make passing time even more enjoyable their members consist of the always energetic kyouko toshinou calm and sensible yui funami polite but often overlooked akari akaza and chinatsu yoshikawa who stumbled upon the others while looking for the tea ceremony club together they are the amusement club which has the deceptively simple task of keeping its members entertained along with the student council and the odd family member they strive to enjoy their youth to the fullest whether its a trip to a hot spring or finishing overdue homework their lives are never dull and they will always find an excuse to spend time together   \n",
       "10495                                                                                                                                                                                                                                                                                                                                                                                                      after a year in grade school without her childhood friends first year student akari akaza is finally reunited with second years yui funami and kyouko toshinou at their allgirls middle school during the duos first year yui and kyouko formed the amusement club which occupies the now nonexistent tea clubs room shortly after akari joins one of her fellow classmates chinatsu yoshikawa pays the trio a visit under the impression that they are the tea club it is only once the three girls explain that the tea club has been disbanded that they can convince chinatsu to join the amusement club—a group with no purpose other than to provide entertainment for its members based on the sliceoflife manga by namori yuru yuri is an eccentric comedy about a group of girls who spend their spare time drinking tea and fawning over each other all while completely failing to even notice the supposed main character akari amongst them   \n",
       "23225                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    even during summer break the amusement club lives up to its name when akari akaza kyouko toshinou chinatsu yoshikawa and yui funami find a camping tent they decide to put it to good use by spending the weekend outside in the mountains when some student council members catch wind of this they are invited to come along as well after a very long journey the group arrives at their destination and is ready to make the most of their trip they engage in classic camping activities such as outdoor cooking and tests of courage and finish it all off with a visit to the hot springs an extravagant trip like this doesnt happen every day but the amusement club is sure to savor each moment   \n",
       "30902                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    extra episodes of yuru yuri nachuyachumi summer vacation is drawing to a close but the amusement club members make the most of the last days between outdoor activities in the sun reminiscing on their recent camping trip and a sleepover the members of the amusement club and their classmates in the student council continue to make summer memories   \n",
       "\n",
       "                                                      image_url  \\\n",
       "id                                                                \n",
       "39783  https://cdn.myanimelist.net/images/anime/1775/109514.jpg   \n",
       "38101   https://cdn.myanimelist.net/images/anime/1819/97947.jpg   \n",
       "38328  https://cdn.myanimelist.net/images/anime/1106/111620.jpg   \n",
       "55351  https://cdn.myanimelist.net/images/anime/1421/135967.jpg   \n",
       "48610  https://cdn.myanimelist.net/images/anime/1680/113838.jpg   \n",
       "...                                                         ...   \n",
       "48365  https://cdn.myanimelist.net/images/anime/1682/118273.jpg   \n",
       "12403      https://cdn.myanimelist.net/images/anime/8/75174.jpg   \n",
       "10495     https://cdn.myanimelist.net/images/anime/12/75173.jpg   \n",
       "23225      https://cdn.myanimelist.net/images/anime/2/73281.jpg   \n",
       "30902      https://cdn.myanimelist.net/images/anime/2/75992.jpg   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         transformed_synopsis  \n",
       "id                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             \n",
       "39783                                                                                                                                                                                                                                                                                                                                                                                     tutor fuutarou uesugis guidance quintuplet academic performance show sign improvement path graduation rocky continue cause situation delay actual tutoring fuutarou increasingly involve personal life complicate relationship note fuutarou slowly begin realize existence possible connection past believe share girl everyone feeling begin develop overlap able bond strictly teacher student — mature entirely  \n",
       "38101                                                                                                                                                           ace high school student lead tough life standoffish personality reclusive nature leave friendless father force family scrape day lunch break argue female transfer student claim seat lead dislike day present golden opportunity clear family debt private tutoring gig wealthy family daughter wage time market price accept proposal horrified discover girl confront early unsuccessfully try itsukis good uesugi find problem not end itsuki actually quintuplet addition tutor sister — — despite real threat flunking want tutor familys livelihood line uesugi push adamant resolve rid sister det study successfully lead graduation  \n",
       "38328  siren alien force arsenal far surpass limit current technology suddenly appear divided humanity stand complete solidarity time country — eagle empire iron blood — form lane pave way improvement modern warfare lead initial victory common threat tenuous union threaten oppose ideal divide alliance sakura empire iron blood break away form red axis humanity fragment seasoned experienced fighter ghost enterprise shoulder hope end war stoic persona hide frail girl afraid ocean continue fight believe purpose existence unicorn — ship union — stumble ayanami spy red axis strange try befriend enemy effort naught persevere hope succeed day amidst neverending conflict humankind key unite fragmented race exist soldier come term mysterious personality camaraderie different ideal  \n",
       "55351                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               assorted commercial game post official youtube channel animation unique commercial present game tv series  \n",
       "48610                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  miniserie blue reflection ray superdeforme character post official twitter account dmm youtube channel  \n",
       "...                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       ...  \n",
       "48365                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       new feature unique return yokai comedy center original series main character fifthgrader nate english version ghost butler whisper popular yokai like original cast member character return new series source ann  \n",
       "12403                                                                                                                                                                                                                                                                                                                                                                                                                     girl amusement club return ♪ find new way pass time enjoyable member consist energetic calm sensible funami polite overlook akaza chinatsu yoshikawa stumble look tea ceremony club amusement club deceptively simple task keep member entertain student council odd family member strive enjoy youth full trip hot spring finish overdue homework life dull find excuse spend time  \n",
       "10495                                                                                                                                                                                                                                                                                         year grade school childhood friend year student akaza finally reunite second year funami allgirl middle school duos year form amusement club occupy nonexistent tea club room shortly join fellow classmate chinatsu pay trio visit impression tea club girl explain tea club disband convince chinatsu join amusement club — group purpose provide entertainment member base sliceoflife manga eccentric comedy group girl spend spare time drink tea fawn completely fail notice suppose main character akari  \n",
       "23225                                                                                                                                                                                                                                                                                                                                                                                                                                      summer break amusement club live funami find camping tent decide good use spend weekend outside mountain student council member catch wind invite come long journey group arrive destination ready trip engage classic camping activity outdoor cooking test courage finish visit hot spring extravagant trip like not happen day amusement club sure savor moment  \n",
       "30902                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  extra episode summer vacation draw close amusement club member day outdoor activity sun reminisce recent camping trip sleepover member amusement club classmate student council continue summer memory  \n",
       "\n",
       "[111 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---- Dealing with Duplicated Titles: Transforming the Titles ----\n",
    "duplicated_animes_df = animes_df[duplicated_title_indexes].sort_values(by='title', ascending=True)\n",
    "duplicated_animes_df['title'] = duplicated_titles_list\n",
    "animes_df.loc[duplicated_title_indexes] = duplicated_animes_df\n",
    "animes_df.loc[duplicated_title_indexes].sort_values(by='title', ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23b7a61a",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Creating Search Function**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "082bce41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ---- Recommending Animes: Reseting Animes Dataframe Index ----\n",
    "#\n",
    "# - in order to the index follow a sequence from 0 to 'n', being 'n'\n",
    "# the total number of animes.\n",
    "#\n",
    "animes_df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b6ccec5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5604                                                           steins gate\n",
       "6303                                  steins gate oukoubakko no poriomania\n",
       "6450                              steins gate movie fuka ryouiki no d j vu\n",
       "9398                       steins gate soumei eichi no cognitive computing\n",
       "10232                                                        steins gate 0\n",
       "10890           steins gate kyoukaimenjou no missing link - divide by zero\n",
       "13693    steins gate 0 kesshou takei no valentine - bittersweet intermedio\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---- Recommending Animes ----\n",
    "#\n",
    "# - search animes titles that contains a given string in order to use it\n",
    "# in the next cell to get recommendations.\n",
    "#\n",
    "animes_df.title.loc[animes_df.title.str.contains('steins')]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3abe055e-e347-4394-9faf-f94bf520d3c8",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**- Recommendations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b86cf602",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>score</th>\n",
       "      <th>genres</th>\n",
       "      <th>is_hentai</th>\n",
       "      <th>image_url</th>\n",
       "      <th>cosine_similarity</th>\n",
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       "      <th>id</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10863</th>\n",
       "      <td>steins gate oukoubakko no poriomania</td>\n",
       "      <td>8.29</td>\n",
       "      <td>comedy, sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1805/123188.jpg</td>\n",
       "      <td>0.185586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32188</th>\n",
       "      <td>steins gate kyoukaimenjou no missing link - divide by zero</td>\n",
       "      <td>8.25</td>\n",
       "      <td>suspense, sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/7/77324.jpg</td>\n",
       "      <td>0.171298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11577</th>\n",
       "      <td>steins gate movie fuka ryouiki no d j vu</td>\n",
       "      <td>8.45</td>\n",
       "      <td>sci-fi, drama</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1611/112806.jpg</td>\n",
       "      <td>0.168413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30484</th>\n",
       "      <td>steins gate 0</td>\n",
       "      <td>8.53</td>\n",
       "      <td>suspense, sci-fi, drama</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1375/93521.jpg</td>\n",
       "      <td>0.154389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40139</th>\n",
       "      <td>konohakaseki no natsu</td>\n",
       "      <td>6.14</td>\n",
       "      <td>slice of life, drama</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1963/102128.jpg</td>\n",
       "      <td>0.153178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37246</th>\n",
       "      <td>moshimoshi, terumi desu</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>slice of life</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1812/108112.jpg</td>\n",
       "      <td>0.134788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52624</th>\n",
       "      <td>duoyun shi qing</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>drama</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/1861/126609.jpg</td>\n",
       "      <td>0.123118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27957</th>\n",
       "      <td>steins gate soumei eichi no cognitive computing</td>\n",
       "      <td>7.42</td>\n",
       "      <td>comedy, sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/10/71319.jpg</td>\n",
       "      <td>0.106900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21587</th>\n",
       "      <td>mou hitotsu no mirai wo</td>\n",
       "      <td>6.02</td>\n",
       "      <td>sci-fi</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/10/56893.jpg</td>\n",
       "      <td>0.103686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9491</th>\n",
       "      <td>katsugeki shoujo tanteidan</td>\n",
       "      <td>4.48</td>\n",
       "      <td>comedy, action</td>\n",
       "      <td>0</td>\n",
       "      <td>https://cdn.myanimelist.net/images/anime/10/41457.jpg</td>\n",
       "      <td>0.103333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                            title  score  \\\n",
       "id                                                                         \n",
       "10863                        steins gate oukoubakko no poriomania   8.29   \n",
       "32188  steins gate kyoukaimenjou no missing link - divide by zero   8.25   \n",
       "11577                    steins gate movie fuka ryouiki no d j vu   8.45   \n",
       "30484                                               steins gate 0   8.53   \n",
       "40139                                       konohakaseki no natsu   6.14   \n",
       "37246                                     moshimoshi, terumi desu  -1.00   \n",
       "52624                                             duoyun shi qing  -1.00   \n",
       "27957             steins gate soumei eichi no cognitive computing   7.42   \n",
       "21587                                     mou hitotsu no mirai wo   6.02   \n",
       "9491                                   katsugeki shoujo tanteidan   4.48   \n",
       "\n",
       "                        genres  is_hentai  \\\n",
       "id                                          \n",
       "10863           comedy, sci-fi          0   \n",
       "32188         suspense, sci-fi          0   \n",
       "11577            sci-fi, drama          0   \n",
       "30484  suspense, sci-fi, drama          0   \n",
       "40139     slice of life, drama          0   \n",
       "37246            slice of life          0   \n",
       "52624                    drama          0   \n",
       "27957           comedy, sci-fi          0   \n",
       "21587                   sci-fi          0   \n",
       "9491            comedy, action          0   \n",
       "\n",
       "                                                      image_url  \\\n",
       "id                                                                \n",
       "10863  https://cdn.myanimelist.net/images/anime/1805/123188.jpg   \n",
       "32188      https://cdn.myanimelist.net/images/anime/7/77324.jpg   \n",
       "11577  https://cdn.myanimelist.net/images/anime/1611/112806.jpg   \n",
       "30484   https://cdn.myanimelist.net/images/anime/1375/93521.jpg   \n",
       "40139  https://cdn.myanimelist.net/images/anime/1963/102128.jpg   \n",
       "37246  https://cdn.myanimelist.net/images/anime/1812/108112.jpg   \n",
       "52624  https://cdn.myanimelist.net/images/anime/1861/126609.jpg   \n",
       "27957     https://cdn.myanimelist.net/images/anime/10/71319.jpg   \n",
       "21587     https://cdn.myanimelist.net/images/anime/10/56893.jpg   \n",
       "9491      https://cdn.myanimelist.net/images/anime/10/41457.jpg   \n",
       "\n",
       "       cosine_similarity  \n",
       "id                        \n",
       "10863           0.185586  \n",
       "32188           0.171298  \n",
       "11577           0.168413  \n",
       "30484           0.154389  \n",
       "40139           0.153178  \n",
       "37246           0.134788  \n",
       "52624           0.123118  \n",
       "27957           0.106900  \n",
       "21587           0.103686  \n",
       "9491            0.103333  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---- Recommending Animes ----\n",
    "animes_indices = pd.Series(animes_df.index, index=animes_df.title)\n",
    "\n",
    "get_recommendations(\n",
    "    dataset=animes_df\n",
    "    , title='steins gate'\n",
    "    , animes_indices=animes_indices\n",
    "    , cosine_similarity=cosine_similarity_synopsis\n",
    "    , number_recommendations=10\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "556708ca",
   "metadata": {},
   "source": [
    "Realize that Content-Based Filtering by Plot Descriptions usually recommends sequels and prequels of the same anime first. Even though it is good for those who watched and liked the show, it can bore the users since there is a chance to they only receive recommendations about the same anime universe. For instance, try replacing 'steins gate' by 'dragon ball z' or 'naruto', almost all recommendations will be sequels and prequels of the same anime."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25cac339",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "<h1 id='reach-me' style='color:#7159c1; border-bottom:3px solid #7159c1; letter-spacing:2px; font-family:JetBrains Mono; font-weight: bold; text-align:left; font-size:240%;padding:0'>📫 | Reach Me</h1>\n",
    "\n",
    "> **Email** - [csfelix08@gmail.com](mailto:csfelix08@gmail.com?)\n",
    "\n",
    "> **Linkedin** - [linkedin.com/in/csfelix/](https://www.linkedin.com/in/csfelix/)\n",
    "\n",
    "> **GitHub:** - [CSFelix](https://github.com/CSFelix)\n",
    "\n",
    "> **Kaggle** - [DSFelix](https://www.kaggle.com/dsfelix)\n",
    "\n",
    "> **Portfolio** - [CSFelix.io](https://csfelix.github.io/)."
   ]
  }
 ],
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