{
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   "metadata": {},
   "source": [
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)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe80b124b7d573c4",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "# US baby names dataset\n",
    "\n",
    "This notebook gives an example of Active Anomaly Detection with `coniferest` and [US baby names](https://www.ssa.gov/OACT/babynames/) dataset.\n",
    "\n",
    "Developers of `conferest`:\n",
    "- [Matwey Kornilov (MSU)](https://matwey.name)\n",
    "- [Vladimir Korolev](https://www.linkedin.com/in/vladimir-korolev-a4195b86/)\n",
    "- [Konstantin Malanchev (LINCC Frameworks / CMU)](https://homb.it), notebook author\n",
    "\n",
    "The tutorial is co-authored by [Etienne Russeil (LPC)](https://github.com/erusseil)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9540d709-09ca-41ed-bceb-92370a82bd37",
   "metadata": {},
   "source": [
    "**[Run this NB in Google Colab](https://colab.research.google.com/github/snad-space/coniferest/blob/master/docs/notebooks/us-names.ipynb)**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3cef2a4-3270-4f94-b37c-bd8ada31a53c",
   "metadata": {},
   "source": [
    "## Install and import modules"
   ]
  },
  {
   "cell_type": "code",
   "id": "826cf8dd-003a-42e3-83df-c19ded1d2b83",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:49:41.831606Z",
     "start_time": "2025-10-17T17:49:41.068336Z"
    }
   },
   "source": "%pip install 'coniferest[datasets]' pandas",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (2.3.0)\r\n",
      "Requirement already satisfied: coniferest[datasets] in /Users/hombit/projects/supernovaAD/coniferest (0.0.11)\r\n",
      "\u001B[33mWARNING: coniferest 0.0.11 does not provide the extra 'datasets'\u001B[0m\u001B[33m\r\n",
      "\u001B[0mRequirement already satisfied: click in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (8.2.1)\r\n",
      "Requirement already satisfied: joblib in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (1.5.1)\r\n",
      "Requirement already satisfied: numpy in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (2.3.1)\r\n",
      "Requirement already satisfied: scikit-learn<2,>=1 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (1.7.0)\r\n",
      "Requirement already satisfied: matplotlib in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (3.10.3)\r\n",
      "Requirement already satisfied: onnxconverter-common in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from coniferest[datasets]) (1.14.0)\r\n",
      "Requirement already satisfied: scipy>=1.8.0 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from scikit-learn<2,>=1->coniferest[datasets]) (1.16.0)\r\n",
      "Requirement already satisfied: threadpoolctl>=3.1.0 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from scikit-learn<2,>=1->coniferest[datasets]) (3.6.0)\r\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from pandas) (2.9.0.post0)\r\n",
      "Requirement already satisfied: pytz>=2020.1 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from pandas) (2025.2)\r\n",
      "Requirement already satisfied: tzdata>=2022.7 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from pandas) (2025.2)\r\n",
      "Requirement already satisfied: six>=1.5 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\r\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (1.3.2)\r\n",
      "Requirement already satisfied: cycler>=0.10 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (0.12.1)\r\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (4.58.4)\r\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (1.4.8)\r\n",
      "Requirement already satisfied: packaging>=20.0 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (25.0)\r\n",
      "Requirement already satisfied: pillow>=8 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (11.2.1)\r\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from matplotlib->coniferest[datasets]) (3.2.3)\r\n",
      "Requirement already satisfied: onnx in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from onnxconverter-common->coniferest[datasets]) (1.17.0)\r\n",
      "Requirement already satisfied: protobuf==3.20.2 in /Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages (from onnxconverter-common->coniferest[datasets]) (3.20.2)\r\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "id": "1bbe8848",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:49:43.475648Z",
     "start_time": "2025-10-17T17:49:41.842695Z"
    }
   },
   "source": [
    "import datasets\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "from coniferest.pineforest import PineForest\n",
    "from coniferest.isoforest import IsolationForest\n",
    "from coniferest.pineforest import PineForest\n",
    "from coniferest.session import Session\n",
    "from coniferest.session.callback import TerminateAfter, prompt_decision_callback, Label"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/hombit/.virtualenvs/coniferest/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "id": "f85849cf-ae6b-4422-a7b6-39defe4400b6",
   "metadata": {},
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3010d52e-2e26-494a-90e2-d8c552f39dd9",
   "metadata": {},
   "source": [
    "Download data and put into a single data frame"
   ]
  },
  {
   "cell_type": "code",
   "id": "ce14ad6e-838b-4ea7-a97b-b90c2478b228",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:49:49.172101Z",
     "start_time": "2025-10-17T17:49:43.522024Z"
    }
   },
   "source": [
    "%%time\n",
    "\n",
    "# Hugging Face dataset constructed from\n",
    "# https://www.ssa.gov/OACT/babynames/state/namesbystate.zip\n",
    "dataset = datasets.load_dataset(\"snad-space/us-names-by-state\")\n",
    "raw = dataset['train'].to_pandas()\n",
    "\n",
    "raw"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data: 100%|██████████| 51/51 [00:01<00:00, 41.41files/s]\n",
      "Generating train split: 100%|██████████| 6600640/6600640 [00:02<00:00, 2268886.44 examples/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.14 s, sys: 970 ms, total: 4.1 s\n",
      "Wall time: 5.64 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "        State Gender  Year      Name  Count\n",
       "0          AK      F  1910      Mary     14\n",
       "1          AK      F  1910     Annie     12\n",
       "2          AK      F  1910      Anna     10\n",
       "3          AK      F  1910  Margaret      8\n",
       "4          AK      F  1910     Helen      7\n",
       "...       ...    ...   ...       ...    ...\n",
       "6600635    WY      M  2024     Royce      5\n",
       "6600636    WY      M  2024   Spencer      5\n",
       "6600637    WY      M  2024    Truett      5\n",
       "6600638    WY      M  2024    Wylder      5\n",
       "6600639    WY      M  2024    Xander      5\n",
       "\n",
       "[6600640 rows x 5 columns]"
      ],
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Year</th>\n",
       "      <th>Name</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>F</td>\n",
       "      <td>1910</td>\n",
       "      <td>Mary</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>F</td>\n",
       "      <td>1910</td>\n",
       "      <td>Annie</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>F</td>\n",
       "      <td>1910</td>\n",
       "      <td>Anna</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AK</td>\n",
       "      <td>F</td>\n",
       "      <td>1910</td>\n",
       "      <td>Margaret</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AK</td>\n",
       "      <td>F</td>\n",
       "      <td>1910</td>\n",
       "      <td>Helen</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6600635</th>\n",
       "      <td>WY</td>\n",
       "      <td>M</td>\n",
       "      <td>2024</td>\n",
       "      <td>Royce</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6600636</th>\n",
       "      <td>WY</td>\n",
       "      <td>M</td>\n",
       "      <td>2024</td>\n",
       "      <td>Spencer</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6600637</th>\n",
       "      <td>WY</td>\n",
       "      <td>M</td>\n",
       "      <td>2024</td>\n",
       "      <td>Truett</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6600638</th>\n",
       "      <td>WY</td>\n",
       "      <td>M</td>\n",
       "      <td>2024</td>\n",
       "      <td>Wylder</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>6600639</th>\n",
       "      <td>WY</td>\n",
       "      <td>M</td>\n",
       "      <td>2024</td>\n",
       "      <td>Xander</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6600640 rows × 5 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "id": "2acb0285-36bc-4b12-be08-37e456f147a6",
   "metadata": {},
   "source": [
    "Let's load the data and transform it into a feature matrix where each column is the number (normalized by peak value) of US citizens that got this name in a given year. We apply few quality filter. We require the name to appear at least 10000 times over the full time range, this will prevent noisy data from names that are barely used. \n",
    "\n",
    "Optionally, we use first few Fourier terms to better detect \"bumps\" and \"waves\" in the time-series."
   ]
  },
  {
   "cell_type": "code",
   "id": "956e9a5c-fa19-4802-b83b-a9cca5b481ee",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:22.110276Z",
     "start_time": "2025-10-17T17:49:49.212796Z"
    }
   },
   "source": [
    "%%time\n",
    "\n",
    "WITH_FFT = True\n",
    "\n",
    "all_years = np.unique(raw['Year'])\n",
    "all_names = np.unique(raw['Name'])\n",
    "\n",
    "# Accumulate names over states and genders\n",
    "counts = raw.groupby(\n",
    "    ['Name', 'Year'],\n",
    ").apply(\n",
    "    lambda df: df['Count'].sum(),\n",
    "    include_groups=False,\n",
    ")\n",
    "\n",
    "# Transform to a data frame where names are labels, years are columns and counts are values (features)\n",
    "years = [f'year_{i}' for i in all_years]\n",
    "year_columns = pd.DataFrame(data=0.0, index=all_names, columns=years)\n",
    "for name, year in counts.index:\n",
    "    year_columns.loc[name, f'year_{year}'] = counts.loc[name, year]\n",
    "\n",
    "# Account for total population changes\n",
    "trend = year_columns.sum(axis=0)\n",
    "detrended = year_columns / trend\n",
    "\n",
    "# Normalise and filter\n",
    "norm = detrended.apply(lambda column: column / detrended.max(axis=1))\n",
    "filtered = norm[year_columns.sum(axis=1) >= 10_000]\n",
    "\n",
    "if WITH_FFT:\n",
    "    # Fourier-transform, normalize by zero frequency and get power-spectrum for few lowest frequencies\n",
    "    power_spectrum = np.square(np.abs(np.fft.fft(filtered)))\n",
    "    power_spectrum_norm = power_spectrum / power_spectrum[:, 0, None]\n",
    "    power_spectrum_low_freq = power_spectrum_norm[:, 1:21]\n",
    "    frequencies = [f'freq_{i}' for i in range(power_spectrum_low_freq.shape[1])]\n",
    "    power = pd.DataFrame(data=power_spectrum_low_freq, index=filtered.index, columns=frequencies)\n",
    "\n",
    "    # Concatenate time-series data and power spectrum\n",
    "    final = pd.merge(filtered, power, left_index=True, right_index=True)\n",
    "else:\n",
    "    # Use time-series data\n",
    "    final = filtered\n",
    "\n",
    "final"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 32 s, sys: 492 ms, total: 32.5 s\n",
      "Wall time: 32.9 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "          year_1910  year_1911  year_1912  year_1913  year_1914  year_1915  \\\n",
       "Aaliyah    0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "Aaron      0.045721   0.053748   0.062029   0.077329   0.074982   0.065564   \n",
       "Abbey      0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "Abbie      0.359963   0.269810   0.306465   0.464630   0.215549   0.302426   \n",
       "Abbigail   0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "Zelma      0.932474   1.000000   0.729411   0.723821   0.652394   0.669621   \n",
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       "\n",
       "          year_1916  year_1917  year_1918  year_1919  ...   freq_10   freq_11  \\\n",
       "Aaliyah    0.000000   0.000000   0.000000   0.000000  ...  0.007815  0.011471   \n",
       "Aaron      0.066903   0.066013   0.065492   0.066256  ...  0.000203  0.000332   \n",
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       "Abbigail   0.000000   0.000000   0.000000   0.000000  ...  0.002717  0.001827   \n",
       "...             ...        ...        ...        ...  ...       ...       ...   \n",
       "Zelma      0.600106   0.576397   0.536196   0.576366  ...  0.012596  0.010955   \n",
       "Zion       0.000000   0.000000   0.000000   0.000000  ...  0.022560  0.009141   \n",
       "Zoe        0.004275   0.004373   0.002134   0.001221  ...  0.010147  0.009064   \n",
       "Zoey       0.000000   0.000000   0.000000   0.000000  ...  0.010202  0.010542   \n",
       "Zuri       0.000000   0.000000   0.000000   0.000000  ...  0.041216  0.032491   \n",
       "\n",
       "           freq_12   freq_13   freq_14   freq_15   freq_16   freq_17  \\\n",
       "Aaliyah   0.009205  0.002661  0.000384  0.003367  0.004686  0.002152   \n",
       "Aaron     0.000003  0.000209  0.000003  0.000213  0.000325  0.000083   \n",
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       "Abbie     0.000180  0.000260  0.001956  0.000199  0.000055  0.000111   \n",
       "Abbigail  0.001172  0.001199  0.001423  0.001123  0.000468  0.000081   \n",
       "...            ...       ...       ...       ...       ...       ...   \n",
       "Zelma     0.009435  0.007556  0.005983  0.005520  0.005827  0.005979   \n",
       "Zion      0.002182  0.006346  0.010988  0.008036  0.002212  0.001621   \n",
       "Zoe       0.004659  0.001311  0.001038  0.002035  0.002939  0.003169   \n",
       "Zoey      0.008716  0.005578  0.002431  0.000437  0.000107  0.000786   \n",
       "Zuri      0.029391  0.026944  0.022914  0.018828  0.013810  0.008968   \n",
       "\n",
       "           freq_18   freq_19  \n",
       "Aaliyah   0.000062  0.000980  \n",
       "Aaron     0.000084  0.000259  \n",
       "Abbey     0.000016  0.000096  \n",
       "Abbie     0.000089  0.000495  \n",
       "Abbigail  0.000061  0.000128  \n",
       "...            ...       ...  \n",
       "Zelma     0.005959  0.006366  \n",
       "Zion      0.005530  0.006818  \n",
       "Zoe       0.002656  0.002130  \n",
       "Zoey      0.001459  0.001728  \n",
       "Zuri      0.007011  0.007291  \n",
       "\n",
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       "      <td>0.053748</td>\n",
       "      <td>0.062029</td>\n",
       "      <td>0.077329</td>\n",
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       "      <td>0.066013</td>\n",
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       "      <td>0.066256</td>\n",
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       "      <td>0.002742</td>\n",
       "      <td>0.000650</td>\n",
       "      <td>0.000279</td>\n",
       "      <td>0.000762</td>\n",
       "      <td>0.000680</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.000096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abbie</th>\n",
       "      <td>0.359963</td>\n",
       "      <td>0.269810</td>\n",
       "      <td>0.306465</td>\n",
       "      <td>0.464630</td>\n",
       "      <td>0.215549</td>\n",
       "      <td>0.302426</td>\n",
       "      <td>0.349251</td>\n",
       "      <td>0.307615</td>\n",
       "      <td>0.197811</td>\n",
       "      <td>0.346344</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000792</td>\n",
       "      <td>0.000478</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>0.001956</td>\n",
       "      <td>0.000199</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.000495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abbigail</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002717</td>\n",
       "      <td>0.001827</td>\n",
       "      <td>0.001172</td>\n",
       "      <td>0.001199</td>\n",
       "      <td>0.001423</td>\n",
       "      <td>0.001123</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>0.000128</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>Zelma</th>\n",
       "      <td>0.932474</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.729411</td>\n",
       "      <td>0.723821</td>\n",
       "      <td>0.652394</td>\n",
       "      <td>0.669621</td>\n",
       "      <td>0.600106</td>\n",
       "      <td>0.576397</td>\n",
       "      <td>0.536196</td>\n",
       "      <td>0.576366</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012596</td>\n",
       "      <td>0.010955</td>\n",
       "      <td>0.009435</td>\n",
       "      <td>0.007556</td>\n",
       "      <td>0.005983</td>\n",
       "      <td>0.005520</td>\n",
       "      <td>0.005827</td>\n",
       "      <td>0.005979</td>\n",
       "      <td>0.005959</td>\n",
       "      <td>0.006366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zion</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022560</td>\n",
       "      <td>0.009141</td>\n",
       "      <td>0.002182</td>\n",
       "      <td>0.006346</td>\n",
       "      <td>0.010988</td>\n",
       "      <td>0.008036</td>\n",
       "      <td>0.002212</td>\n",
       "      <td>0.001621</td>\n",
       "      <td>0.005530</td>\n",
       "      <td>0.006818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoe</th>\n",
       "      <td>0.009245</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003225</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001845</td>\n",
       "      <td>0.002542</td>\n",
       "      <td>0.004275</td>\n",
       "      <td>0.004373</td>\n",
       "      <td>0.002134</td>\n",
       "      <td>0.001221</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010147</td>\n",
       "      <td>0.009064</td>\n",
       "      <td>0.004659</td>\n",
       "      <td>0.001311</td>\n",
       "      <td>0.001038</td>\n",
       "      <td>0.002035</td>\n",
       "      <td>0.002939</td>\n",
       "      <td>0.003169</td>\n",
       "      <td>0.002656</td>\n",
       "      <td>0.002130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoey</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010202</td>\n",
       "      <td>0.010542</td>\n",
       "      <td>0.008716</td>\n",
       "      <td>0.005578</td>\n",
       "      <td>0.002431</td>\n",
       "      <td>0.000437</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>0.000786</td>\n",
       "      <td>0.001459</td>\n",
       "      <td>0.001728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zuri</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041216</td>\n",
       "      <td>0.032491</td>\n",
       "      <td>0.029391</td>\n",
       "      <td>0.026944</td>\n",
       "      <td>0.022914</td>\n",
       "      <td>0.018828</td>\n",
       "      <td>0.013810</td>\n",
       "      <td>0.008968</td>\n",
       "      <td>0.007011</td>\n",
       "      <td>0.007291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2337 rows × 135 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "id": "c696e452-966e-4209-97b1-d6d6684ba542",
   "metadata": {},
   "source": [
    "Plotting function"
   ]
  },
  {
   "cell_type": "code",
   "id": "2403af70-6116-4523-9036-0467a142a164",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:22.316478Z",
     "start_time": "2025-10-17T17:50:22.313747Z"
    }
   },
   "source": [
    "def basic_plot(idx):\n",
    "    cols = [col.startswith('year') for col in final.columns]\n",
    "    all_years = [int(col.removeprefix('year_')) for col in final.columns[cols]]\n",
    "\n",
    "    if isinstance(idx, str):\n",
    "        counts = final.loc[idx][cols]\n",
    "        title = idx\n",
    "    else:\n",
    "        counts = final.iloc[idx][cols]\n",
    "        title = final.iloc[idx].name\n",
    "\n",
    "    plt.plot(all_years, counts.values)\n",
    "    # plt.ylim(-0.1, 1.1)\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Year')\n",
    "    plt.ylabel('Count')\n",
    "    plt.show()\n",
    "    return"
   ],
   "outputs": [],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "id": "5ac11144-8fd8-4044-b4bf-07ce105322ef",
   "metadata": {},
   "source": [
    "We can now easily look at the evolution of a given name over the years"
   ]
  },
  {
   "cell_type": "code",
   "id": "f03c6c96",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:22.512977Z",
     "start_time": "2025-10-17T17:50:22.415604Z"
    }
   },
   "source": [
    "print(len(final))\n",
    "basic_plot('Anastasia')\n",
    "basic_plot('Leo')"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2337\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "id": "e4799cd6-f209-48b4-9d7e-f171362c5c8c",
   "metadata": {},
   "source": [
    "## Classical anomaly detection"
   ]
  },
  {
   "cell_type": "code",
   "id": "0f25516e-d8da-4612-b716-87f143fead52",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:23.077778Z",
     "start_time": "2025-10-17T17:50:22.581810Z"
    }
   },
   "source": [
    "model = IsolationForest(random_seed=1, n_trees=1000)\n",
    "model.fit(np.array(final))\n",
    "scores = model.score_samples(np.array(final))\n",
    "ordered_scores, ordered_index = zip(*sorted(zip(scores, final.index)))\n",
    "\n",
    "print(f\"Top 10 weirdest names : {ordered_index[:10]}\")\n",
    "print(f\"Top 10 most regular names : {ordered_index[-10:]}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 weirdest names : ('Manuel', 'Marshall', 'Alfonso', 'Vincent', 'Margarita', 'Byron', 'Rudy', 'Benito', 'Peter', 'Ruben')\n",
      "Top 10 most regular names : ('Kian', 'Jayla', 'Kenzie', 'Ibrahim', 'Teagan', 'Phoenix', 'Kaliyah', 'Holden', 'Cali', 'Raegan')\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "id": "4ce10ca9-c592-42b4-973b-f7f0a8bf3815",
   "metadata": {},
   "source": [
    "Let's have a look at their distributions"
   ]
  },
  {
   "cell_type": "code",
   "id": "25ea04e3-e446-4854-9b8c-f1c231536e2f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:23.224795Z",
     "start_time": "2025-10-17T17:50:23.081512Z"
    }
   },
   "source": [
    "for normal in ordered_index[-4:]:\n",
    "    basic_plot(normal)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "id": "7cceb0df-4f07-4fb0-b5cc-e86e29053fe0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:23.376737Z",
     "start_time": "2025-10-17T17:50:23.228531Z"
    }
   },
   "source": [
    "for weird in ordered_index[:4]:\n",
    "    basic_plot(weird)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "markdown",
   "id": "e2cb8939-ceca-469c-8ead-79ba3877e7d5",
   "metadata": {},
   "source": [
    "It seems that anomalies are either very localised peak or very recent trending names."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c696fd1-98da-419d-bbe8-51f377cb2ac2",
   "metadata": {},
   "source": [
    "## Active Anomaly Detection "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "653700d8-6199-476a-b260-7158fe3f034f",
   "metadata": {},
   "source": [
    "First, we need a function helping us to make a decision.\n",
    "\n",
    "### Comment dummy decision function and uncomment interactive one"
   ]
  },
  {
   "cell_type": "code",
   "id": "b0f8195d-8b4e-44e3-b73f-0d446a50a8e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:23.381761Z",
     "start_time": "2025-10-17T17:50:23.380002Z"
    }
   },
   "source": [
    "# Comment\n",
    "def help_decision(metadata, data, session):\n",
    "    \"\"\"Dummy, says YES to everything\"\"\"\n",
    "    return Label.ANOMALY\n",
    "\n",
    "### UNCOMMENT\n",
    "# def help_decision(metadata, data, session):\n",
    "#     \"\"\"Plots data and asks expert interactively\"\"\"\n",
    "#     basic_plot(metadata)\n",
    "#     return prompt_decision_callback(metadata, data, session)"
   ],
   "outputs": [],
   "execution_count": 10
  },
  {
   "cell_type": "markdown",
   "id": "6f5d4c2d-8545-447c-a7b4-b9fa5f1a173f",
   "metadata": {},
   "source": [
    "Let's create a model and run a session"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9a3d594-a818-4db4-ad0c-383111fb04c9",
   "metadata": {},
   "source": [
    "Let's run PineForest and say YES every time we see a recent growth"
   ]
  },
  {
   "cell_type": "code",
   "id": "f6861278-7822-4a86-910c-4772de2c1487",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:26.472454Z",
     "start_time": "2025-10-17T17:50:23.384619Z"
    }
   },
   "source": [
    "model = PineForest(\n",
    "    # Number of trees to use for predictions\n",
    "    n_trees=256,\n",
    "    # Number of new trees to grow for each decision\n",
    "    n_spare_trees=768,\n",
    "    # Fix random seed for reproducibility\n",
    "    random_seed=0,\n",
    ")\n",
    "session = Session(\n",
    "    data=final,\n",
    "    metadata=final.index,\n",
    "    model=model,\n",
    "    decision_callback=help_decision,\n",
    "    on_decision_callbacks=[\n",
    "        TerminateAfter(10),\n",
    "    ],\n",
    ")\n",
    "session.run()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<coniferest.session.Session at 0x12f081b20>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "cell_type": "markdown",
   "id": "5e245ee2-08e6-4304-ae86-f65860280c63",
   "metadata": {},
   "source": [
    "Wow! Good almost 100% of the behavior we were looking for\n",
    "\n",
    "Now we can run it again and say YES every time we see a sharp peak"
   ]
  },
  {
   "cell_type": "code",
   "id": "4dd0746e-594d-4333-95ef-6404050f277a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-17T17:50:32.793087Z",
     "start_time": "2025-10-17T17:50:26.502186Z"
    }
   },
   "source": [
    "model = PineForest(\n",
    "    # Number of trees to use for predictions\n",
    "    n_trees=256,\n",
    "    # Number of new trees to grow for each decision\n",
    "    n_spare_trees=768,\n",
    "    # Fix random seed for reproducibility\n",
    "    random_seed=0,\n",
    ")\n",
    "session = Session(\n",
    "    data=final,\n",
    "    metadata=final.index,\n",
    "    model=model,\n",
    "    decision_callback=help_decision,\n",
    "    on_decision_callbacks=[\n",
    "        TerminateAfter(20),\n",
    "    ],\n",
    ")\n",
    "session.run()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<coniferest.session.Session at 0x12f1930b0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "markdown",
   "id": "cbed8132-fa11-4b64-8caa-f6c3656c56d0",
   "metadata": {},
   "source": [
    "PineForest learns the profile interesting for the user and outputs it."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Try to change Pineforest hyperparameters and see how results change. Try different random seeds and number of trees."
   ]
  },
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   "id": "c2b9e528-8c2b-415d-a4b2-58302bb125d9",
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     "start_time": "2025-10-17T17:50:32.821811Z"
    }
   },
   "source": [],
   "outputs": [],
   "execution_count": null
  }
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