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- {
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- "nbformat": 4,
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- "nbformat_minor": 0,
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- "metadata": {
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- "colab": {
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- "provenance": []
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- },
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- "kernelspec": {
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- "name": "python3",
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- "display_name": "Python 3"
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- },
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- "language_info": {
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- "name": "python"
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- }
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- },
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 5,
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- "metadata": {
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- "colab": {
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- "base_uri": "https://localhost:8080/"
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- },
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- "id": "XQZJSSopDet9",
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- "outputId": "61ea737f-4653-41ba-964f-f4c88e7a0738"
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- },
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- "outputs": [
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- {
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- "output_type": "stream",
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- "name": "stdout",
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- "text": [
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- "Requirement already satisfied: pandas in /usr/local/lib/python3.12/dist-packages (2.2.2)\n",
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- "Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (2.0.2)\n",
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- "Requirement already satisfied: matplotlib in /usr/local/lib/python3.12/dist-packages (3.10.0)\n",
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- "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.12/dist-packages (1.6.1)\n",
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- "Requirement already satisfied: statsmodels in /usr/local/lib/python3.12/dist-packages (0.14.6)\n",
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- "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas) (2.9.0.post0)\n",
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- "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas) (2025.2)\n",
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- "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.12/dist-packages (from pandas) (2026.1)\n",
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- "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (1.3.3)\n",
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- "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (0.12.1)\n",
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- "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (4.62.1)\n",
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- "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (1.5.0)\n",
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- "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (26.1)\n",
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- "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (11.3.0)\n",
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- "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib) (3.3.2)\n",
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- "Requirement already satisfied: scipy>=1.6.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn) (1.16.3)\n",
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- "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn) (1.5.3)\n",
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- "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn) (3.6.0)\n",
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- "Requirement already satisfied: patsy>=0.5.6 in /usr/local/lib/python3.12/dist-packages (from statsmodels) (1.0.2)\n",
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- "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n"
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- ]
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- }
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- ],
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- "source": [
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- "!pip install pandas numpy matplotlib scikit-learn statsmodels"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "source": [
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- "import random\n",
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- "import numpy as np\n",
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- "import pandas as pd\n",
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- "\n",
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- "random.seed(42)\n",
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- "np.random.seed(42)"
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- ],
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- "metadata": {
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- "id": "yzXlo3jYDi0f"
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- },
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- "execution_count": 6,
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- "outputs": []
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- },
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- {
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- "cell_type": "code",
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- "source": [
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- "print(\"=\" * 50)\n",
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- "print(\"STEP 1/2: Data Creation (real data + synthetic enrichment)\")\n",
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- "print(\"=\" * 50)"
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- ],
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- "metadata": {
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- "colab": {
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- "base_uri": "https://localhost:8080/"
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- },
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- "id": "EL_CQaWsDkGw",
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- "outputId": "793b948a-a315-43d5-d2bc-6b8589dcb4b4"
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- },
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- "execution_count": 7,
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- "outputs": [
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- {
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- "output_type": "stream",
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- "name": "stdout",
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- "text": [
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- "==================================================\n",
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- "STEP 1/2: Data Creation (real data + synthetic enrichment)\n",
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- "==================================================\n"
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- ]
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- }
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- ]
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- },
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- {
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- "cell_type": "code",
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- "source": [
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- "jobs_df = pd.read_csv(\"CSV-JOBS.csv\")\n",
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- "\n",
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- "print(\"Shape:\", jobs_df.shape)\n",
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- "print(\"Columns:\")\n",
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- "print(jobs_df.columns.tolist())\n",
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- "\n",
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- "display(jobs_df.head())"
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- ],
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- "metadata": {
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- "colab": {
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- "base_uri": "https://localhost:8080/",
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- "height": 505
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- },
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- "id": "jyIW1KljDlXP",
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- "outputId": "ea7ebc0a-bf5f-4923-b855-2d35cbd83968"
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- },
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- "execution_count": 8,
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- "outputs": [
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- {
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- "output_type": "stream",
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- "name": "stdout",
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- "text": [
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- "Shape: (103, 9)\n",
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- "Columns:\n",
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- "['ID', 'title', 'Domain(s)', 'Grade', 'Type of contract', 'Institution(s) ', 'Location(s)', 'Deadline ', 'Link to Content']\n"
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- ]
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- "output_type": "display_data",
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- "text/plain": [
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- " ID title \\\n",
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- "0 19702 Project Assistant \n",
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- "1 19703 Policy Officer \n",
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- "2 19664 Senior Military Advisor to the Executive Director \n",
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- "3 19665 Structures Expert \n",
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- "4 19666 Certification Expert - Hydromechanical and Fli... \n",
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- "\n",
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- " Domain(s) Grade Type of contract \\\n",
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- "0 Justice and human rights FG III Contract staff \n",
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- "1 Justice and human rights FG IV Contract staff \n",
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- "2 Transport AD 10 Temporary staff \n",
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- "3 Transport AD 7 Temporary staff \n",
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- "4 Transport AD 7 Temporary staff \n",
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- "\n",
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- " Institution(s) Location(s) \\\n",
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- "0 (FRA) European Union Agency for Fundamental Ri... Vienna (Austria) \n",
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- "1 (FRA) European Union Agency for Fundamental Ri... Vienna (Austria) \n",
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- "2 (EASA) European Union Aviation Safety Agency Cologne (Germany) \n",
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- "3 (EASA) European Union Aviation Safety Agency Cologne (Germany) \n",
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- "4 (EASA) European Union Aviation Safety Agency Cologne (Germany) \n",
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- "\n",
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- " Deadline Link to Content \n",
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- "0 30/04/2026 - 13:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
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- "1 30/04/2026 - 13:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
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- "2 30/04/2026 - 23:59 https://eu-careers.europa.eu/en/job-opportunit... \n",
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- "3 30/04/2026 - 23:59 https://eu-careers.europa.eu/en/job-opportunit... \n",
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- "<style scoped>\n",
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- " .dataframe tbody tr th:only-of-type {\n",
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- "</style>\n",
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- "<table border=\"1\" class=\"dataframe\">\n",
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- " <thead>\n",
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- " <tr style=\"text-align: right;\">\n",
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- " <th></th>\n",
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- " <th>ID</th>\n",
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- " <th>title</th>\n",
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- " <th>Domain(s)</th>\n",
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- " <th>Grade</th>\n",
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- " <th>Type of contract</th>\n",
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- " <th>Institution(s)</th>\n",
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- " <th>Location(s)</th>\n",
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- " <th>Deadline</th>\n",
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- " <th>Link to Content</th>\n",
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- " <td>(FRA) European Union Agency for Fundamental Ri...</td>\n",
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- " <td>Vienna (Austria)</td>\n",
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- " <td>30/04/2026 - 13:00</td>\n",
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- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>1</th>\n",
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- " <td>19703</td>\n",
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- " <td>Policy Officer</td>\n",
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- " <td>Justice and human rights</td>\n",
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- " <td>FG IV</td>\n",
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- " <td>Contract staff</td>\n",
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- " <td>(FRA) European Union Agency for Fundamental Ri...</td>\n",
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- " <td>Vienna (Austria)</td>\n",
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- " <td>30/04/2026 - 13:00</td>\n",
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- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
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- " <th>2</th>\n",
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- " <td>19664</td>\n",
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- " <td>Senior Military Advisor to the Executive Director</td>\n",
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- " <td>Transport</td>\n",
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- " <td>AD 10</td>\n",
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- " <td>Temporary staff</td>\n",
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- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
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- " <td>Cologne (Germany)</td>\n",
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- " <td>30/04/2026 - 23:59</td>\n",
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- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>3</th>\n",
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- " <td>19665</td>\n",
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- " <td>Structures Expert</td>\n",
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- " <td>Transport</td>\n",
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- " <td>AD 7</td>\n",
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- " <td>Temporary staff</td>\n",
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- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
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- " <td>Cologne (Germany)</td>\n",
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- " <td>30/04/2026 - 23:59</td>\n",
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- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>4</th>\n",
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- " <td>19666</td>\n",
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- " <td>Certification Expert - Hydromechanical and Fli...</td>\n",
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- " <td>Transport</td>\n",
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- " <td>AD 7</td>\n",
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- " <td>Temporary staff</td>\n",
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- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
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- " <td>Cologne (Germany)</td>\n",
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- " <td>30/04/2026 - 23:59</td>\n",
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- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
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- " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-94849428-3ad1-4840-b983-058c86036565')\"\n",
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- " title=\"Convert this dataframe to an interactive table.\"\n",
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- "\n",
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- " <style>\n",
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- " .colab-df-container {\n",
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- " display:flex;\n",
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- " gap: 12px;\n",
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- " }\n",
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- "\n",
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- " .colab-df-convert {\n",
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- " background-color: #E8F0FE;\n",
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- " border: none;\n",
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- " border-radius: 50%;\n",
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- " cursor: pointer;\n",
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- " display: none;\n",
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- " fill: #1967D2;\n",
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- " height: 32px;\n",
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- " padding: 0 0 0 0;\n",
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- " width: 32px;\n",
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- " }\n",
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- "\n",
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- " .colab-df-convert:hover {\n",
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- " background-color: #E2EBFA;\n",
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- " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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- " fill: #174EA6;\n",
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- " }\n",
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- "\n",
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- " .colab-df-buttons div {\n",
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- " margin-bottom: 4px;\n",
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- " }\n",
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- "\n",
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- " [theme=dark] .colab-df-convert {\n",
301
- " background-color: #3B4455;\n",
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- " fill: #D2E3FC;\n",
303
- " }\n",
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- "\n",
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- " [theme=dark] .colab-df-convert:hover {\n",
306
- " background-color: #434B5C;\n",
307
- " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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- " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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- " fill: #FFFFFF;\n",
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- " }\n",
311
- " </style>\n",
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- "\n",
313
- " <script>\n",
314
- " const buttonEl =\n",
315
- " document.querySelector('#df-94849428-3ad1-4840-b983-058c86036565 button.colab-df-convert');\n",
316
- " buttonEl.style.display =\n",
317
- " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
318
- "\n",
319
- " async function convertToInteractive(key) {\n",
320
- " const element = document.querySelector('#df-94849428-3ad1-4840-b983-058c86036565');\n",
321
- " const dataTable =\n",
322
- " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
323
- " [key], {});\n",
324
- " if (!dataTable) return;\n",
325
- "\n",
326
- " const docLinkHtml = 'Like what you see? Visit the ' +\n",
327
- " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
328
- " + ' to learn more about interactive tables.';\n",
329
- " element.innerHTML = '';\n",
330
- " dataTable['output_type'] = 'display_data';\n",
331
- " await google.colab.output.renderOutput(dataTable, element);\n",
332
- " const docLink = document.createElement('div');\n",
333
- " docLink.innerHTML = docLinkHtml;\n",
334
- " element.appendChild(docLink);\n",
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- " }\n",
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- " </script>\n",
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- " </div>\n",
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- "\n",
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- "\n",
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- " </div>\n",
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- " </div>\n"
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- ],
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- "application/vnd.google.colaboratory.intrinsic+json": {
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- "type": "dataframe",
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- "summary": "{\n \"name\": \"display(jobs_df\",\n \"rows\": 5,\n \"fields\": [\n {\n \"column\": \"ID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 20,\n \"min\": 19664,\n \"max\": 19703,\n \"num_unique_values\": 5,\n \"samples\": [\n 19703,\n 19666,\n 19664\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"Policy Officer\",\n \"Certification Expert - Hydromechanical and Flight Control Systems\",\n \"Senior Military Advisor to the Executive Director\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Domain(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Transport\",\n \"Justice and human rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Grade\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"FG IV\",\n \"AD 7\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Type of contract\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Temporary staff\",\n \"Contract staff\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Institution(s) \",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"(EASA) European Union Aviation Safety Agency\",\n \"(FRA) European Union Agency for Fundamental Rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Location(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Cologne (Germany)\",\n \"Vienna (Austria)\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Deadline \",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"30/04/2026 - 23:59\",\n \"30/04/2026 - 13:00\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Link to Content\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"https://eu-careers.europa.eu/en/job-opportunities/policy-officer/fra-ca-polof-fgiv-2026\",\n \"https://eu-careers.europa.eu/en/job-opportunities/certification-expert-hydromechanical-and-flight-control-systems/easa-ad-2026-997\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
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- }
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- },
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- "metadata": {}
349
- }
350
- ]
351
- },
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- {
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- "cell_type": "code",
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- "source": [
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- "jobs_clean = jobs_df.copy()\n",
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- "\n",
357
- "jobs_clean.columns = jobs_clean.columns.str.strip()\n",
358
- "jobs_clean[\"Deadline\"] = pd.to_datetime(jobs_clean[\"Deadline\"], errors=\"coerce\")\n",
359
- "\n",
360
- "jobs_clean = jobs_clean.dropna(subset=[\"title\", \"Domain(s)\", \"Type of contract\", \"Deadline\"])\n",
361
- "\n",
362
- "print(\"Cleaned shape:\", jobs_clean.shape)\n",
363
- "display(jobs_clean.head())"
364
- ],
365
- "metadata": {
366
- "colab": {
367
- "base_uri": "https://localhost:8080/",
368
- "height": 505
369
- },
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- "id": "UgMfW50wDm1g",
371
- "outputId": "4b88a153-aa33-44db-87ae-28013ca4ac56"
372
- },
373
- "execution_count": 9,
374
- "outputs": [
375
- {
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- "output_type": "stream",
377
- "name": "stdout",
378
- "text": [
379
- "Cleaned shape: (99, 9)\n"
380
- ]
381
- },
382
- {
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- "output_type": "stream",
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- "name": "stderr",
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- "text": [
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- "/tmp/ipykernel_25014/2873856445.py:4: UserWarning: Parsing dates in %d/%m/%Y - %H:%M format when dayfirst=False (the default) was specified. Pass `dayfirst=True` or specify a format to silence this warning.\n",
387
- " jobs_clean[\"Deadline\"] = pd.to_datetime(jobs_clean[\"Deadline\"], errors=\"coerce\")\n"
388
- ]
389
- },
390
- {
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- "output_type": "display_data",
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- "data": {
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- "text/plain": [
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- " ID title \\\n",
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- "0 19702 Project Assistant \n",
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- "1 19703 Policy Officer \n",
397
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405
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406
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407
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408
- " Institution(s) Location(s) \\\n",
409
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410
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411
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419
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580
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582
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- "summary": "{\n \"name\": \"display(jobs_clean\",\n \"rows\": 5,\n \"fields\": [\n {\n \"column\": \"ID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 20,\n \"min\": 19664,\n \"max\": 19703,\n \"num_unique_values\": 5,\n \"samples\": [\n 19703,\n 19666,\n 19664\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"Policy Officer\",\n \"Certification Expert - Hydromechanical and Flight Control Systems\",\n \"Senior Military Advisor to the Executive Director\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Domain(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Transport\",\n \"Justice and human rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Grade\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"FG IV\",\n \"AD 7\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Type of contract\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Temporary staff\",\n \"Contract staff\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Institution(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"(EASA) European Union Aviation Safety Agency\",\n \"(FRA) European Union Agency for Fundamental Rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Location(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Cologne (Germany)\",\n \"Vienna (Austria)\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Deadline\",\n \"properties\": {\n \"dtype\": \"date\",\n \"min\": \"2026-04-30 13:00:00\",\n \"max\": \"2026-04-30 23:59:00\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"2026-04-30 23:59:00\",\n \"2026-04-30 13:00:00\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Link to Content\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"https://eu-careers.europa.eu/en/job-opportunities/policy-officer/fra-ca-polof-fgiv-2026\",\n \"https://eu-careers.europa.eu/en/job-opportunities/certification-expert-hydromechanical-and-flight-control-systems/easa-ad-2026-997\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
604
- }
605
- },
606
- "metadata": {}
607
- }
608
- ]
609
- },
610
- {
611
- "cell_type": "code",
612
- "source": [
613
- "print(\"Unique domains:\", jobs_clean[\"Domain(s)\"].nunique())\n",
614
- "print(\"Unique contract types:\", jobs_clean[\"Type of contract\"].nunique())\n",
615
- "print(\"Unique institutions:\", jobs_clean[\"Institution(s)\"].nunique())\n",
616
- "print(\"Unique locations:\", jobs_clean[\"Location(s)\"].nunique())"
617
- ],
618
- "metadata": {
619
- "colab": {
620
- "base_uri": "https://localhost:8080/"
621
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622
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623
- "outputId": "1230b9e7-4d0b-44da-bf73-61a5a39d0ab9"
624
- },
625
- "execution_count": 10,
626
- "outputs": [
627
- {
628
- "output_type": "stream",
629
- "name": "stdout",
630
- "text": [
631
- "Unique domains: 35\n",
632
- "Unique contract types: 5\n",
633
- "Unique institutions: 38\n",
634
- "Unique locations: 31\n"
635
- ]
636
- }
637
- ]
638
- },
639
- {
640
- "cell_type": "code",
641
- "source": [
642
- "comments_by_demand = {\n",
643
- " \"high\": [\n",
644
- " \"This role appears to be in strong demand across institutions.\",\n",
645
- " \"The labor market for this profile looks highly competitive.\",\n",
646
- " \"This posting suggests strong employment opportunities.\",\n",
647
- " \"Demand for this skill set appears to be growing.\",\n",
648
- " \"This category seems to attract significant hiring activity.\"\n",
649
- " ],\n",
650
- " \"stable\": [\n",
651
- " \"This role appears to have steady demand.\",\n",
652
- " \"The market for this profile looks relatively balanced.\",\n",
653
- " \"This posting suggests moderate but stable opportunities.\",\n",
654
- " \"Demand appears consistent across institutions.\",\n",
655
- " \"This category seems to have regular hiring activity.\"\n",
656
- " ],\n",
657
- " \"low\": [\n",
658
- " \"This role appears to have weaker demand.\",\n",
659
- " \"The market for this profile looks more limited.\",\n",
660
- " \"This posting suggests fewer employment opportunities.\",\n",
661
- " \"Demand for this skill set appears relatively low.\",\n",
662
- " \"This category seems to have less hiring activity.\"\n",
663
- " ]\n",
664
- "}"
665
- ],
666
- "metadata": {
667
- "id": "HHqueIqZDqVe"
668
- },
669
- "execution_count": 11,
670
- "outputs": []
671
- },
672
- {
673
- "cell_type": "code",
674
- "source": [
675
- "jobs_enriched = jobs_clean.copy()\n",
676
- "\n",
677
- "today = pd.Timestamp.today().normalize()\n",
678
- "jobs_enriched[\"days_to_deadline\"] = (jobs_enriched[\"Deadline\"] - today).dt.days\n",
679
- "\n",
680
- "def urgency_from_days(days):\n",
681
- " if pd.isna(days):\n",
682
- " return random.randint(3, 6)\n",
683
- " if days <= 7:\n",
684
- " return random.randint(8, 10)\n",
685
- " elif days <= 21:\n",
686
- " return random.randint(5, 8)\n",
687
- " else:\n",
688
- " return random.randint(2, 6)\n",
689
- "\n",
690
- "jobs_enriched[\"urgency_score\"] = jobs_enriched[\"days_to_deadline\"].apply(urgency_from_days)\n",
691
- "\n",
692
- "def demand_from_urgency(score):\n",
693
- " if score >= 8:\n",
694
- " return random.randint(7, 10)\n",
695
- " elif score >= 5:\n",
696
- " return random.randint(4, 7)\n",
697
- " else:\n",
698
- " return random.randint(2, 5)\n",
699
- "\n",
700
- "jobs_enriched[\"job_demand_score\"] = jobs_enriched[\"urgency_score\"].apply(demand_from_urgency)\n",
701
- "\n",
702
- "def demand_label(score):\n",
703
- " if score <= 3:\n",
704
- " return \"low\"\n",
705
- " elif score <= 6:\n",
706
- " return \"stable\"\n",
707
- " else:\n",
708
- " return \"high\"\n",
709
- "\n",
710
- "jobs_enriched[\"demand_label\"] = jobs_enriched[\"job_demand_score\"].apply(demand_label)\n",
711
- "\n",
712
- "jobs_enriched[\"estimated_salary\"] = np.random.randint(35000, 95000, len(jobs_enriched))\n",
713
- "\n",
714
- "jobs_enriched[\"automation_risk\"] = np.random.choice(\n",
715
- " [\"low\", \"medium\", \"high\"],\n",
716
- " size=len(jobs_enriched),\n",
717
- " p=[0.35, 0.45, 0.20]\n",
718
- ")\n",
719
- "\n",
720
- "jobs_enriched[\"estimated_applications\"] = np.random.randint(20, 250, len(jobs_enriched))\n",
721
- "\n",
722
- "jobs_enriched[\"job_comment\"] = jobs_enriched[\"demand_label\"].apply(\n",
723
- " lambda x: random.choice(comments_by_demand[x])\n",
724
- ")\n",
725
- "\n",
726
- "display(jobs_enriched.head())"
727
- ],
728
- "metadata": {
729
- "colab": {
730
- "base_uri": "https://localhost:8080/",
731
- "height": 539
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734
- "outputId": "1f359396-203b-4d7a-8671-d58ccee2df1a"
735
- },
736
- "execution_count": 12,
737
- "outputs": [
738
- {
739
- "output_type": "display_data",
740
- "data": {
741
- "text/plain": [
742
- " ID title \\\n",
743
- "0 19702 Project Assistant \n",
744
- "1 19703 Policy Officer \n",
745
- "2 19664 Senior Military Advisor to the Executive Director \n",
746
- "3 19665 Structures Expert \n",
747
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748
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749
- " Domain(s) Grade Type of contract \\\n",
750
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751
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752
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753
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754
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755
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756
- " Institution(s) Location(s) \\\n",
757
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758
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759
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760
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761
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762
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763
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764
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765
- "1 2026-04-30 13:00:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
766
- "2 2026-04-30 23:59:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
767
- "3 2026-04-30 23:59:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
768
- "4 2026-04-30 23:59:00 https://eu-careers.europa.eu/en/job-opportunit... \n",
769
- "\n",
770
- " days_to_deadline urgency_score job_demand_score demand_label \\\n",
771
- "0 1 10 9 high \n",
772
- "1 1 8 10 high \n",
773
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774
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775
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776
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777
- " estimated_salary automation_risk estimated_applications \\\n",
778
- "0 91422 low 87 \n",
779
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780
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781
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783
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784
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785
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786
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787
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- " }\n",
807
- "</style>\n",
808
- "<table border=\"1\" class=\"dataframe\">\n",
809
- " <thead>\n",
810
- " <tr style=\"text-align: right;\">\n",
811
- " <th></th>\n",
812
- " <th>ID</th>\n",
813
- " <th>title</th>\n",
814
- " <th>Domain(s)</th>\n",
815
- " <th>Grade</th>\n",
816
- " <th>Type of contract</th>\n",
817
- " <th>Institution(s)</th>\n",
818
- " <th>Location(s)</th>\n",
819
- " <th>Deadline</th>\n",
820
- " <th>Link to Content</th>\n",
821
- " <th>days_to_deadline</th>\n",
822
- " <th>urgency_score</th>\n",
823
- " <th>job_demand_score</th>\n",
824
- " <th>demand_label</th>\n",
825
- " <th>estimated_salary</th>\n",
826
- " <th>automation_risk</th>\n",
827
- " <th>estimated_applications</th>\n",
828
- " <th>job_comment</th>\n",
829
- " </tr>\n",
830
- " </thead>\n",
831
- " <tbody>\n",
832
- " <tr>\n",
833
- " <th>0</th>\n",
834
- " <td>19702</td>\n",
835
- " <td>Project Assistant</td>\n",
836
- " <td>Justice and human rights</td>\n",
837
- " <td>FG III</td>\n",
838
- " <td>Contract staff</td>\n",
839
- " <td>(FRA) European Union Agency for Fundamental Ri...</td>\n",
840
- " <td>Vienna (Austria)</td>\n",
841
- " <td>2026-04-30 13:00:00</td>\n",
842
- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
843
- " <td>1</td>\n",
844
- " <td>10</td>\n",
845
- " <td>9</td>\n",
846
- " <td>high</td>\n",
847
- " <td>91422</td>\n",
848
- " <td>low</td>\n",
849
- " <td>87</td>\n",
850
- " <td>Demand for this skill set appears to be growing.</td>\n",
851
- " </tr>\n",
852
- " <tr>\n",
853
- " <th>1</th>\n",
854
- " <td>19703</td>\n",
855
- " <td>Policy Officer</td>\n",
856
- " <td>Justice and human rights</td>\n",
857
- " <td>FG IV</td>\n",
858
- " <td>Contract staff</td>\n",
859
- " <td>(FRA) European Union Agency for Fundamental Ri...</td>\n",
860
- " <td>Vienna (Austria)</td>\n",
861
- " <td>2026-04-30 13:00:00</td>\n",
862
- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
863
- " <td>1</td>\n",
864
- " <td>8</td>\n",
865
- " <td>10</td>\n",
866
- " <td>high</td>\n",
867
- " <td>50795</td>\n",
868
- " <td>low</td>\n",
869
- " <td>202</td>\n",
870
- " <td>This posting suggests strong employment opport...</td>\n",
871
- " </tr>\n",
872
- " <tr>\n",
873
- " <th>2</th>\n",
874
- " <td>19664</td>\n",
875
- " <td>Senior Military Advisor to the Executive Director</td>\n",
876
- " <td>Transport</td>\n",
877
- " <td>AD 10</td>\n",
878
- " <td>Temporary staff</td>\n",
879
- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
880
- " <td>Cologne (Germany)</td>\n",
881
- " <td>2026-04-30 23:59:00</td>\n",
882
- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
883
- " <td>1</td>\n",
884
- " <td>8</td>\n",
885
- " <td>10</td>\n",
886
- " <td>high</td>\n",
887
- " <td>35860</td>\n",
888
- " <td>low</td>\n",
889
- " <td>222</td>\n",
890
- " <td>This role appears to be in strong demand acros...</td>\n",
891
- " </tr>\n",
892
- " <tr>\n",
893
- " <th>3</th>\n",
894
- " <td>19665</td>\n",
895
- " <td>Structures Expert</td>\n",
896
- " <td>Transport</td>\n",
897
- " <td>AD 7</td>\n",
898
- " <td>Temporary staff</td>\n",
899
- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
900
- " <td>Cologne (Germany)</td>\n",
901
- " <td>2026-04-30 23:59:00</td>\n",
902
- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
903
- " <td>1</td>\n",
904
- " <td>10</td>\n",
905
- " <td>9</td>\n",
906
- " <td>high</td>\n",
907
- " <td>73158</td>\n",
908
- " <td>medium</td>\n",
909
- " <td>203</td>\n",
910
- " <td>The labor market for this profile looks highly...</td>\n",
911
- " </tr>\n",
912
- " <tr>\n",
913
- " <th>4</th>\n",
914
- " <td>19666</td>\n",
915
- " <td>Certification Expert - Hydromechanical and Fli...</td>\n",
916
- " <td>Transport</td>\n",
917
- " <td>AD 7</td>\n",
918
- " <td>Temporary staff</td>\n",
919
- " <td>(EASA) European Union Aviation Safety Agency</td>\n",
920
- " <td>Cologne (Germany)</td>\n",
921
- " <td>2026-04-30 23:59:00</td>\n",
922
- " <td>https://eu-careers.europa.eu/en/job-opportunit...</td>\n",
923
- " <td>1</td>\n",
924
- " <td>9</td>\n",
925
- " <td>8</td>\n",
926
- " <td>high</td>\n",
927
- " <td>89343</td>\n",
928
- " <td>low</td>\n",
929
- " <td>142</td>\n",
930
- " <td>The labor market for this profile looks highly...</td>\n",
931
- " </tr>\n",
932
- " </tbody>\n",
933
- "</table>\n",
934
- "</div>\n",
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993
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994
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995
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996
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997
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998
- " [key], {});\n",
999
- " if (!dataTable) return;\n",
1000
- "\n",
1001
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1003
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1005
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1016
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1019
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1020
- "summary": "{\n \"name\": \"display(jobs_enriched\",\n \"rows\": 5,\n \"fields\": [\n {\n \"column\": \"ID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 20,\n \"min\": 19664,\n \"max\": 19703,\n \"num_unique_values\": 5,\n \"samples\": [\n 19703,\n 19666,\n 19664\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"Policy Officer\",\n \"Certification Expert - Hydromechanical and Flight Control Systems\",\n \"Senior Military Advisor to the Executive Director\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Domain(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Transport\",\n \"Justice and human rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Grade\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"FG IV\",\n \"AD 7\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Type of contract\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Temporary staff\",\n \"Contract staff\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Institution(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"(EASA) European Union Aviation Safety Agency\",\n \"(FRA) European Union Agency for Fundamental Rights\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Location(s)\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Cologne (Germany)\",\n \"Vienna (Austria)\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Deadline\",\n \"properties\": {\n \"dtype\": \"date\",\n \"min\": \"2026-04-30 13:00:00\",\n \"max\": \"2026-04-30 23:59:00\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"2026-04-30 23:59:00\",\n \"2026-04-30 13:00:00\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Link to Content\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"https://eu-careers.europa.eu/en/job-opportunities/policy-officer/fra-ca-polof-fgiv-2026\",\n \"https://eu-careers.europa.eu/en/job-opportunities/certification-expert-hydromechanical-and-flight-control-systems/easa-ad-2026-997\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"days_to_deadline\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 1,\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"urgency_score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 8,\n \"max\": 10,\n \"num_unique_values\": 3,\n \"samples\": [\n 10\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"job_demand_score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 8,\n \"max\": 10,\n \"num_unique_values\": 3,\n \"samples\": [\n 9\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"demand_label\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"high\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"estimated_salary\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 24288,\n \"min\": 35860,\n \"max\": 91422,\n \"num_unique_values\": 5,\n \"samples\": [\n 50795\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"automation_risk\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"medium\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"estimated_applications\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 55,\n \"min\": 87,\n \"max\": 222,\n \"num_unique_values\": 5,\n \"samples\": [\n 202\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"job_comment\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"This posting suggests strong employment opportunities.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
1021
- }
1022
- },
1023
- "metadata": {}
1024
- }
1025
- ]
1026
- },
1027
- {
1028
- "cell_type": "code",
1029
- "source": [
1030
- "jobs_enriched.to_csv(\"jobs_enriched.csv\", index=False)\n",
1031
- "print(\"Saved: jobs_enriched.csv\")"
1032
- ],
1033
- "metadata": {
1034
- "colab": {
1035
- "base_uri": "https://localhost:8080/"
1036
- },
1037
- "id": "s00SIZBsDtd-",
1038
- "outputId": "e5dbe4a5-e76a-48b2-ac18-866a964dfe3d"
1039
- },
1040
- "execution_count": 13,
1041
- "outputs": [
1042
- {
1043
- "output_type": "stream",
1044
- "name": "stdout",
1045
- "text": [
1046
- "Saved: jobs_enriched.csv\n"
1047
- ]
1048
- }
1049
- ]
1050
- },
1051
- {
1052
- "cell_type": "code",
1053
- "source": [
1054
- "jobs_enriched[\"deadline_month\"] = jobs_enriched[\"Deadline\"].dt.to_period(\"M\").astype(str)\n",
1055
- "\n",
1056
- "monthly_openings = (\n",
1057
- " jobs_enriched\n",
1058
- " .groupby([\"deadline_month\", \"Domain(s)\"], as_index=False)\n",
1059
- " .agg(\n",
1060
- " postings=(\"title\", \"count\"),\n",
1061
- " avg_salary=(\"estimated_salary\", \"mean\"),\n",
1062
- " avg_demand_score=(\"job_demand_score\", \"mean\"),\n",
1063
- " avg_applications=(\"estimated_applications\", \"mean\")\n",
1064
- " )\n",
1065
- ")\n",
1066
- "\n",
1067
- "display(monthly_openings.head())\n",
1068
- "print(\"Shape:\", monthly_openings.shape)"
1069
- ],
1070
- "metadata": {
1071
- "colab": {
1072
- "base_uri": "https://localhost:8080/",
1073
- "height": 241
1074
- },
1075
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1076
- "outputId": "f2fab0c5-a09f-4276-a1c7-f171375ac23b"
1077
- },
1078
- "execution_count": 14,
1079
- "outputs": [
1080
- {
1081
- "output_type": "display_data",
1082
- "data": {
1083
- "text/plain": [
1084
- " deadline_month Domain(s) postings avg_salary \\\n",
1085
- "0 2026-04 Data protection 1 79732.000000 \n",
1086
- "1 2026-04 Economics, Finance and Statistics 1 46284.000000 \n",
1087
- "2 2026-04 Human Resources 1 89886.000000 \n",
1088
- "3 2026-04 Justice and human rights 2 71108.500000 \n",
1089
- "4 2026-04 Transport 3 66120.333333 \n",
1090
- "\n",
1091
- " avg_demand_score avg_applications \n",
1092
- "0 8.0 164.0 \n",
1093
- "1 10.0 57.0 \n",
1094
- "2 7.0 43.0 \n",
1095
- "3 9.5 144.5 \n",
1096
- "4 9.0 189.0 "
1097
- ],
1098
- "text/html": [
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1100
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1101
- " <div>\n",
1102
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1103
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1104
- " vertical-align: middle;\n",
1105
- " }\n",
1106
- "\n",
1107
- " .dataframe tbody tr th {\n",
1108
- " vertical-align: top;\n",
1109
- " }\n",
1110
- "\n",
1111
- " .dataframe thead th {\n",
1112
- " text-align: right;\n",
1113
- " }\n",
1114
- "</style>\n",
1115
- "<table border=\"1\" class=\"dataframe\">\n",
1116
- " <thead>\n",
1117
- " <tr style=\"text-align: right;\">\n",
1118
- " <th></th>\n",
1119
- " <th>deadline_month</th>\n",
1120
- " <th>Domain(s)</th>\n",
1121
- " <th>postings</th>\n",
1122
- " <th>avg_salary</th>\n",
1123
- " <th>avg_demand_score</th>\n",
1124
- " <th>avg_applications</th>\n",
1125
- " </tr>\n",
1126
- " </thead>\n",
1127
- " <tbody>\n",
1128
- " <tr>\n",
1129
- " <th>0</th>\n",
1130
- " <td>2026-04</td>\n",
1131
- " <td>Data protection</td>\n",
1132
- " <td>1</td>\n",
1133
- " <td>79732.000000</td>\n",
1134
- " <td>8.0</td>\n",
1135
- " <td>164.0</td>\n",
1136
- " </tr>\n",
1137
- " <tr>\n",
1138
- " <th>1</th>\n",
1139
- " <td>2026-04</td>\n",
1140
- " <td>Economics, Finance and Statistics</td>\n",
1141
- " <td>1</td>\n",
1142
- " <td>46284.000000</td>\n",
1143
- " <td>10.0</td>\n",
1144
- " <td>57.0</td>\n",
1145
- " </tr>\n",
1146
- " <tr>\n",
1147
- " <th>2</th>\n",
1148
- " <td>2026-04</td>\n",
1149
- " <td>Human Resources</td>\n",
1150
- " <td>1</td>\n",
1151
- " <td>89886.000000</td>\n",
1152
- " <td>7.0</td>\n",
1153
- " <td>43.0</td>\n",
1154
- " </tr>\n",
1155
- " <tr>\n",
1156
- " <th>3</th>\n",
1157
- " <td>2026-04</td>\n",
1158
- " <td>Justice and human rights</td>\n",
1159
- " <td>2</td>\n",
1160
- " <td>71108.500000</td>\n",
1161
- " <td>9.5</td>\n",
1162
- " <td>144.5</td>\n",
1163
- " </tr>\n",
1164
- " <tr>\n",
1165
- " <th>4</th>\n",
1166
- " <td>2026-04</td>\n",
1167
- " <td>Transport</td>\n",
1168
- " <td>3</td>\n",
1169
- " <td>66120.333333</td>\n",
1170
- " <td>9.0</td>\n",
1171
- " <td>189.0</td>\n",
1172
- " </tr>\n",
1173
- " </tbody>\n",
1174
- "</table>\n",
1175
- "</div>\n",
1176
- " <div class=\"colab-df-buttons\">\n",
1177
- "\n",
1178
- " <div class=\"colab-df-container\">\n",
1179
- " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8cae9ab8-ac0a-4995-90c7-0321e6dabc74')\"\n",
1180
- " title=\"Convert this dataframe to an interactive table.\"\n",
1181
- " style=\"display:none;\">\n",
1182
- "\n",
1183
- " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
1184
- " <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
1185
- " </svg>\n",
1186
- " </button>\n",
1187
- "\n",
1188
- " <style>\n",
1189
- " .colab-df-container {\n",
1190
- " display:flex;\n",
1191
- " gap: 12px;\n",
1192
- " }\n",
1193
- "\n",
1194
- " .colab-df-convert {\n",
1195
- " background-color: #E8F0FE;\n",
1196
- " border: none;\n",
1197
- " border-radius: 50%;\n",
1198
- " cursor: pointer;\n",
1199
- " display: none;\n",
1200
- " fill: #1967D2;\n",
1201
- " height: 32px;\n",
1202
- " padding: 0 0 0 0;\n",
1203
- " width: 32px;\n",
1204
- " }\n",
1205
- "\n",
1206
- " .colab-df-convert:hover {\n",
1207
- " background-color: #E2EBFA;\n",
1208
- " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
1209
- " fill: #174EA6;\n",
1210
- " }\n",
1211
- "\n",
1212
- " .colab-df-buttons div {\n",
1213
- " margin-bottom: 4px;\n",
1214
- " }\n",
1215
- "\n",
1216
- " [theme=dark] .colab-df-convert {\n",
1217
- " background-color: #3B4455;\n",
1218
- " fill: #D2E3FC;\n",
1219
- " }\n",
1220
- "\n",
1221
- " [theme=dark] .colab-df-convert:hover {\n",
1222
- " background-color: #434B5C;\n",
1223
- " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
1224
- " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
1225
- " fill: #FFFFFF;\n",
1226
- " }\n",
1227
- " </style>\n",
1228
- "\n",
1229
- " <script>\n",
1230
- " const buttonEl =\n",
1231
- " document.querySelector('#df-8cae9ab8-ac0a-4995-90c7-0321e6dabc74 button.colab-df-convert');\n",
1232
- " buttonEl.style.display =\n",
1233
- " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
1234
- "\n",
1235
- " async function convertToInteractive(key) {\n",
1236
- " const element = document.querySelector('#df-8cae9ab8-ac0a-4995-90c7-0321e6dabc74');\n",
1237
- " const dataTable =\n",
1238
- " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
1239
- " [key], {});\n",
1240
- " if (!dataTable) return;\n",
1241
- "\n",
1242
- " const docLinkHtml = 'Like what you see? Visit the ' +\n",
1243
- " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
1244
- " + ' to learn more about interactive tables.';\n",
1245
- " element.innerHTML = '';\n",
1246
- " dataTable['output_type'] = 'display_data';\n",
1247
- " await google.colab.output.renderOutput(dataTable, element);\n",
1248
- " const docLink = document.createElement('div');\n",
1249
- " docLink.innerHTML = docLinkHtml;\n",
1250
- " element.appendChild(docLink);\n",
1251
- " }\n",
1252
- " </script>\n",
1253
- " </div>\n",
1254
- "\n",
1255
- "\n",
1256
- " </div>\n",
1257
- " </div>\n"
1258
- ],
1259
- "application/vnd.google.colaboratory.intrinsic+json": {
1260
- "type": "dataframe",
1261
- "summary": "{\n \"name\": \"print(\\\"Shape:\\\", monthly_openings\",\n \"rows\": 5,\n \"fields\": [\n {\n \"column\": \"deadline_month\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"2026-04\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Domain(s)\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 5,\n \"samples\": [\n \"Economics, Finance and Statistics\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"postings\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 3,\n \"num_unique_values\": 3,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"avg_salary\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 16331.975065972749,\n \"min\": 46284.0,\n \"max\": 89886.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 46284.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"avg_demand_score\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.2041594578792296,\n \"min\": 7.0,\n \"max\": 10.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 10.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"avg_applications\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 65.56294685262401,\n \"min\": 43.0,\n \"max\": 189.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 57.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
1262
- }
1263
- },
1264
- "metadata": {}
1265
- },
1266
- {
1267
- "output_type": "stream",
1268
- "name": "stdout",
1269
- "text": [
1270
- "Shape: (51, 6)\n"
1271
- ]
1272
- }
1273
- ]
1274
- },
1275
- {
1276
- "cell_type": "code",
1277
- "source": [
1278
- "monthly_openings.to_csv(\"jobs_monthly_openings.csv\", index=False)\n",
1279
- "print(\"Saved: jobs_monthly_openings.csv\")"
1280
- ],
1281
- "metadata": {
1282
- "colab": {
1283
- "base_uri": "https://localhost:8080/"
1284
- },
1285
- "id": "_WpGUgWSDxDr",
1286
- "outputId": "3214fc49-8b8f-4810-eed9-6befe196b7df"
1287
- },
1288
- "execution_count": 15,
1289
- "outputs": [
1290
- {
1291
- "output_type": "stream",
1292
- "name": "stdout",
1293
- "text": [
1294
- "Saved: jobs_monthly_openings.csv\n"
1295
- ]
1296
- }
1297
- ]
1298
- }
1299
- ]
1300
- }