feat (component-service): new section

.gitignore

@@ -37,4 +37,8 @@ build/
 *.class
 
 ## Node ##
-node_modules
+node_modules
+
+### Python ###
+*.pyc
+__pycache__/

notebooks/ai/age-food-correlation.ipynb

@@ -0,0 +1,96 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'fcid_code': '600349000', 'correlation': -0.42727039243602566, 'p_value': 1.3055703823764138e-50}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from scipy import stats\n",
+    "\n",
+    "# Load the CSV file\n",
+    "df = pd.read_csv(\"intake-person-demo(age).csv\", dtype={'fcid_code': str})\n",
+    "\n",
+    "def get_correlation(fcid_code):\n",
+    "    # Filter the dataframe for the given fcid_code\n",
+    "    filtered_df = df[df['fcid_code'] == fcid_code]\n",
+    "    \n",
+    "    # Check if there's data for the given fcid_code\n",
+    "    if filtered_df.empty:\n",
+    "        return {\"error\": \"No data found for the given fcid_code\"}\n",
+    "    \n",
+    "    # Calculate the correlation between age and intake_bw\n",
+    "    correlation, p_value = stats.pearsonr(filtered_df['age'], filtered_df['intake_bw'])\n",
+    "    \n",
+    "    return {\n",
+    "        \"fcid_code\": fcid_code,\n",
+    "        \"correlation\": correlation,\n",
+    "        \"p_value\": p_value\n",
+    "    }\n",
+    "\n",
+    "# Example usage\n",
+    "result = get_correlation(\"600349000\")\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To use this function, make sure you have the required libraries installed and the CSV file in the same directory as your notebook. You can install the libraries using:\n",
+    "\n",
+    "```\n",
+    "!pip install pandas scipy\n",
+    "```\n",
+    "\n",
+    "Then, you can call the function with different fcid_codes to get the correlation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Example usage with multiple fcid_codes\n",
+    "fcid_codes = [\"code1\", \"code2\", \"code3\"]\n",
+    "\n",
+    "for code in fcid_codes:\n",
+    "    result = get_correlation(code)\n",
+    "    print(f\"Result for {code}:\")\n",
+    "    print(result)\n",
+    "    print()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}