SubjectDemographics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "76b8274d-018e-48c5-9fe3-6ebdb5c3f3b5",
   "metadata": {},
   "source": [
    "# Subject Demographics Exploration\n",
    "\n",
    "This Jupyter Notebook explores the demographics of subjects in a project, focusing on their gender distribution and age ranges. The notebook retrieves the gender and age information for each subject with [XNATpy](https://xnat.readthedocs.io/en/latest/) and presents the findings through a histogram and a pie chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "205d3fd7-b89e-47ae-afeb-b5c5fd4b49eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import xnat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6d2bda5a-1390-4ba0-bb81-4dac1c4d8ea5",
   "metadata": {},
   "outputs": [],
   "source": [
    "if os.environ['XNAT_XSI_TYPE'] != 'xnat:projectData':\n",
    "    raise Exception('Manually enter your project id')\n",
    "\n",
    "project_id = os.environ['XNAT_ITEM_ID']\n",
    "\n",
    "connection = xnat.connect()\n",
    "project = connection.projects[project_id]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0a66d59-4086-4f2f-b7f7-e59ea29dd455",
   "metadata": {},
   "outputs": [],
   "source": [
    "subject_data = {\n",
    "    'id': [],\n",
    "    'gender': [],\n",
    "    'age': []\n",
    "}\n",
    "\n",
    "for subject in project.subjects.values():\n",
    "    subject_data['id'].append(subject.label)\n",
    "    subject_data['gender'].append(subject.demographics.gender)\n",
    "    subject_data['age'].append(subject.demographics.age)\n",
    "    \n",
    "df = pd.DataFrame(subject_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fcc4e29c-cd86-4560-acea-0614e0398367",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ages = df['age']\n",
    "\n",
    "# Create the histogram\n",
    "plt.hist(ages, bins=10, edgecolor='black')\n",
    "\n",
    "# Set the labels and title\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Age Distribution')\n",
    "\n",
    "# Display the histogram\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "627429bc-c388-43ab-b7d5-0a61216f1a7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "genders = df['gender'].value_counts()\n",
    "\n",
    "# Create the pie chart\n",
    "plt.pie(genders, labels=genders.index, autopct='%1.1f%%')\n",
    "\n",
    "# Set the title\n",
    "plt.title('Gender Distribution')\n",
    "\n",
    "# Display the pie chart\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}