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diff --git a/megapixels/notebooks/datasets/visualizations/age_gender.ipynb b/megapixels/notebooks/datasets/visualizations/age_gender.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Age Gender to CSV for Site"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%reload_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "import os\n",
+    "from os.path import join\n",
+    "import math\n",
+    "import time\n",
+    "from glob import glob\n",
+    "import datetime\n",
+    "from collections import OrderedDict\n",
+    "from operator import itemgetter\n",
+    "from datetime import datetime\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from pathlib import Path\n",
+    "from tqdm import tqdm_notebook as tqdm\n",
+    "import imutils\n",
+    "import random\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import random\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('/work/megapixels_dev/megapixels')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dk = 'helen'\n",
+    "fp_in = '/data_store_hdd/datasets/people/helen/metadata/face_attributes.csv'\n",
+    "fp_out_age = f'/work/megapixels_dev/site/content/pages/datasets/{dk}/assets/age.csv'\n",
+    "fp_out_gender = f'/work/megapixels_dev/site/content/pages/datasets/{dk}/assets/gender.csv'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(fp_in)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Age\n",
+    "results = []\n",
+    "brackets = [(0, 12), (13, 18), (19,24), (25, 34), (35, 44), (45, 54), (55, 64), (64, 75), (75, 100)]\n",
+    "df_age = df['age_real']\n",
+    "\n",
+    "for a1, a2 in brackets:\n",
+    "  n = len(df_age.loc[((df_age >= a1) & (df_age <= a2))])\n",
+    "  results.append({'age': f'{a1} - {a2}', 'faces': n})\n",
+    "  \n",
+    "df_out = pd.DataFrame.from_dict(results)\n",
+    "df_out = df_out[['age','faces']]\n",
+    "df_out.to_csv(fp_out_age, index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Gender\n",
+    "results = []\n",
+    "\n",
+    "df_f = df['f']\n",
+    "nm = len(df_f.loc[((df_f < 0.33))])\n",
+    "nnb = len(df_f.loc[((df_f >= 0.33) & (df_f <= 0.66))])\n",
+    "nf = len(df_f.loc[((df_f > 0.66))])\n",
+    "\n",
+    "results = []\n",
+    "results.append({'gender': 'male', 'faces':nm})\n",
+    "results.append({'gender': 'female', 'faces': nf})\n",
+    "results.append({'gender': 'they', 'faces': nnb})\n",
+    "\n",
+    "df_out = pd.DataFrame.from_dict(results)\n",
+    "df_out = df_out[['gender','faces']]\n",
+    "df_out.to_csv(fp_out_gender, index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "megapixels",
+   "language": "python",
+   "name": "megapixels"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}