diff --git a/scripts/ai-heatmap.ipynb b/scripts/ai-heatmap.ipynb
index 589a6bb..9553adb 100644
--- a/scripts/ai-heatmap.ipynb
+++ b/scripts/ai-heatmap.ipynb
@@ -14,19 +14,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "id": "bef16296",
    "metadata": {},
    "outputs": [],
    "source": [
-    "convo_folder = '/Users/chip/dev/chatgpt-data/chatgpt-2025-01-13' # change to where your exported ChatGPT folder is \n",
+    "convo_folder = 'export_chatgpt' # change to where your exported ChatGPT folder is \n",
     "local_tz = 'US/Pacific' # change to your local timezone.\n",
     "# pytz.all_timezones # uncomment to see a list of all supported timezones."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 8,
    "id": "f7447d09",
    "metadata": {},
    "outputs": [],
@@ -34,12 +34,12 @@
     "import json\n",
     "\n",
     "with open(f'{convo_folder}/conversations.json', 'r') as f:\n",
-    "    convs = json.load(f)"
+    "    oai_convs = json.load(f)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 16,
    "id": "b30fff71",
    "metadata": {},
    "outputs": [],
@@ -48,8 +48,8 @@
     "\n",
     "from datetime import datetime, timezone, timedelta\n",
     "\n",
-    "convo_times = []\n",
-    "for conv in convs:\n",
+    "oai_convo_times = []\n",
+    "for conv in oai_convs:\n",
     "    # Given Unix timestamp\n",
     "    unix_timestamp = conv['create_time']\n",
     "\n",
@@ -58,12 +58,12 @@
     "\n",
     "    # Convert UTC datetime to local timezone\n",
     "    pt_datetime = utc_datetime.astimezone(pytz.timezone(local_tz))\n",
-    "    convo_times.append(pt_datetime)"
+    "    oai_convo_times.append(pt_datetime)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 17,
    "id": "0c121446",
    "metadata": {},
    "outputs": [],
@@ -149,7 +149,7 @@
     }
    ],
    "source": [
-    "create_year_heatmap(convo_times, 2025)"
+    "create_year_heatmap(oai_convo_times, 2025)"
    ]
   },
   {
@@ -170,21 +170,235 @@
     }
    ],
    "source": [
-    "create_year_heatmap(convo_times, 2024)"
+    "create_year_heatmap(oai_convo_times, 2024)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c5de1c0",
+   "metadata": {},
+   "source": [
+    "### Adding Claude \n",
+    "\n",
+    "You can optionally add your Claude data as well, through the following step:\n",
+    "\n",
+    "1. Export your Claude conversations.\n",
+    "    - From your Claude account, go to Settings -> Account -> Data -> Export data\n",
+    "2. Unzip the downloaded data\n",
+    "3. Point `claude_convs` to your exported directory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "024dfc4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "claude_convo_folder = \"export_claude\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "024dfc4c",
+   "id": "e6a2fa6a",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "with open(f'{claude_convo_folder}/conversations.json', 'r') as f:\n",
+    "    claude_convs = json.load(f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "bbdd30bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_claude_timestamps(convs, local_tz, claude=True):\n",
+    "    convo_times = []\n",
+    "    for conv in convs:\n",
+    "        # Parse ISO format string to datetime\n",
+    "        utc_datetime = datetime.strptime(conv['created_at'], \"%Y-%m-%dT%H:%M:%S.%fZ\")\n",
+    "\n",
+    "        # Add UTC timezone info\n",
+    "        utc_datetime = utc_datetime.replace(tzinfo=timezone.utc)\n",
+    "\n",
+    "        # Convert UTC to local timezone\n",
+    "        local_datetime = utc_datetime.astimezone(pytz.timezone(local_tz))\n",
+    "        convo_times.append(local_datetime)\n",
+    "\n",
+    "    return convo_times"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "b117b6dd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "claude_convo_times = convert_claude_timestamps(claude_convs, local_tz)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "1a57909e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_comparison_heatmap(claude_times, openai_times, year):\n",
+    "    # Convert times to dates and filter for the given year\n",
+    "    claude_dates = [convo.date() for convo in claude_times if convo.year == year]\n",
+    "    openai_dates = [convo.date() for convo in openai_times if convo.year == year]\n",
+    "\n",
+    "    claude_counts = Counter(claude_dates)\n",
+    "    openai_counts = Counter(openai_dates)\n",
+    "\n",
+    "    # Calculate totals\n",
+    "    claude_total = sum(claude_counts.values())\n",
+    "    openai_total = sum(openai_counts.values())\n",
+    "    combined_total = claude_total + openai_total\n",
+    "\n",
+    "    # Create a full year date range\n",
+    "    start_date = datetime(year, 1, 1).date()\n",
+    "    end_date = datetime(year, 12, 31).date()\n",
+    "    total_days = (end_date - start_date).days + 1\n",
+    "    date_range = [start_date + timedelta(days=i) for i in range(total_days)]\n",
+    "\n",
+    "    # Prepare data for plotting - Reverse the day_of_week calculation\n",
+    "    data = []\n",
+    "    for date in date_range:\n",
+    "        week = ((date - start_date).days + start_date.weekday()) // 7\n",
+    "        # Reverse the order: 0 (Mon) -> 6, 1 (Tue) -> 5, etc.\n",
+    "        day_of_week = 6 - date.weekday()  # This reverses the order\n",
+    "        claude_count = claude_counts.get(date, 0)\n",
+    "        openai_count = openai_counts.get(date, 0)\n",
+    "        dominant_llm = 'claude' if claude_count > openai_count else 'openai' if openai_count > claude_count else 'tie'\n",
+    "        count = max(claude_count, openai_count)\n",
+    "        data.append((week, day_of_week, count, dominant_llm))\n",
+    "\n",
+    "    weeks_in_year = (end_date - start_date).days // 7 + 2\n",
+    "\n",
+    "    # Calculate overall p90 for color scaling\n",
+    "    all_counts = list(claude_counts.values()) + list(openai_counts.values())\n",
+    "    p90_count = np.percentile(all_counts, 90) if all_counts else 1\n",
+    "\n",
+    "    # Plot setup\n",
+    "    plt.figure(figsize=(20, 8))\n",
+    "    ax = plt.gca()\n",
+    "    ax.set_aspect('equal')\n",
+    "\n",
+    "    # Plot rectangles\n",
+    "    for week, day_of_week, count, dominant_llm in data:\n",
+    "        if count > 0:\n",
+    "            # Start at 0.1 (10%) intensity and scale up to 1\n",
+    "            intensity = min(0.1 + (count / p90_count * 0.9), 1)\n",
+    "            color = plt.cm.Oranges(intensity) if dominant_llm == 'claude' else \\\n",
+    "                   plt.cm.Greens(intensity) if dominant_llm == 'openai' else \\\n",
+    "                   'lightgray'\n",
+    "        else:\n",
+    "            color = '#F5F5F5'  # Light gray for empty cells\n",
+    "\n",
+    "        rect = patches.Rectangle(\n",
+    "            (week, day_of_week), 1, 1,\n",
+    "            linewidth=1,\n",
+    "            edgecolor='black',\n",
+    "            facecolor=color\n",
+    "        )\n",
+    "        ax.add_patch(rect)\n",
+    "\n",
+    "    # Add month labels\n",
+    "    month_starts = [start_date + timedelta(days=i) for i in range(total_days)\n",
+    "                   if (start_date + timedelta(days=i)).day == 1]\n",
+    "    for month_start in month_starts:\n",
+    "        week = (month_start - start_date).days // 7\n",
+    "        plt.text(week + 0.5, -0.5, month_start.strftime('%b'),\n",
+    "                ha='center', va='top', fontsize=10)\n",
+    "\n",
+    "    # Find most active days\n",
+    "    claude_max_date = max(claude_counts.items(), key=lambda x: x[1]) if claude_counts else (None, 0)\n",
+    "    openai_max_date = max(openai_counts.items(), key=lambda x: x[1]) if openai_counts else (None, 0)\n",
+    "\n",
+    "    # Title and formatting\n",
+    "    plt.title(\n",
+    "        f'{year} AI Conversation Comparison (Total: {combined_total:,} conversations)\\n'\n",
+    "        f'Claude total: {claude_total:,}, max: {claude_max_date[1]} on {claude_max_date[0]}\\n'\n",
+    "        f'OpenAI total: {openai_total:,}, max: {openai_max_date[1]} on {openai_max_date[0]}',\n",
+    "        fontsize=12, pad=15\n",
+    "    )\n",
+    "\n",
+    "    # Adjust axis limits and labels\n",
+    "    plt.xlim(-0.5, weeks_in_year + 0.5)\n",
+    "    plt.ylim(-1, 7)\n",
+    "    plt.xticks([])\n",
+    "\n",
+    "    # Set y-ticks at the center of each box (offset by 0.5)\n",
+    "    plt.yticks([i + 0.5 for i in range(7)], ['Sun', 'Sat', 'Fri', 'Thu', 'Wed', 'Tue', 'Mon'])\n",
+    "\n",
+    "    # Adjust y-axis label positioning\n",
+    "    ax.yaxis.set_tick_params(pad=10)\n",
+    "\n",
+    "    # Add legend\n",
+    "    legend_elements = [\n",
+    "        patches.Patch(facecolor=plt.cm.Oranges(0.7), label='Claude Dominant'),\n",
+    "        patches.Patch(facecolor=plt.cm.Greens(0.7), label='OpenAI Dominant'),\n",
+    "        patches.Patch(facecolor='lightgray', label='Tie')\n",
+    "    ]\n",
+    "    plt.legend(handles=legend_elements, loc='center left', bbox_to_anchor=(1.02, 0.5))\n",
+    "\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "92ab25e6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_comparison_heatmap(claude_convo_times, oai_convo_times, 2025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "1bb44afc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 2000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "create_comparison_heatmap(claude_convo_times, oai_convo_times, 2024)"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -198,7 +412,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.11"
   }
  },
  "nbformat": 4,