diff --git a/diagrams.ipynb b/diagrams.ipynb
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index 0000000000000000000000000000000000000000..58b2f4c9d18cdd74cadc6fb1ffeef0beb19be50d
--- /dev/null
+++ b/diagrams.ipynb
@@ -0,0 +1,1880 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "reduced-accreditation",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import re\n",
+    "from itertools import groupby, count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "involved-message",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load(filename, sep=\";\"):\n",
+    "    df = pd.read_csv(filename,sep=sep)\n",
+    "    df = df[df.MetricName == \"Time\" ]\n",
+    "    df.MetricValue = df.MetricValue.astype(float)\n",
+    "    df.ChangeSet = df.ChangeSet.astype(int)\n",
+    "    # convert from nanoseconds to seconds\n",
+    "    df.MetricValue = df.MetricValue / 1e9    \n",
+    "    return df\n",
+    "\n",
+    "def value_or_na(v):\n",
+    "    return np.nan if v.empty else v.MetricValue.values[0]\n",
+    "\n",
+    "def prepare_and_plot(ldf, phase=\"Update\", query='Q2'):\n",
+    "    ldf = ldf[ldf.View == query ]\n",
+    "    ldf = ldf[ldf.PhaseName == phase ]\n",
+    "    g = ldf.groupby([\"Tool\", \"View\", \"ChangeSet\", \"PhaseName\", \"MetricName\"]).mean()\n",
+    "    g.reset_index(inplace=True)\n",
+    "    display(g.head())\n",
+    "    tools = sorted(set(g.Tool))\n",
+    "#    display(tools)\n",
+    "    df2 = pd.DataFrame(columns=['ChangeSet'] + tools)\n",
+    "    for changeSet in sorted(set(g.ChangeSet)):\n",
+    "#        display(changeSet)\n",
+    "        toAppend = {'ChangeSet': str(changeSet), **{tool: value_or_na(g[(g.Tool==tool) & (g.ChangeSet==changeSet)]) for tool in tools}}\n",
+    "        df2 = df2.append(toAppend, ignore_index=True)\n",
+    "    display(df2)\n",
+    "    df2.plot(x='ChangeSet', logy=True, style='.-', grid=True, title=phase)\n",
+    "\n",
+    "PHASE_INITIAL = \"Initial\"\n",
+    "PHASE_UPDATE = \"Update\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "forty-reliance",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = load('results/output.csv',sep=';')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "dietary-cruise",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>RunIndex</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.017459</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.051881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>32</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.116222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>64</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.399595</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>128</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.456226</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   Tool View  ChangeSet PhaseName MetricName  RunIndex  \\\n",
+       "0  namelookup-xml-flush   Q2          8   Initial       Time         0   \n",
+       "1  namelookup-xml-flush   Q2         16   Initial       Time         0   \n",
+       "2  namelookup-xml-flush   Q2         32   Initial       Time         0   \n",
+       "3  namelookup-xml-flush   Q2         64   Initial       Time         0   \n",
+       "4  namelookup-xml-flush   Q2        128   Initial       Time         0   \n",
+       "\n",
+       "   Iteration  MetricValue  \n",
+       "0          0     0.017459  \n",
+       "1          0     0.051881  \n",
+       "2          0     0.116222  \n",
+       "3          0     0.399595  \n",
+       "4          0     2.456226  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>namelookup-xml-flush</th>\n",
+       "      <th>namelookup-xml-inc</th>\n",
+       "      <th>relast-reusable-flush</th>\n",
+       "      <th>relast-reusable-inc</th>\n",
+       "      <th>relast-xml-flush</th>\n",
+       "      <th>relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.017459</td>\n",
+       "      <td>0.034966</td>\n",
+       "      <td>0.016809</td>\n",
+       "      <td>0.040396</td>\n",
+       "      <td>0.014307</td>\n",
+       "      <td>0.025429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.051881</td>\n",
+       "      <td>0.089643</td>\n",
+       "      <td>0.025637</td>\n",
+       "      <td>0.050947</td>\n",
+       "      <td>0.031076</td>\n",
+       "      <td>0.046838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.116222</td>\n",
+       "      <td>0.215648</td>\n",
+       "      <td>0.042131</td>\n",
+       "      <td>0.117571</td>\n",
+       "      <td>0.102511</td>\n",
+       "      <td>0.143685</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.399595</td>\n",
+       "      <td>0.682137</td>\n",
+       "      <td>0.064535</td>\n",
+       "      <td>0.209905</td>\n",
+       "      <td>0.283938</td>\n",
+       "      <td>0.397969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>128</td>\n",
+       "      <td>2.456226</td>\n",
+       "      <td>4.353875</td>\n",
+       "      <td>0.114178</td>\n",
+       "      <td>0.427490</td>\n",
+       "      <td>1.825512</td>\n",
+       "      <td>2.526684</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  ChangeSet  namelookup-xml-flush  namelookup-xml-inc  relast-reusable-flush  \\\n",
+       "0         8              0.017459            0.034966               0.016809   \n",
+       "1        16              0.051881            0.089643               0.025637   \n",
+       "2        32              0.116222            0.215648               0.042131   \n",
+       "3        64              0.399595            0.682137               0.064535   \n",
+       "4       128              2.456226            4.353875               0.114178   \n",
+       "\n",
+       "   relast-reusable-inc  relast-xml-flush  relast-xml-inc  \n",
+       "0             0.040396          0.014307        0.025429  \n",
+       "1             0.050947          0.031076        0.046838  \n",
+       "2             0.117571          0.102511        0.143685  \n",
+       "3             0.209905          0.283938        0.397969  \n",
+       "4             0.427490          1.825512        2.526684  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(df, PHASE_INITIAL)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "manual-basement",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>RunIndex</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.004956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.014071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>32</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.050026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>64</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.238042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>namelookup-xml-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>128</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>2.203233</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   Tool View  ChangeSet PhaseName MetricName  RunIndex  \\\n",
+       "0  namelookup-xml-flush   Q2          8    Update       Time       0.0   \n",
+       "1  namelookup-xml-flush   Q2         16    Update       Time       0.0   \n",
+       "2  namelookup-xml-flush   Q2         32    Update       Time       0.0   \n",
+       "3  namelookup-xml-flush   Q2         64    Update       Time       0.0   \n",
+       "4  namelookup-xml-flush   Q2        128    Update       Time       0.0   \n",
+       "\n",
+       "   Iteration  MetricValue  \n",
+       "0       10.5     0.004956  \n",
+       "1       10.5     0.014071  \n",
+       "2       10.5     0.050026  \n",
+       "3       10.5     0.238042  \n",
+       "4       10.5     2.203233  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>namelookup-xml-flush</th>\n",
+       "      <th>namelookup-xml-inc</th>\n",
+       "      <th>relast-reusable-flush</th>\n",
+       "      <th>relast-reusable-inc</th>\n",
+       "      <th>relast-xml-flush</th>\n",
+       "      <th>relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.004956</td>\n",
+       "      <td>0.012070</td>\n",
+       "      <td>0.003319</td>\n",
+       "      <td>0.006073</td>\n",
+       "      <td>0.003382</td>\n",
+       "      <td>0.006423</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.014071</td>\n",
+       "      <td>0.022902</td>\n",
+       "      <td>0.006055</td>\n",
+       "      <td>0.010526</td>\n",
+       "      <td>0.009128</td>\n",
+       "      <td>0.012205</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.050026</td>\n",
+       "      <td>0.053385</td>\n",
+       "      <td>0.010640</td>\n",
+       "      <td>0.021106</td>\n",
+       "      <td>0.035256</td>\n",
+       "      <td>0.026071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.238042</td>\n",
+       "      <td>0.188963</td>\n",
+       "      <td>0.017379</td>\n",
+       "      <td>0.039525</td>\n",
+       "      <td>0.152674</td>\n",
+       "      <td>0.083124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>128</td>\n",
+       "      <td>2.203233</td>\n",
+       "      <td>0.607577</td>\n",
+       "      <td>0.038637</td>\n",
+       "      <td>0.078485</td>\n",
+       "      <td>1.629153</td>\n",
+       "      <td>0.316941</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  ChangeSet  namelookup-xml-flush  namelookup-xml-inc  relast-reusable-flush  \\\n",
+       "0         8              0.004956            0.012070               0.003319   \n",
+       "1        16              0.014071            0.022902               0.006055   \n",
+       "2        32              0.050026            0.053385               0.010640   \n",
+       "3        64              0.238042            0.188963               0.017379   \n",
+       "4       128              2.203233            0.607577               0.038637   \n",
+       "\n",
+       "   relast-reusable-inc  relast-xml-flush  relast-xml-inc  \n",
+       "0             0.006073          0.003382        0.006423  \n",
+       "1             0.010526          0.009128        0.012205  \n",
+       "2             0.021106          0.035256        0.026071  \n",
+       "3             0.039525          0.152674        0.083124  \n",
+       "4             0.078485          1.629153        0.316941  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(df, PHASE_UPDATE)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "rocky-devon",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ggdf = load('output-docker-2021-04-22T16.29.58-java11.csv',sep=';')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "experimental-uganda",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>RunIndex</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.015003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.017701</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.021071</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.025645</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.030807</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            Tool View  ChangeSet PhaseName MetricName  \\\n",
+       "0  jastadd-relast-reusable-flush   Q2          1   Initial       Time   \n",
+       "1  jastadd-relast-reusable-flush   Q2          2   Initial       Time   \n",
+       "2  jastadd-relast-reusable-flush   Q2          4   Initial       Time   \n",
+       "3  jastadd-relast-reusable-flush   Q2          8   Initial       Time   \n",
+       "4  jastadd-relast-reusable-flush   Q2         16   Initial       Time   \n",
+       "\n",
+       "   RunIndex  Iteration  MetricValue  \n",
+       "0         0          0     0.015003  \n",
+       "1         0          0     0.017701  \n",
+       "2         0          0     0.021071  \n",
+       "3         0          0     0.025645  \n",
+       "4         0          0     0.030807  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>jastadd-relast-reusable-flush</th>\n",
+       "      <th>jastadd-relast-reusable-inc</th>\n",
+       "      <th>jastadd-relast-xml-flush</th>\n",
+       "      <th>jastadd-relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0.015003</td>\n",
+       "      <td>0.019933</td>\n",
+       "      <td>0.015648</td>\n",
+       "      <td>0.014249</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0.017701</td>\n",
+       "      <td>0.025262</td>\n",
+       "      <td>0.018504</td>\n",
+       "      <td>0.018222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4</td>\n",
+       "      <td>0.021071</td>\n",
+       "      <td>0.031845</td>\n",
+       "      <td>0.025999</td>\n",
+       "      <td>0.023545</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.025645</td>\n",
+       "      <td>0.050149</td>\n",
+       "      <td>0.037249</td>\n",
+       "      <td>0.037166</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.030807</td>\n",
+       "      <td>0.079381</td>\n",
+       "      <td>0.065508</td>\n",
+       "      <td>0.061003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.048201</td>\n",
+       "      <td>0.140781</td>\n",
+       "      <td>0.174442</td>\n",
+       "      <td>0.158202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.086057</td>\n",
+       "      <td>0.247120</td>\n",
+       "      <td>0.448559</td>\n",
+       "      <td>0.415601</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>128</td>\n",
+       "      <td>0.165314</td>\n",
+       "      <td>0.444614</td>\n",
+       "      <td>3.527665</td>\n",
+       "      <td>3.318671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>256</td>\n",
+       "      <td>0.301716</td>\n",
+       "      <td>0.783245</td>\n",
+       "      <td>31.515041</td>\n",
+       "      <td>29.187061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>512</td>\n",
+       "      <td>0.528066</td>\n",
+       "      <td>1.581990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1024</td>\n",
+       "      <td>1.133841</td>\n",
+       "      <td>3.381065</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   ChangeSet  jastadd-relast-reusable-flush  jastadd-relast-reusable-inc  \\\n",
+       "0          1                       0.015003                     0.019933   \n",
+       "1          2                       0.017701                     0.025262   \n",
+       "2          4                       0.021071                     0.031845   \n",
+       "3          8                       0.025645                     0.050149   \n",
+       "4         16                       0.030807                     0.079381   \n",
+       "5         32                       0.048201                     0.140781   \n",
+       "6         64                       0.086057                     0.247120   \n",
+       "7        128                       0.165314                     0.444614   \n",
+       "8        256                       0.301716                     0.783245   \n",
+       "9        512                       0.528066                     1.581990   \n",
+       "10      1024                       1.133841                     3.381065   \n",
+       "\n",
+       "    jastadd-relast-xml-flush  jastadd-relast-xml-inc  \n",
+       "0                   0.015648                0.014249  \n",
+       "1                   0.018504                0.018222  \n",
+       "2                   0.025999                0.023545  \n",
+       "3                   0.037249                0.037166  \n",
+       "4                   0.065508                0.061003  \n",
+       "5                   0.174442                0.158202  \n",
+       "6                   0.448559                0.415601  \n",
+       "7                   3.527665                3.318671  \n",
+       "8                  31.515041               29.187061  \n",
+       "9                        NaN                     NaN  \n",
+       "10                       NaN                     NaN  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(ggdf, phase=PHASE_INITIAL)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "better-projector",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>RunIndex</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.001189</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.002261</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.003098</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.005166</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.008128</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            Tool View  ChangeSet PhaseName MetricName  \\\n",
+       "0  jastadd-relast-reusable-flush   Q2          1    Update       Time   \n",
+       "1  jastadd-relast-reusable-flush   Q2          2    Update       Time   \n",
+       "2  jastadd-relast-reusable-flush   Q2          4    Update       Time   \n",
+       "3  jastadd-relast-reusable-flush   Q2          8    Update       Time   \n",
+       "4  jastadd-relast-reusable-flush   Q2         16    Update       Time   \n",
+       "\n",
+       "   RunIndex  Iteration  MetricValue  \n",
+       "0       0.0       10.5     0.001189  \n",
+       "1       0.0       10.5     0.002261  \n",
+       "2       0.0       10.5     0.003098  \n",
+       "3       0.0       10.5     0.005166  \n",
+       "4       0.0       10.5     0.008128  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>jastadd-relast-reusable-flush</th>\n",
+       "      <th>jastadd-relast-reusable-inc</th>\n",
+       "      <th>jastadd-relast-xml-flush</th>\n",
+       "      <th>jastadd-relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0.001189</td>\n",
+       "      <td>0.001805</td>\n",
+       "      <td>0.001732</td>\n",
+       "      <td>0.001469</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0.002261</td>\n",
+       "      <td>0.003171</td>\n",
+       "      <td>0.003021</td>\n",
+       "      <td>0.002706</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4</td>\n",
+       "      <td>0.003098</td>\n",
+       "      <td>0.005977</td>\n",
+       "      <td>0.005393</td>\n",
+       "      <td>0.004810</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.005166</td>\n",
+       "      <td>0.009463</td>\n",
+       "      <td>0.010448</td>\n",
+       "      <td>0.009266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.008128</td>\n",
+       "      <td>0.016735</td>\n",
+       "      <td>0.019091</td>\n",
+       "      <td>0.017765</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.014843</td>\n",
+       "      <td>0.030060</td>\n",
+       "      <td>0.041859</td>\n",
+       "      <td>0.039395</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.032173</td>\n",
+       "      <td>0.055751</td>\n",
+       "      <td>0.118721</td>\n",
+       "      <td>0.111231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>128</td>\n",
+       "      <td>0.063316</td>\n",
+       "      <td>0.108934</td>\n",
+       "      <td>0.415689</td>\n",
+       "      <td>0.376500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>256</td>\n",
+       "      <td>0.148531</td>\n",
+       "      <td>0.217814</td>\n",
+       "      <td>5.551732</td>\n",
+       "      <td>5.419983</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>512</td>\n",
+       "      <td>0.379443</td>\n",
+       "      <td>0.484185</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1024</td>\n",
+       "      <td>1.081582</td>\n",
+       "      <td>0.672208</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   ChangeSet  jastadd-relast-reusable-flush  jastadd-relast-reusable-inc  \\\n",
+       "0          1                       0.001189                     0.001805   \n",
+       "1          2                       0.002261                     0.003171   \n",
+       "2          4                       0.003098                     0.005977   \n",
+       "3          8                       0.005166                     0.009463   \n",
+       "4         16                       0.008128                     0.016735   \n",
+       "5         32                       0.014843                     0.030060   \n",
+       "6         64                       0.032173                     0.055751   \n",
+       "7        128                       0.063316                     0.108934   \n",
+       "8        256                       0.148531                     0.217814   \n",
+       "9        512                       0.379443                     0.484185   \n",
+       "10      1024                       1.081582                     0.672208   \n",
+       "\n",
+       "    jastadd-relast-xml-flush  jastadd-relast-xml-inc  \n",
+       "0                   0.001732                0.001469  \n",
+       "1                   0.003021                0.002706  \n",
+       "2                   0.005393                0.004810  \n",
+       "3                   0.010448                0.009266  \n",
+       "4                   0.019091                0.017765  \n",
+       "5                   0.041859                0.039395  \n",
+       "6                   0.118721                0.111231  \n",
+       "7                   0.415689                0.376500  \n",
+       "8                   5.551732                5.419983  \n",
+       "9                        NaN                     NaN  \n",
+       "10                       NaN                     NaN  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(ggdf, phase=PHASE_UPDATE)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "english-groove",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>RunIndex</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.009767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.010879</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.012476</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q1</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.012990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>jastadd-relast-reusable-flush</td>\n",
+       "      <td>Q1</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.015991</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            Tool View  ChangeSet PhaseName MetricName  \\\n",
+       "0  jastadd-relast-reusable-flush   Q1          1   Initial       Time   \n",
+       "1  jastadd-relast-reusable-flush   Q1          2   Initial       Time   \n",
+       "2  jastadd-relast-reusable-flush   Q1          4   Initial       Time   \n",
+       "3  jastadd-relast-reusable-flush   Q1          8   Initial       Time   \n",
+       "4  jastadd-relast-reusable-flush   Q1         16   Initial       Time   \n",
+       "\n",
+       "   RunIndex  Iteration  MetricValue  \n",
+       "0         0          0     0.009767  \n",
+       "1         0          0     0.010879  \n",
+       "2         0          0     0.012476  \n",
+       "3         0          0     0.012990  \n",
+       "4         0          0     0.015991  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>jastadd-relast-reusable-flush</th>\n",
+       "      <th>jastadd-relast-reusable-inc</th>\n",
+       "      <th>jastadd-relast-xml-flush</th>\n",
+       "      <th>jastadd-relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0.009767</td>\n",
+       "      <td>0.014784</td>\n",
+       "      <td>0.013163</td>\n",
+       "      <td>0.013747</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0.010879</td>\n",
+       "      <td>0.017063</td>\n",
+       "      <td>0.015925</td>\n",
+       "      <td>0.015979</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4</td>\n",
+       "      <td>0.012476</td>\n",
+       "      <td>0.021022</td>\n",
+       "      <td>0.019902</td>\n",
+       "      <td>0.019872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.012990</td>\n",
+       "      <td>0.026704</td>\n",
+       "      <td>0.024901</td>\n",
+       "      <td>0.025397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.015991</td>\n",
+       "      <td>0.037474</td>\n",
+       "      <td>0.037270</td>\n",
+       "      <td>0.037604</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.019786</td>\n",
+       "      <td>0.065975</td>\n",
+       "      <td>0.068592</td>\n",
+       "      <td>0.065704</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.027380</td>\n",
+       "      <td>0.120008</td>\n",
+       "      <td>0.122040</td>\n",
+       "      <td>0.113032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>128</td>\n",
+       "      <td>0.044298</td>\n",
+       "      <td>0.206033</td>\n",
+       "      <td>0.217752</td>\n",
+       "      <td>0.206561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>256</td>\n",
+       "      <td>0.080795</td>\n",
+       "      <td>0.360224</td>\n",
+       "      <td>0.366728</td>\n",
+       "      <td>0.348644</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>512</td>\n",
+       "      <td>0.126134</td>\n",
+       "      <td>0.675223</td>\n",
+       "      <td>0.668883</td>\n",
+       "      <td>0.651784</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1024</td>\n",
+       "      <td>0.204023</td>\n",
+       "      <td>1.257982</td>\n",
+       "      <td>1.244882</td>\n",
+       "      <td>1.200255</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   ChangeSet  jastadd-relast-reusable-flush  jastadd-relast-reusable-inc  \\\n",
+       "0          1                       0.009767                     0.014784   \n",
+       "1          2                       0.010879                     0.017063   \n",
+       "2          4                       0.012476                     0.021022   \n",
+       "3          8                       0.012990                     0.026704   \n",
+       "4         16                       0.015991                     0.037474   \n",
+       "5         32                       0.019786                     0.065975   \n",
+       "6         64                       0.027380                     0.120008   \n",
+       "7        128                       0.044298                     0.206033   \n",
+       "8        256                       0.080795                     0.360224   \n",
+       "9        512                       0.126134                     0.675223   \n",
+       "10      1024                       0.204023                     1.257982   \n",
+       "\n",
+       "    jastadd-relast-xml-flush  jastadd-relast-xml-inc  \n",
+       "0                   0.013163                0.013747  \n",
+       "1                   0.015925                0.015979  \n",
+       "2                   0.019902                0.019872  \n",
+       "3                   0.024901                0.025397  \n",
+       "4                   0.037270                0.037604  \n",
+       "5                   0.068592                0.065704  \n",
+       "6                   0.122040                0.113032  \n",
+       "7                   0.217752                0.206561  \n",
+       "8                   0.366728                0.348644  \n",
+       "9                   0.668883                0.651784  \n",
+       "10                  1.244882                1.200255  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(ggdf, phase=PHASE_INITIAL, query=\"Q1\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "australian-description",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "newdf = load('results/merged-2021-04-23_12-40-35.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "overall-catalyst",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.017487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.029385</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>32</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.046105</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>64</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.073027</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>128</td>\n",
+       "      <td>Initial</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.118512</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    Tool View  ChangeSet PhaseName MetricName  Iteration  \\\n",
+       "0  relast-reusable-flush   Q2          8   Initial       Time          0   \n",
+       "1  relast-reusable-flush   Q2         16   Initial       Time          0   \n",
+       "2  relast-reusable-flush   Q2         32   Initial       Time          0   \n",
+       "3  relast-reusable-flush   Q2         64   Initial       Time          0   \n",
+       "4  relast-reusable-flush   Q2        128   Initial       Time          0   \n",
+       "\n",
+       "   MetricValue  \n",
+       "0     0.017487  \n",
+       "1     0.029385  \n",
+       "2     0.046105  \n",
+       "3     0.073027  \n",
+       "4     0.118512  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>relast-reusable-flush</th>\n",
+       "      <th>relast-reusable-inc</th>\n",
+       "      <th>relast-xml-flush</th>\n",
+       "      <th>relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.017487</td>\n",
+       "      <td>0.038890</td>\n",
+       "      <td>0.016371</td>\n",
+       "      <td>0.025484</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.029385</td>\n",
+       "      <td>0.057344</td>\n",
+       "      <td>0.031096</td>\n",
+       "      <td>0.044917</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.046105</td>\n",
+       "      <td>0.127792</td>\n",
+       "      <td>0.094724</td>\n",
+       "      <td>0.147872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.073027</td>\n",
+       "      <td>0.236716</td>\n",
+       "      <td>0.274071</td>\n",
+       "      <td>0.380728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>128</td>\n",
+       "      <td>0.118512</td>\n",
+       "      <td>0.431099</td>\n",
+       "      <td>1.573482</td>\n",
+       "      <td>2.494142</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  ChangeSet  relast-reusable-flush  relast-reusable-inc  relast-xml-flush  \\\n",
+       "0         8               0.017487             0.038890          0.016371   \n",
+       "1        16               0.029385             0.057344          0.031096   \n",
+       "2        32               0.046105             0.127792          0.094724   \n",
+       "3        64               0.073027             0.236716          0.274071   \n",
+       "4       128               0.118512             0.431099          1.573482   \n",
+       "\n",
+       "   relast-xml-inc  \n",
+       "0        0.025484  \n",
+       "1        0.044917  \n",
+       "2        0.147872  \n",
+       "3        0.380728  \n",
+       "4        2.494142  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(newdf, phase=PHASE_INITIAL)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "primary-finance",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Tool</th>\n",
+       "      <th>View</th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>PhaseName</th>\n",
+       "      <th>MetricName</th>\n",
+       "      <th>Iteration</th>\n",
+       "      <th>MetricValue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.003376</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.006238</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>32</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.016220</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>64</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.017028</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>relast-reusable-flush</td>\n",
+       "      <td>Q2</td>\n",
+       "      <td>128</td>\n",
+       "      <td>Update</td>\n",
+       "      <td>Time</td>\n",
+       "      <td>10.5</td>\n",
+       "      <td>0.035924</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    Tool View  ChangeSet PhaseName MetricName  Iteration  \\\n",
+       "0  relast-reusable-flush   Q2          8    Update       Time       10.5   \n",
+       "1  relast-reusable-flush   Q2         16    Update       Time       10.5   \n",
+       "2  relast-reusable-flush   Q2         32    Update       Time       10.5   \n",
+       "3  relast-reusable-flush   Q2         64    Update       Time       10.5   \n",
+       "4  relast-reusable-flush   Q2        128    Update       Time       10.5   \n",
+       "\n",
+       "   MetricValue  \n",
+       "0     0.003376  \n",
+       "1     0.006238  \n",
+       "2     0.016220  \n",
+       "3     0.017028  \n",
+       "4     0.035924  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ChangeSet</th>\n",
+       "      <th>relast-reusable-flush</th>\n",
+       "      <th>relast-reusable-inc</th>\n",
+       "      <th>relast-xml-flush</th>\n",
+       "      <th>relast-xml-inc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.003376</td>\n",
+       "      <td>0.005956</td>\n",
+       "      <td>0.003368</td>\n",
+       "      <td>0.006453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>0.006238</td>\n",
+       "      <td>0.010285</td>\n",
+       "      <td>0.010808</td>\n",
+       "      <td>0.014899</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>32</td>\n",
+       "      <td>0.016220</td>\n",
+       "      <td>0.021703</td>\n",
+       "      <td>0.035156</td>\n",
+       "      <td>0.027184</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>64</td>\n",
+       "      <td>0.017028</td>\n",
+       "      <td>0.039328</td>\n",
+       "      <td>0.152410</td>\n",
+       "      <td>0.092637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>128</td>\n",
+       "      <td>0.035924</td>\n",
+       "      <td>0.080913</td>\n",
+       "      <td>1.504092</td>\n",
+       "      <td>0.308104</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  ChangeSet  relast-reusable-flush  relast-reusable-inc  relast-xml-flush  \\\n",
+       "0         8               0.003376             0.005956          0.003368   \n",
+       "1        16               0.006238             0.010285          0.010808   \n",
+       "2        32               0.016220             0.021703          0.035156   \n",
+       "3        64               0.017028             0.039328          0.152410   \n",
+       "4       128               0.035924             0.080913          1.504092   \n",
+       "\n",
+       "   relast-xml-inc  \n",
+       "0        0.006453  \n",
+       "1        0.014899  \n",
+       "2        0.027184  \n",
+       "3        0.092637  \n",
+       "4        0.308104  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prepare_and_plot(newdf, phase=PHASE_UPDATE)"
+   ]
+  }
+ ],
+ "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": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}