From afb5f6242bfb24e4744ef0d331ccf0cf77eae5a7 Mon Sep 17 00:00:00 2001
From: Vinzenz Schroeter <vinzenz.f.s@gmail.com>
Date: Tue, 26 Aug 2025 17:11:39 +0200
Subject: [PATCH] wip

---
 flake.nix      |   5 +
 notebook.ipynb | 705 ++++++++++++++++++++++++++++++++++++++-----------
 2 files changed, 555 insertions(+), 155 deletions(-)

diff --git a/flake.nix b/flake.nix
index 9387a4d..5d9ea1e 100644
--- a/flake.nix
+++ b/flake.nix
@@ -37,6 +37,11 @@
                     pandas
                     pip
                     notebook
+                    jupyterlab-lsp
+                    jupyterlab-git
+                    python-lsp-server
+                    python-lsp-ruff
+                    python-lsp-ruff
                   ];
                 pythonEnv = pkgs.python3.withPackages pythonPackages;
               in
diff --git a/notebook.ipynb b/notebook.ipynb
index c44a15a..1bf7b81 100644
--- a/notebook.ipynb
+++ b/notebook.ipynb
@@ -8,65 +8,50 @@
      "languageId": "plaintext"
     },
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:06.528706Z",
-     "start_time": "2025-08-19T21:11:06.090989Z"
+     "end_time": "2025-08-19T23:39:53.836251Z",
+     "start_time": "2025-08-19T23:39:53.832994Z"
     }
    },
    "source": [
+    "from datetime import datetime\n",
+    "\n",
     "import pandas\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "from dataclasses import dataclass\n",
-    "from math import floor"
+    "import matplotlib.pyplot as plt"
    ],
    "outputs": [],
-   "execution_count": 1
+   "execution_count": 25
   },
   {
    "cell_type": "code",
    "id": "388b7c16-61c3-4ddc-ac85-bf2094cbfda0",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:06.595407Z",
-     "start_time": "2025-08-19T21:11:06.563450Z"
+     "end_time": "2025-08-19T23:40:17.840982Z",
+     "start_time": "2025-08-19T23:40:17.825194Z"
     }
    },
    "source": [
-    "scorelog = pandas.read_csv('PolyGenStats-vinzenz-scorelog.csv', sep=',', dtype={'score': int, 'sourcename': str, 'name': str, 'mapx': int, 'mapy': int}, parse_dates=['when'])\n",
-    "scorelog['mapcoord'] = list(zip(scorelog['mapx'], scorelog['mapy']))\n",
+    "scorelog = pandas.read_csv('PolyGenStats-vinzenz-scorelog.csv', sep=',', dtype={'score': int, 'sourcename': str, 'name': str, 'mapx': int, 'mapy': int}, parse_dates=['when'], date_format='%d/%m/%Y %H:%M')\n",
     "scorelog"
    ],
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "                   when  score    sourcename                  name  mapx  \\\n",
-       "0   2025-08-08 20:14:00    100   First Visit             Info Desk   216   \n",
-       "1   2025-08-08 20:19:00    282       Capture             Info Desk   216   \n",
-       "2   2025-08-08 20:20:00     58       Capture             Info Desk   216   \n",
-       "3   2025-08-08 20:22:00    100   First Visit              Main Bar   190   \n",
-       "4   2025-08-08 20:23:00    100   First Visit            Badge Tent   328   \n",
-       "..                  ...    ...           ...                   ...   ...   \n",
-       "896 2025-12-08 13:34:00     91       Capture                    0E     0   \n",
-       "897 2025-12-08 13:39:00     50         Visit              Pixelbar   379   \n",
-       "898 2025-12-08 13:42:00    164  Output Boost             Site Sign   207   \n",
-       "899 2025-12-08 13:50:00    694       Capture              Pixelbar   379   \n",
-       "900 2025-12-08 14:00:00    284  Output Boost  Maker Days Eindhoven   115   \n",
+       "                   when  score    sourcename                  name  mapx  mapy\n",
+       "0   2025-08-08 20:14:00    100   First Visit             Info Desk   216   505\n",
+       "1   2025-08-08 20:19:00    282       Capture             Info Desk   216   505\n",
+       "2   2025-08-08 20:20:00     58       Capture             Info Desk   216   505\n",
+       "3   2025-08-08 20:22:00    100   First Visit              Main Bar   190   570\n",
+       "4   2025-08-08 20:23:00    100   First Visit            Badge Tent   328   607\n",
+       "..                  ...    ...           ...                   ...   ...   ...\n",
+       "896 2025-08-12 13:34:00     91       Capture                    0E     0     0\n",
+       "897 2025-08-12 13:39:00     50         Visit              Pixelbar   379   602\n",
+       "898 2025-08-12 13:42:00    164  Output Boost             Site Sign   207   874\n",
+       "899 2025-08-12 13:50:00    694       Capture              Pixelbar   379   602\n",
+       "900 2025-08-12 14:00:00    284  Output Boost  Maker Days Eindhoven   115   749\n",
        "\n",
-       "     mapy    mapcoord  \n",
-       "0     505  (216, 505)  \n",
-       "1     505  (216, 505)  \n",
-       "2     505  (216, 505)  \n",
-       "3     570  (190, 570)  \n",
-       "4     607  (328, 607)  \n",
-       "..    ...         ...  \n",
-       "896     0      (0, 0)  \n",
-       "897   602  (379, 602)  \n",
-       "898   874  (207, 874)  \n",
-       "899   602  (379, 602)  \n",
-       "900   749  (115, 749)  \n",
-       "\n",
-       "[901 rows x 7 columns]"
+       "[901 rows x 6 columns]"
       ],
       "text/html": [
        "<div>\n",
@@ -93,7 +78,6 @@
        "      <th>name</th>\n",
        "      <th>mapx</th>\n",
        "      <th>mapy</th>\n",
-       "      <th>mapcoord</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -105,7 +89,6 @@
        "      <td>Info Desk</td>\n",
        "      <td>216</td>\n",
        "      <td>505</td>\n",
-       "      <td>(216, 505)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -115,7 +98,6 @@
        "      <td>Info Desk</td>\n",
        "      <td>216</td>\n",
        "      <td>505</td>\n",
-       "      <td>(216, 505)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -125,7 +107,6 @@
        "      <td>Info Desk</td>\n",
        "      <td>216</td>\n",
        "      <td>505</td>\n",
-       "      <td>(216, 505)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -135,7 +116,6 @@
        "      <td>Main Bar</td>\n",
        "      <td>190</td>\n",
        "      <td>570</td>\n",
-       "      <td>(190, 570)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -145,7 +125,6 @@
        "      <td>Badge Tent</td>\n",
        "      <td>328</td>\n",
        "      <td>607</td>\n",
-       "      <td>(328, 607)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -155,78 +134,72 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
-       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>896</th>\n",
-       "      <td>2025-12-08 13:34:00</td>\n",
+       "      <td>2025-08-12 13:34:00</td>\n",
        "      <td>91</td>\n",
        "      <td>Capture</td>\n",
        "      <td>0E</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>(0, 0)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>897</th>\n",
-       "      <td>2025-12-08 13:39:00</td>\n",
+       "      <td>2025-08-12 13:39:00</td>\n",
        "      <td>50</td>\n",
        "      <td>Visit</td>\n",
        "      <td>Pixelbar</td>\n",
        "      <td>379</td>\n",
        "      <td>602</td>\n",
-       "      <td>(379, 602)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>898</th>\n",
-       "      <td>2025-12-08 13:42:00</td>\n",
+       "      <td>2025-08-12 13:42:00</td>\n",
        "      <td>164</td>\n",
        "      <td>Output Boost</td>\n",
        "      <td>Site Sign</td>\n",
        "      <td>207</td>\n",
        "      <td>874</td>\n",
-       "      <td>(207, 874)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>899</th>\n",
-       "      <td>2025-12-08 13:50:00</td>\n",
+       "      <td>2025-08-12 13:50:00</td>\n",
        "      <td>694</td>\n",
        "      <td>Capture</td>\n",
        "      <td>Pixelbar</td>\n",
        "      <td>379</td>\n",
        "      <td>602</td>\n",
-       "      <td>(379, 602)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>900</th>\n",
-       "      <td>2025-12-08 14:00:00</td>\n",
+       "      <td>2025-08-12 14:00:00</td>\n",
        "      <td>284</td>\n",
        "      <td>Output Boost</td>\n",
        "      <td>Maker Days Eindhoven</td>\n",
        "      <td>115</td>\n",
        "      <td>749</td>\n",
-       "      <td>(115, 749)</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>901 rows × 7 columns</p>\n",
+       "<p>901 rows × 6 columns</p>\n",
        "</div>"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 2
+   "execution_count": 36
   },
   {
    "cell_type": "code",
    "id": "e8888706-1439-4b73-97cc-06dd416d9e23",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:06.706214Z",
-     "start_time": "2025-08-19T21:11:06.692755Z"
+     "end_time": "2025-08-19T23:39:54.083367Z",
+     "start_time": "2025-08-19T23:39:54.071862Z"
     }
    },
    "source": [
@@ -523,26 +496,26 @@
        "</div>"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 3
+   "execution_count": 27
   },
   {
    "cell_type": "code",
    "id": "3c3ca9ba-b545-4f10-a34d-4c35323363fc",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:07.091537Z",
-     "start_time": "2025-08-19T21:11:07.071338Z"
+     "end_time": "2025-08-19T23:39:54.465235Z",
+     "start_time": "2025-08-19T23:39:54.440411Z"
     }
    },
    "source": [
     "summary = pandas.merge(summary, scorelog[scorelog['sourcename'] == 'First Visit'][['name', 'mapx', 'mapy', 'when']], on='name')\n",
     "summary = pandas.merge(summary, scorelog[['name', 'score']].groupby('name').sum(), on='name', validate='1:1')\n",
-    "summary.rename(columns={'when': 'first_visit'}, inplace=True)\n",
+    "summary.rename(columns={'when': 'first_visit', 'score': 'total_score'}, inplace=True)\n",
     "\n",
     "summary"
    ],
@@ -580,29 +553,29 @@
        "    maxheldduration  mapx  mapy         first_visit  score  \n",
        "0             46380   207   874 2025-08-08 22:12:00  63688  \n",
        "1             44313   115   749 2025-08-08 22:28:00  62440  \n",
-       "2             36261   379   602 2025-09-08 00:42:00  52601  \n",
+       "2             36261   379   602 2025-08-09 00:42:00  52601  \n",
        "3             22971   305   402 2025-08-08 21:56:00  50757  \n",
        "4             23180   292   446 2025-08-08 21:55:00  45272  \n",
        "5             23237    34   523 2025-08-08 21:39:00  44374  \n",
        "6             28498   240   916 2025-08-08 22:10:00  41486  \n",
        "7             16913   190   570 2025-08-08 20:22:00  36884  \n",
        "8             18329   328   607 2025-08-08 20:23:00  32599  \n",
-       "9             18829   251   553 2025-09-08 02:28:00  29550  \n",
-       "10             7753    82   337 2025-10-08 19:51:00  17711  \n",
+       "9             18829   251   553 2025-08-09 02:28:00  29550  \n",
+       "10             7753    82   337 2025-08-10 19:51:00  17711  \n",
        "11             3304   216   505 2025-08-08 20:14:00  17026  \n",
-       "12             5316   322   591 2025-09-08 17:52:00  14376  \n",
-       "13             3386    95   498 2025-09-08 17:07:00  11003  \n",
+       "12             5316   322   591 2025-08-09 17:52:00  14376  \n",
+       "13             3386    95   498 2025-08-09 17:07:00  11003  \n",
        "14             7694    67   289 2025-08-08 22:54:00  13340  \n",
        "15             3756   183   227 2025-08-08 21:46:00  10057  \n",
        "16             1394   164   635 2025-08-08 22:37:00   8564  \n",
        "17             3483   120   637 2025-08-08 22:34:00   8281  \n",
-       "18             3365   361   468 2025-11-08 17:42:00   6515  \n",
+       "18             3365   361   468 2025-08-11 17:42:00   6515  \n",
        "19             1782   188   166 2025-08-08 23:03:00   6899  \n",
-       "20              993   119   571 2025-10-08 18:31:00   5308  \n",
-       "21             1258    41   475 2025-10-08 04:12:00   4167  \n",
+       "20              993   119   571 2025-08-10 18:31:00   5308  \n",
+       "21             1258    41   475 2025-08-10 04:12:00   4167  \n",
        "22             1969   163   425 2025-08-08 23:17:00   3863  \n",
-       "23             1096   164   731 2025-11-08 15:33:00   2696  \n",
-       "24               91     0     0 2025-12-08 13:32:00    191  "
+       "23             1096   164   731 2025-08-11 15:33:00   2696  \n",
+       "24               91     0     0 2025-08-12 13:32:00    191  "
       ],
       "text/html": [
        "<div>\n",
@@ -668,7 +641,7 @@
        "      <td>36261</td>\n",
        "      <td>379</td>\n",
        "      <td>602</td>\n",
-       "      <td>2025-09-08 00:42:00</td>\n",
+       "      <td>2025-08-09 00:42:00</td>\n",
        "      <td>52601</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -752,7 +725,7 @@
        "      <td>18829</td>\n",
        "      <td>251</td>\n",
        "      <td>553</td>\n",
-       "      <td>2025-09-08 02:28:00</td>\n",
+       "      <td>2025-08-09 02:28:00</td>\n",
        "      <td>29550</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -764,7 +737,7 @@
        "      <td>7753</td>\n",
        "      <td>82</td>\n",
        "      <td>337</td>\n",
-       "      <td>2025-10-08 19:51:00</td>\n",
+       "      <td>2025-08-10 19:51:00</td>\n",
        "      <td>17711</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -788,7 +761,7 @@
        "      <td>5316</td>\n",
        "      <td>322</td>\n",
        "      <td>591</td>\n",
-       "      <td>2025-09-08 17:52:00</td>\n",
+       "      <td>2025-08-09 17:52:00</td>\n",
        "      <td>14376</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -800,7 +773,7 @@
        "      <td>3386</td>\n",
        "      <td>95</td>\n",
        "      <td>498</td>\n",
-       "      <td>2025-09-08 17:07:00</td>\n",
+       "      <td>2025-08-09 17:07:00</td>\n",
        "      <td>11003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -860,7 +833,7 @@
        "      <td>3365</td>\n",
        "      <td>361</td>\n",
        "      <td>468</td>\n",
-       "      <td>2025-11-08 17:42:00</td>\n",
+       "      <td>2025-08-11 17:42:00</td>\n",
        "      <td>6515</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -884,7 +857,7 @@
        "      <td>993</td>\n",
        "      <td>119</td>\n",
        "      <td>571</td>\n",
-       "      <td>2025-10-08 18:31:00</td>\n",
+       "      <td>2025-08-10 18:31:00</td>\n",
        "      <td>5308</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -896,7 +869,7 @@
        "      <td>1258</td>\n",
        "      <td>41</td>\n",
        "      <td>475</td>\n",
-       "      <td>2025-10-08 04:12:00</td>\n",
+       "      <td>2025-08-10 04:12:00</td>\n",
        "      <td>4167</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -920,7 +893,7 @@
        "      <td>1096</td>\n",
        "      <td>164</td>\n",
        "      <td>731</td>\n",
-       "      <td>2025-11-08 15:33:00</td>\n",
+       "      <td>2025-08-11 15:33:00</td>\n",
        "      <td>2696</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -932,7 +905,7 @@
        "      <td>91</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>2025-12-08 13:32:00</td>\n",
+       "      <td>2025-08-12 13:32:00</td>\n",
        "      <td>191</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -940,21 +913,22 @@
        "</div>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 4
+   "execution_count": 28
   },
   {
+   "cell_type": "code",
+   "id": "9f15abc665d134d7",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:07.670668Z",
-     "start_time": "2025-08-19T21:11:07.658321Z"
+     "end_time": "2025-08-19T23:39:55.025235Z",
+     "start_time": "2025-08-19T23:39:55.004437Z"
     }
    },
-   "cell_type": "code",
    "source": [
     "boosts = scorelog[scorelog['sourcename'] == 'Output Boost'][['name', 'score']].groupby('name')\n",
     "\n",
@@ -973,7 +947,6 @@
     "del boosts\n",
     "summary"
    ],
-   "id": "9f15abc665d134d7",
    "outputs": [
     {
      "data": {
@@ -1010,19 +983,19 @@
        "5             28498   240   916 2025-08-08 22:10:00  41486               70   \n",
        "6             16913   190   570 2025-08-08 20:22:00  36884              735   \n",
        "7             18329   328   607 2025-08-08 20:23:00  32599               47   \n",
-       "8             18829   251   553 2025-09-08 02:28:00  29550              110   \n",
-       "9              7753    82   337 2025-10-08 19:51:00  17711              842   \n",
+       "8             18829   251   553 2025-08-09 02:28:00  29550              110   \n",
+       "9              7753    82   337 2025-08-10 19:51:00  17711              842   \n",
        "10             3304   216   505 2025-08-08 20:14:00  17026             2341   \n",
-       "11             5316   322   591 2025-09-08 17:52:00  14376              738   \n",
-       "12             3386    95   498 2025-09-08 17:07:00  11003               40   \n",
+       "11             5316   322   591 2025-08-09 17:52:00  14376              738   \n",
+       "12             3386    95   498 2025-08-09 17:07:00  11003               40   \n",
        "13             7694    67   289 2025-08-08 22:54:00  13340             3439   \n",
        "14             3756   183   227 2025-08-08 21:46:00  10057              277   \n",
        "15             1394   164   635 2025-08-08 22:37:00   8564               38   \n",
        "16             3483   120   637 2025-08-08 22:34:00   8281               24   \n",
        "17             1782   188   166 2025-08-08 23:03:00   6899             1113   \n",
-       "18              993   119   571 2025-10-08 18:31:00   5308               31   \n",
+       "18              993   119   571 2025-08-10 18:31:00   5308               31   \n",
        "19             1969   163   425 2025-08-08 23:17:00   3863              665   \n",
-       "20             1096   164   731 2025-11-08 15:33:00   2696               45   \n",
+       "20             1096   164   731 2025-08-11 15:33:00   2696               45   \n",
        "\n",
        "    totalboostduration  maxboostscore  maxboostduration  \n",
        "0                 6810            199              1990  \n",
@@ -1219,7 +1192,7 @@
        "      <td>18829</td>\n",
        "      <td>251</td>\n",
        "      <td>553</td>\n",
-       "      <td>2025-09-08 02:28:00</td>\n",
+       "      <td>2025-08-09 02:28:00</td>\n",
        "      <td>29550</td>\n",
        "      <td>110</td>\n",
        "      <td>1100</td>\n",
@@ -1235,7 +1208,7 @@
        "      <td>7753</td>\n",
        "      <td>82</td>\n",
        "      <td>337</td>\n",
-       "      <td>2025-10-08 19:51:00</td>\n",
+       "      <td>2025-08-10 19:51:00</td>\n",
        "      <td>17711</td>\n",
        "      <td>842</td>\n",
        "      <td>8420</td>\n",
@@ -1267,7 +1240,7 @@
        "      <td>5316</td>\n",
        "      <td>322</td>\n",
        "      <td>591</td>\n",
-       "      <td>2025-09-08 17:52:00</td>\n",
+       "      <td>2025-08-09 17:52:00</td>\n",
        "      <td>14376</td>\n",
        "      <td>738</td>\n",
        "      <td>7380</td>\n",
@@ -1283,7 +1256,7 @@
        "      <td>3386</td>\n",
        "      <td>95</td>\n",
        "      <td>498</td>\n",
-       "      <td>2025-09-08 17:07:00</td>\n",
+       "      <td>2025-08-09 17:07:00</td>\n",
        "      <td>11003</td>\n",
        "      <td>40</td>\n",
        "      <td>400</td>\n",
@@ -1379,7 +1352,7 @@
        "      <td>993</td>\n",
        "      <td>119</td>\n",
        "      <td>571</td>\n",
-       "      <td>2025-10-08 18:31:00</td>\n",
+       "      <td>2025-08-10 18:31:00</td>\n",
        "      <td>5308</td>\n",
        "      <td>31</td>\n",
        "      <td>310</td>\n",
@@ -1411,7 +1384,7 @@
        "      <td>1096</td>\n",
        "      <td>164</td>\n",
        "      <td>731</td>\n",
-       "      <td>2025-11-08 15:33:00</td>\n",
+       "      <td>2025-08-11 15:33:00</td>\n",
        "      <td>2696</td>\n",
        "      <td>45</td>\n",
        "      <td>450</td>\n",
@@ -1423,20 +1396,20 @@
        "</div>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 5
+   "execution_count": 29
   },
   {
    "cell_type": "code",
    "id": "583c3529-d482-4891-84fa-880920f631b6",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:07.874878Z",
-     "start_time": "2025-08-19T21:11:07.779114Z"
+     "end_time": "2025-08-19T23:39:55.305636Z",
+     "start_time": "2025-08-19T23:39:55.152953Z"
     }
    },
    "source": [
@@ -1456,19 +1429,19 @@
      "output_type": "display_data"
     }
    ],
-   "execution_count": 6
+   "execution_count": 30
   },
   {
    "cell_type": "code",
    "id": "1b54986e-4f48-4208-96ad-61203e74c38c",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:07.986493Z",
-     "start_time": "2025-08-19T21:11:07.931939Z"
+     "end_time": "2025-08-19T23:39:55.512773Z",
+     "start_time": "2025-08-19T23:39:55.405984Z"
     }
    },
    "source": [
-    "plt.hist2d(scorelog['mapx'], scorelog['mapy'], density=False, bins=50)\n",
+    "plt.hist2d(scorelog['mapx'], scorelog['mapy'], weights=scorelog['score'], density=False, bins=50)\n",
     "plt.show()"
    ],
    "outputs": [
@@ -1477,75 +1450,497 @@
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ],
-      "image/png": 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"
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pKCjQmDFjlJubG7S9vLxc9fX1Qdv79eunXr16yePxSJI8Ho8GDBggp9MZGJOXlye/369t27a1+PVqa2vl9/uDXgAAhGro5saQXrBHqx/UtmzZMn3wwQfasGHDMfu8Xq+SkpKUlpYWtN3pdMrr9QbG/HecNO9v3teS4uJizZkzp7VTBQAAUapVV1D27Nmj22+/XUuXLlX79u3DNadjFBUVyefzBV579uxps68NAADaXqsCpby8XNXV1br44ouVkJCghIQElZaWav78+UpISJDT6VRdXZ1qamqC3ldVVSWXyyVJcrlcx9zV0/zn5jFHS05OlsPhCHoBAIDY1apAGTFihLZs2aLNmzcHXkOGDFF+fn7gvxMTE1VSUhJ4T0VFhSorK+V2uyVJbrdbW7ZsUXV1dWDMmjVr5HA4lJ2dfZoOCwAARLNWfQalc+fO6t+/f9C2jh07qlu3boHtEydO1LRp09S1a1c5HA7ddtttcrvdGjZsmCRp5MiRys7O1g033KC5c+fK6/Xq3nvvVUFBgZKTk0/TYQEAgGh22n+b8e9+9zvFx8dr3Lhxqq2tVV5enp588snA/nbt2mnlypWaMmWK3G63OnbsqAkTJuj+++8/3VMBAABRKs4YYyI9idby+/1KTU3VFbpGCXGJkZ4OAAAIQYOp1zqtkM/nO+HnSfldPAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsE5CpCeA6Hfg+mEhjev8wvowzwQAECu4ggIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA63CbMU4Ztw8DAE43rqAAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6CZGeANpew/8MCWlcwpqNYZ4JAAAt4woKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKzDbcZnIG4fBgDYjisoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwTkKkJwDgzBE3dEBI48z7W8I8EwC24woKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOvwHBQAbYbnmwAIFVdQAACAdQgUAABgnVYFSnFxsS655BJ17txZ6enpGjt2rCoqKoLGHDlyRAUFBerWrZs6deqkcePGqaqqKmhMZWWlxowZow4dOig9PV0zZsxQQ0PDqR8NAACICa0KlNLSUhUUFGj9+vVas2aN6uvrNXLkSB06dCgw5o477tBrr72ml156SaWlpdq7d6+uvfbawP7GxkaNGTNGdXV1eu+997RkyRItXrxYs2fPPn1HBQAAolqcMcac7Jv37dun9PR0lZaW6vLLL5fP51OPHj30/PPP68c//rEk6eOPP9b5558vj8ejYcOGadWqVbrqqqu0d+9eOZ1OSdLChQt19913a9++fUpKSjrh1/X7/UpNTdUVukYJcYknO30AANCGGky91mmFfD6fHA7Hccee0mdQfD6fJKlr166SpPLyctXX1ys3Nzcwpl+/furVq5c8Ho8kyePxaMCAAYE4kaS8vDz5/X5t27btVKYDAABixEnfZtzU1KSpU6dq+PDh6t+/vyTJ6/UqKSlJaWlpQWOdTqe8Xm9gzH/HSfP+5n0tqa2tVW1tbeDPfr//ZKcNAACiwElfQSkoKNDWrVu1bNmy0zmfFhUXFys1NTXw6tmzZ9i/JgAAiJyTCpTCwkKtXLlSb775ps4666zAdpfLpbq6OtXU1ASNr6qqksvlCow5+q6e5j83jzlaUVGRfD5f4LVnz56TmTYAAIgSrQoUY4wKCwu1fPlyrV27VllZWUH7Bw8erMTERJWUlAS2VVRUqLKyUm63W5Lkdru1ZcsWVVdXB8asWbNGDodD2dnZLX7d5ORkORyOoBcAAIhdrfoMSkFBgZ5//nmtWLFCnTt3DnxmJDU1VSkpKUpNTdXEiRM1bdo0de3aVQ6HQ7fddpvcbreGDRsmSRo5cqSys7N1ww03aO7cufJ6vbr33ntVUFCg5OTk03+EAAAg6rTqNuO4uLgWty9atEg33nijpH8/qG369Ol64YUXVFtbq7y8PD355JNBP7757LPPNGXKFK1bt04dO3bUhAkT9MgjjyghIbRe4jZjAACiT2tuMz6l56BECoECAED0aU2g8NuMAbSZhL7nhjSuYeenYZ4JANvxywIBAIB1CBQAAGAdAgUAAFiHQAEAANYhUAAAgHUIFAAAYB0CBQAAWIfnoABoMzzfBECouIICAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsQ6AAAADrECgAAMA6BAoAALAOgQIAAKxDoAAAAOsQKAAAwDoECgAAsA6BAgAArEOgAAAA6xAoAADAOgQKAACwDoECAACsE9FAeeKJJ3T22Werffv2ysnJ0fvvvx/J6QAAAEtELFD+/Oc/a9q0abrvvvv0wQcfaNCgQcrLy1N1dXWkpgQAACwRsUCZN2+eJk2apJtuuknZ2dlauHChOnTooGeffTZSUwIAAJZIiMQXraurU3l5uYqKigLb4uPjlZubK4/Hc8z42tpa1dbWBv7s8/kkSQ2ql0z45wsAAE5dg+olScac+B/viATKV199pcbGRjmdzqDtTqdTH3/88THji4uLNWfOnGO2v6PXwzZHAAAQHgcOHFBqaupxx0QkUFqrqKhI06ZNC/y5pqZGvXv3VmVl5QkPMJb5/X717NlTe/bskcPhiPR0IoI1YA2asQ6sQTPWwd41MMbowIEDyszMPOHYiARK9+7d1a5dO1VVVQVtr6qqksvlOmZ8cnKykpOTj9memppq1cJHisPhOOPXgTVgDZqxDqxBM9bBzjUI9cJCRD4km5SUpMGDB6ukpCSwrampSSUlJXK73ZGYEgAAsEjEfsQzbdo0TZgwQUOGDNHQoUP12GOP6dChQ7rpppsiNSUAAGCJiAXKddddp3379mn27Nnyer268MILtXr16mM+ONuS5ORk3XfffS3+2OdMwjqwBhJr0Ix1YA2asQ6xsQZxJpR7fQAAANoQv4sHAABYh0ABAADWIVAAAIB1CBQAAGCdqAyUJ554Qmeffbbat2+vnJwcvf/++5GeUtj87//+r+Li4oJe/fr1C+w/cuSICgoK1K1bN3Xq1Enjxo075gF40eatt97S1VdfrczMTMXFxemVV14J2m+M0ezZs5WRkaGUlBTl5uZq586dQWP279+v/Px8ORwOpaWlaeLEiTp48GAbHsWpO9E63HjjjcecG6NGjQoaE+3rUFxcrEsuuUSdO3dWenq6xo4dq4qKiqAxoXwPVFZWasyYMerQoYPS09M1Y8YMNTQ0tOWhnLRQ1uCKK6445ly45ZZbgsZE8xpI0oIFCzRw4MDAg8fcbrdWrVoV2B/r54F04jWIufPARJlly5aZpKQk8+yzz5pt27aZSZMmmbS0NFNVVRXpqYXFfffdZy644ALz5ZdfBl779u0L7L/llltMz549TUlJidm4caMZNmyYufTSSyM441P3+uuvm1/96lfm5ZdfNpLM8uXLg/Y/8sgjJjU11bzyyivmww8/ND/84Q9NVlaW+eabbwJjRo0aZQYNGmTWr19v3n77bdOnTx9z/fXXt/GRnJoTrcOECRPMqFGjgs6N/fv3B42J9nXIy8szixYtMlu3bjWbN282V155penVq5c5ePBgYMyJvgcaGhpM//79TW5urtm0aZN5/fXXTffu3U1RUVEkDqnVQlmD73//+2bSpElB54LP5wvsj/Y1MMaYV1991fz1r381n3zyiamoqDD33HOPSUxMNFu3bjXGxP55YMyJ1yDWzoOoC5ShQ4eagoKCwJ8bGxtNZmamKS4ujuCswue+++4zgwYNanFfTU2NSUxMNC+99FJg244dO4wk4/F42miG4XX0P8xNTU3G5XKZX//614FtNTU1Jjk52bzwwgvGGGO2b99uJJkNGzYExqxatcrExcWZL774os3mfjp9W6Bcc8013/qeWFyH6upqI8mUlpYaY0L7Hnj99ddNfHy88Xq9gTELFiwwDofD1NbWtu0BnAZHr4Ex//6H6fbbb//W98TaGjTr0qWL+dOf/nRGngfNmtfAmNg7D6LqRzx1dXUqLy9Xbm5uYFt8fLxyc3Pl8XgiOLPw2rlzpzIzM3XOOecoPz9flZWVkqTy8nLV19cHrUe/fv3Uq1evmF2P3bt3y+v1Bh1zamqqcnJyAsfs8XiUlpamIUOGBMbk5uYqPj5eZWVlbT7ncFq3bp3S09N13nnnacqUKfr6668D+2JxHXw+nySpa9eukkL7HvB4PBowYEDQQyDz8vLk9/u1bdu2Npz96XH0GjRbunSpunfvrv79+6uoqEiHDx8O7Iu1NWhsbNSyZct06NAhud3uM/I8OHoNmsXSeRAVv8242VdffaXGxsZjnjbrdDr18ccfR2hW4ZWTk6PFixfrvPPO05dffqk5c+boe9/7nrZu3Sqv16ukpCSlpaUFvcfpdMrr9UZmwmHWfFwtnQPN+7xer9LT04P2JyQkqGvXrjG1LqNGjdK1116rrKwsffrpp7rnnns0evRoeTwetWvXLubWoampSVOnTtXw4cPVv39/SQrpe8Dr9bZ4vjTviyYtrYEk/exnP1Pv3r2VmZmpjz76SHfffbcqKir08ssvS4qdNdiyZYvcbreOHDmiTp06afny5crOztbmzZvPmPPg29ZAir3zIKoC5Uw0evTowH8PHDhQOTk56t27t1588UWlpKREcGaItPHjxwf+e8CAARo4cKDOPfdcrVu3TiNGjIjgzMKjoKBAW7du1TvvvBPpqUTMt63B5MmTA/89YMAAZWRkaMSIEfr000917rnntvU0w+a8887T5s2b5fP59Je//EUTJkxQaWlppKfVpr5tDbKzs2PuPIiqH/F0795d7dq1O+aT2VVVVXK5XBGaVdtKS0vTd7/7Xe3atUsul0t1dXWqqakJGhPL69F8XMc7B1wul6qrq4P2NzQ0aP/+/TG7LpJ0zjnnqHv37tq1a5ek2FqHwsJCrVy5Um+++abOOuuswPZQvgdcLleL50vzvmjxbWvQkpycHEkKOhdiYQ2SkpLUp08fDR48WMXFxRo0aJB+//vfn1HnwbetQUui/TyIqkBJSkrS4MGDVVJSEtjW1NSkkpKSoJ/BxbKDBw/q008/VUZGhgYPHqzExMSg9aioqFBlZWXMrkdWVpZcLlfQMfv9fpWVlQWO2e12q6amRuXl5YExa9euVVNTU+AbNhZ9/vnn+vrrr5WRkSEpNtbBGKPCwkItX75ca9euVVZWVtD+UL4H3G63tmzZEhRra9askcPhCFwat9mJ1qAlmzdvlqSgcyGa1+DbNDU1qba29ow4D75N8xq0JOrPg0h/Sre1li1bZpKTk83ixYvN9u3bzeTJk01aWlrQp5JjyfTp0826devM7t27zbvvvmtyc3NN9+7dTXV1tTHm37fW9erVy6xdu9Zs3LjRuN1u43a7IzzrU3PgwAGzadMms2nTJiPJzJs3z2zatMl89tlnxph/32aclpZmVqxYYT766CNzzTXXtHib8UUXXWTKysrMO++8Y/r27RtVt9cac/x1OHDggLnzzjuNx+Mxu3fvNn//+9/NxRdfbPr27WuOHDkS+DuifR2mTJliUlNTzbp164JunTx8+HBgzIm+B5pvrRw5cqTZvHmzWb16tenRo4e1t1Ye7URrsGvXLnP//febjRs3mt27d5sVK1aYc845x1x++eWBvyPa18AYY2bOnGlKS0vN7t27zUcffWRmzpxp4uLizBtvvGGMif3zwJjjr0EsngdRFyjGGPP444+bXr16maSkJDN06FCzfv36SE8pbK677jqTkZFhkpKSzHe+8x1z3XXXmV27dgX2f/PNN+bWW281Xbp0MR06dDA/+tGPzJdffhnBGZ+6N99800g65jVhwgRjzL9vNZ41a5ZxOp0mOTnZjBgxwlRUVAT9HV9//bW5/vrrTadOnYzD4TA33XSTOXDgQASO5uQdbx0OHz5sRo4caXr06GESExNN7969zaRJk44J9Whfh5aOX5JZtGhRYEwo3wP//Oc/zejRo01KSorp3r27mT59uqmvr2/jozk5J1qDyspKc/nll5uuXbua5ORk06dPHzNjxoyg518YE91rYIwxN998s+ndu7dJSkoyPXr0MCNGjAjEiTGxfx4Yc/w1iMXzIM4YY9rueg0AAMCJRdVnUAAAwJmBQAEAANYhUAAAgHUIFAAAYB0CBQAAWIdAAQAA1iFQAACAdQgUAABgHQIFAABYh0ABAADWIVAAAIB1CBQAAGCd/w+5dDrXCFZMUwAAAABJRU5ErkJggg=="
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 7
+   "execution_count": 31
   },
   {
+   "cell_type": "code",
+   "id": "1371456d-5f15-4eb3-bd01-82a2bc60607a",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:08.084634Z",
-     "start_time": "2025-08-19T21:11:08.080288Z"
+     "end_time": "2025-08-19T23:40:03.763273Z",
+     "start_time": "2025-08-19T23:39:55.581104Z"
     }
    },
-   "cell_type": "code",
    "source": [
     "# one entry per second per point captured\n",
-    "#\n",
-    "#@dataclass\n",
-    "#class ScoreSecond:\n",
-    "#    name: str\n",
-    "#    sourcename: str\n",
-    "#    when: pandas.Timestamp\n",
-    "#    score: float\n",
-    "#    once: bool\n",
-    "#    mapx: int\n",
-    "#    mapy: int\n",
-    "#\n",
-    "#\n",
-    "#def row_to_scoreseconds(row, score_per):\n",
-    "#    seconds = floor(row.score / score_per)\n",
-    "#    assert row.score % score_per < 0.1\n",
-    "#    when = floor(row.when.timestamp())\n",
-    "#    for elapsed in range(0, seconds):\n",
-    "#        timestamp = pandas.Timestamp(when - elapsed)\n",
-    "#        yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=timestamp, score=score_per, once=False)\n",
-    "#\n",
-    "#def gen_scoreseconds():\n",
-    "#    for row in scorelog.itertuples():\n",
-    "#        if row.sourcename == \"Capture\":\n",
-    "#            yield from row_to_scoreseconds(row, 1.0)\n",
-    "#        elif row.sourcename == \"Output Boost\":\n",
-    "#            yield from row_to_scoreseconds(row, 0.1)\n",
-    "#        else: # one-off\n",
-    "#            yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=row.when, score=row.score, once=True)\n",
-    "#\n",
-    "#scoreseconds = pandas.DataFrame(gen_scoreseconds())\n",
-    "#scoreseconds\n"
+    "\n",
+    "import numpy as np\n",
+    "from dataclasses import dataclass\n",
+    "from math import floor\n",
+    "\n",
+    "@dataclass\n",
+    "class ScoreSecond:\n",
+    "    name: str\n",
+    "    sourcename: str\n",
+    "    when: datetime\n",
+    "    score: float\n",
+    "    once: bool\n",
+    "    mapx: int\n",
+    "    mapy: int\n",
+    "\n",
+    "def row_to_scoreseconds(row, score_per):\n",
+    "    seconds = int(floor(row.score / score_per))\n",
+    "    assert row.score % score_per < 0.1\n",
+    "    when = int(floor(row.when.timestamp()))\n",
+    "    for elapsed in range(0, seconds):\n",
+    "        timestamp = pandas.Timestamp(when - elapsed, unit='s')\n",
+    "        yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=timestamp, score=score_per, once=False)\n",
+    "\n",
+    "def gen_scoreseconds():\n",
+    "    for row in scorelog.itertuples():\n",
+    "        if row.sourcename == \"Capture\":\n",
+    "            yield from row_to_scoreseconds(row, 1.0)\n",
+    "        elif row.sourcename == \"Output Boost\":\n",
+    "            yield from row_to_scoreseconds(row, 0.1)\n",
+    "        else: # one-off\n",
+    "            yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=row.when, score=row.score, once=True)\n",
+    "\n",
+    "scoreseconds = pandas.DataFrame(gen_scoreseconds())\n",
+    "scoreseconds.sort_values(by=['when'], inplace=True)\n",
+    "scoreseconds.reset_index(drop=True, inplace=True)\n",
+    "scoreseconds"
    ],
-   "id": "1371456d-5f15-4eb3-bd01-82a2bc60607a",
-   "outputs": [],
-   "execution_count": 8
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "                        name    sourcename                when  score   once  \\\n",
+       "0                  Info Desk   First Visit 2025-08-08 20:14:00  100.0   True   \n",
+       "1                  Info Desk       Capture 2025-08-08 20:14:19    1.0  False   \n",
+       "2                  Info Desk       Capture 2025-08-08 20:14:20    1.0  False   \n",
+       "3                  Info Desk       Capture 2025-08-08 20:14:21    1.0  False   \n",
+       "4                  Info Desk       Capture 2025-08-08 20:14:22    1.0  False   \n",
+       "...                      ...           ...                 ...    ...    ...   \n",
+       "678874  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:56    0.1  False   \n",
+       "678875  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:57    0.1  False   \n",
+       "678876  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:58    0.1  False   \n",
+       "678877  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:59    0.1  False   \n",
+       "678878  Maker Days Eindhoven  Output Boost 2025-08-12 14:00:00    0.1  False   \n",
+       "\n",
+       "        mapx  mapy  \n",
+       "0        216   505  \n",
+       "1        216   505  \n",
+       "2        216   505  \n",
+       "3        216   505  \n",
+       "4        216   505  \n",
+       "...      ...   ...  \n",
+       "678874   115   749  \n",
+       "678875   115   749  \n",
+       "678876   115   749  \n",
+       "678877   115   749  \n",
+       "678878   115   749  \n",
+       "\n",
+       "[678879 rows x 7 columns]"
+      ],
+      "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>name</th>\n",
+       "      <th>sourcename</th>\n",
+       "      <th>when</th>\n",
+       "      <th>score</th>\n",
+       "      <th>once</th>\n",
+       "      <th>mapx</th>\n",
+       "      <th>mapy</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>First Visit</td>\n",
+       "      <td>2025-08-08 20:14:00</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:19</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:20</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:21</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:22</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678874</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:56</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678875</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:57</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678876</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:58</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678877</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:59</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678878</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 14:00:00</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>678879 rows × 7 columns</p>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 32
   },
   {
    "cell_type": "code",
    "id": "24ead54a-01ce-4ab2-9b4e-ffeeaa7191c9",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-08-19T21:11:08.196471Z",
-     "start_time": "2025-08-19T21:11:08.193913Z"
+     "end_time": "2025-08-19T23:40:08.295387Z",
+     "start_time": "2025-08-19T23:40:04.343690Z"
     }
    },
    "source": [
-    "#plt.hist2d(scoreseconds['mapx'], scoreseconds['mapy'], density=False, bins=40)\n",
-    "#plt.show()"
+    "acc_col = pandas.Series([0.0]).repeat(len(scoreseconds)).reset_index(drop=True)\n",
+    "\n",
+    "acc = 0.0\n",
+    "for i, row in enumerate(scoreseconds.itertuples()):\n",
+    "    acc += row.score\n",
+    "    acc_col[i] = acc\n",
+    "\n",
+    "scoreseconds['accumulated_score'] = acc_col\n",
+    "del acc\n",
+    "del acc_col\n",
+    "\n",
+    "scoreseconds"
    ],
-   "outputs": [],
-   "execution_count": 9
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "                        name    sourcename                when  score   once  \\\n",
+       "0                  Info Desk   First Visit 2025-08-08 20:14:00  100.0   True   \n",
+       "1                  Info Desk       Capture 2025-08-08 20:14:19    1.0  False   \n",
+       "2                  Info Desk       Capture 2025-08-08 20:14:20    1.0  False   \n",
+       "3                  Info Desk       Capture 2025-08-08 20:14:21    1.0  False   \n",
+       "4                  Info Desk       Capture 2025-08-08 20:14:22    1.0  False   \n",
+       "...                      ...           ...                 ...    ...    ...   \n",
+       "678874  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:56    0.1  False   \n",
+       "678875  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:57    0.1  False   \n",
+       "678876  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:58    0.1  False   \n",
+       "678877  Maker Days Eindhoven  Output Boost 2025-08-12 13:59:59    0.1  False   \n",
+       "678878  Maker Days Eindhoven  Output Boost 2025-08-12 14:00:00    0.1  False   \n",
+       "\n",
+       "        mapx  mapy  accumulated_score  \n",
+       "0        216   505         100.000000  \n",
+       "1        216   505         101.000000  \n",
+       "2        216   505         102.000000  \n",
+       "3        216   505         103.000000  \n",
+       "4        216   505         104.000000  \n",
+       "...      ...   ...                ...  \n",
+       "678874   115   749      589647.599999  \n",
+       "678875   115   749      589647.699999  \n",
+       "678876   115   749      589647.799999  \n",
+       "678877   115   749      589647.899999  \n",
+       "678878   115   749      589647.999999  \n",
+       "\n",
+       "[678879 rows x 8 columns]"
+      ],
+      "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>name</th>\n",
+       "      <th>sourcename</th>\n",
+       "      <th>when</th>\n",
+       "      <th>score</th>\n",
+       "      <th>once</th>\n",
+       "      <th>mapx</th>\n",
+       "      <th>mapy</th>\n",
+       "      <th>accumulated_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>First Visit</td>\n",
+       "      <td>2025-08-08 20:14:00</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "      <td>100.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:19</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "      <td>101.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:20</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "      <td>102.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:21</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "      <td>103.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Info Desk</td>\n",
+       "      <td>Capture</td>\n",
+       "      <td>2025-08-08 20:14:22</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>216</td>\n",
+       "      <td>505</td>\n",
+       "      <td>104.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678874</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:56</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "      <td>589647.599999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678875</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:57</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "      <td>589647.699999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678876</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:58</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "      <td>589647.799999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678877</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 13:59:59</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "      <td>589647.899999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>678878</th>\n",
+       "      <td>Maker Days Eindhoven</td>\n",
+       "      <td>Output Boost</td>\n",
+       "      <td>2025-08-12 14:00:00</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>115</td>\n",
+       "      <td>749</td>\n",
+       "      <td>589647.999999</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>678879 rows × 8 columns</p>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 33
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-08-19T23:45:26.737903Z",
+     "start_time": "2025-08-19T23:45:26.511905Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from matplotlib import dates\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.plot('when', 'accumulated_score', data=scoreseconds, )\n",
+    "ax.xaxis.set_major_locator(dates.DayLocator(interval=1))    # every day\n",
+    "ax.xaxis.set_major_formatter(dates.DateFormatter('\\n%d-%m-%Y'))\n",
+    "plt.title('Accumulated Score')\n",
+    "plt.show()"
+   ],
+   "id": "6e0a9a80c70d3bb0",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 42
   }
  ],
  "metadata": {