jira status report.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|████████████████████████████████████████| 194/194 [100%] in 2:48.2 (1.16/s)    \n",
      "|████████████████████████████████████████| 94/94 [100%] in 1:26.9 (1.09/s)      \n"
     ]
    }
   ],
   "source": [
    "# loading required env vars\n",
    "import os\n",
    "env_vars = !cat .env\n",
    "for var in env_vars:\n",
    "    if var:\n",
    "        key, value = var.split('=', 1)\n",
    "        os.environ[key] = value\n",
    "\n",
    "from main import *\n",
    "import seaborn as sns\n",
    "\n",
    "reports = time_in_status_per_key()\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-04-20T13:38:57.765803Z",
     "end_time": "2023-04-20T13:38:57.766110Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "outputs": [
    {
     "data": {
      "text/plain": "         key                     assignee                 created   \n0   FBO-1556       luana.santos@loggi.com 2022-12-19 11:02:41.552  \\\n1   FBO-1519   leonardo.machado@loggi.com 2022-11-24 18:24:08.364   \n2   FBO-1518    jorge.silvestre@loggi.com 2022-11-24 18:18:59.611   \n3   FBO-1569   leonardo.machado@loggi.com 2022-12-29 09:37:34.647   \n4   FBO-1542  leonardo.oliveira@loggi.com 2022-12-09 15:54:58.223   \n..       ...                          ...                     ...   \n83  FBO-1623      yara.oliveira@loggi.com 2023-01-23 17:38:10.137   \n84  FBO-1626  leonardo.oliveira@loggi.com 2023-01-23 19:12:56.387   \n87  FBO-1640   leonardo.machado@loggi.com 2023-01-30 19:30:47.381   \n88  FBO-1585      luis.teixeira@loggi.com 2023-01-09 16:38:30.897   \n89  FBO-1662      luis.teixeira@loggi.com 2023-02-10 15:00:12.808   \n\n                  resolved                   to do                 on hold   \n0  2023-01-09 10:54:32.968  8 days 00:17:44.390000         0 days 00:00:00  \\\n1  2023-01-09 11:41:19.679  0 days 00:00:23.646000  5 days 22:49:34.428000   \n2  2023-01-09 11:43:13.042 17 days 16:54:12.940000         0 days 00:00:00   \n3  2023-01-09 11:46:17.358  0 days 00:00:00.450000         0 days 00:00:00   \n4  2023-01-10 11:03:55.074  9 days 19:41:48.546000         0 days 00:00:00   \n..                     ...                     ...                     ...   \n83 2023-03-07 11:42:20.175  0 days 17:28:24.599000 14 days 10:11:59.455000   \n84 2023-03-13 11:08:26.744 30 days 23:39:41.263000         0 days 00:00:00   \n87 2023-03-21 11:53:11.626 43 days 21:36:14.758000         0 days 00:00:00   \n88 2023-03-24 18:14:21.357 73 days 23:42:24.510000         0 days 00:00:00   \n89 2023-03-28 11:32:23.226  3 days 20:34:31.928000         0 days 00:00:00   \n\n               in progress            code review broadcast   done  \n0          0 days 00:00:00        0 days 00:00:00    0 days 0 days  \n1  13 days 01:43:54.485000 5 days 17:00:51.908000    0 days 0 days  \n2  12 days 00:31:44.231000 5 days 00:07:56.796000    0 days 0 days  \n3          0 days 00:00:00        0 days 00:00:00    0 days 0 days  \n4   6 days 08:06:13.058000 2 days 16:55:27.521000    0 days 0 days  \n..                     ...                    ...       ...    ...  \n83 15 days 17:39:45.767000 7 days 20:57:57.238000    0 days 0 days  \n84  3 days 22:59:03.790000 0 days 16:10:17.761000    0 days 0 days  \n87  0 days 16:03:14.558000 1 days 06:11:10.243000    0 days 0 days  \n88         0 days 00:00:00        0 days 00:00:00    0 days 0 days  \n89         0 days 00:00:00        0 days 00:00:00    0 days 0 days  \n\n[85 rows x 10 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>key</th>\n      <th>assignee</th>\n      <th>created</th>\n      <th>resolved</th>\n      <th>to do</th>\n      <th>on hold</th>\n      <th>in progress</th>\n      <th>code review</th>\n      <th>broadcast</th>\n      <th>done</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>FBO-1556</td>\n      <td>luana.santos@loggi.com</td>\n      <td>2022-12-19 11:02:41.552</td>\n      <td>2023-01-09 10:54:32.968</td>\n      <td>8 days 00:17:44.390000</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>FBO-1519</td>\n      <td>leonardo.machado@loggi.com</td>\n      <td>2022-11-24 18:24:08.364</td>\n      <td>2023-01-09 11:41:19.679</td>\n      <td>0 days 00:00:23.646000</td>\n      <td>5 days 22:49:34.428000</td>\n      <td>13 days 01:43:54.485000</td>\n      <td>5 days 17:00:51.908000</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>FBO-1518</td>\n      <td>jorge.silvestre@loggi.com</td>\n      <td>2022-11-24 18:18:59.611</td>\n      <td>2023-01-09 11:43:13.042</td>\n      <td>17 days 16:54:12.940000</td>\n      <td>0 days 00:00:00</td>\n      <td>12 days 00:31:44.231000</td>\n      <td>5 days 00:07:56.796000</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>FBO-1569</td>\n      <td>leonardo.machado@loggi.com</td>\n      <td>2022-12-29 09:37:34.647</td>\n      <td>2023-01-09 11:46:17.358</td>\n      <td>0 days 00:00:00.450000</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>FBO-1542</td>\n      <td>leonardo.oliveira@loggi.com</td>\n      <td>2022-12-09 15:54:58.223</td>\n      <td>2023-01-10 11:03:55.074</td>\n      <td>9 days 19:41:48.546000</td>\n      <td>0 days 00:00:00</td>\n      <td>6 days 08:06:13.058000</td>\n      <td>2 days 16:55:27.521000</td>\n      <td>0 days</td>\n      <td>0 days</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      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>83</th>\n      <td>FBO-1623</td>\n      <td>yara.oliveira@loggi.com</td>\n      <td>2023-01-23 17:38:10.137</td>\n      <td>2023-03-07 11:42:20.175</td>\n      <td>0 days 17:28:24.599000</td>\n      <td>14 days 10:11:59.455000</td>\n      <td>15 days 17:39:45.767000</td>\n      <td>7 days 20:57:57.238000</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>84</th>\n      <td>FBO-1626</td>\n      <td>leonardo.oliveira@loggi.com</td>\n      <td>2023-01-23 19:12:56.387</td>\n      <td>2023-03-13 11:08:26.744</td>\n      <td>30 days 23:39:41.263000</td>\n      <td>0 days 00:00:00</td>\n      <td>3 days 22:59:03.790000</td>\n      <td>0 days 16:10:17.761000</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>FBO-1640</td>\n      <td>leonardo.machado@loggi.com</td>\n      <td>2023-01-30 19:30:47.381</td>\n      <td>2023-03-21 11:53:11.626</td>\n      <td>43 days 21:36:14.758000</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 16:03:14.558000</td>\n      <td>1 days 06:11:10.243000</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>88</th>\n      <td>FBO-1585</td>\n      <td>luis.teixeira@loggi.com</td>\n      <td>2023-01-09 16:38:30.897</td>\n      <td>2023-03-24 18:14:21.357</td>\n      <td>73 days 23:42:24.510000</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n    <tr>\n      <th>89</th>\n      <td>FBO-1662</td>\n      <td>luis.teixeira@loggi.com</td>\n      <td>2023-02-10 15:00:12.808</td>\n      <td>2023-03-28 11:32:23.226</td>\n      <td>3 days 20:34:31.928000</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days 00:00:00</td>\n      <td>0 days</td>\n      <td>0 days</td>\n    </tr>\n  </tbody>\n</table>\n<p>85 rows × 10 columns</p>\n</div>"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(duration, cfd) = reports\n",
    "report_name, report_content = duration\n",
    "data = pd.DataFrame([x[:-1] for x in report_content[1:]], columns=report_content[0][:-1])\n",
    "data = data[data['assignee']!='']  # no assignee are dismissed issues\n",
    "data['resolved_week'] = data['resolved'].dt.isocalendar().week  # per week"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-04-20T13:47:26.108457Z",
     "end_time": "2023-04-20T13:47:26.150868Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1400x500 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = data[['resolved_week'] + statuses_available]\n",
    "df_long = df.melt(\n",
    "    id_vars=['resolved_week'],\n",
    "    value_vars=statuses_available,\n",
    "    var_name='status',\n",
    "    value_name='duration'\n",
    ")\n",
    "df_long = df_long[df_long['duration'] != pd.Timedelta(0, unit='s')]\n",
    "\n",
    "sns.set_theme(rc={'figure.figsize':(14,5)})\n",
    "ax = sns.barplot(\n",
    "    df_long,\n",
    "    x='resolved_week',\n",
    "    y=df_long['duration'].dt.days,\n",
    "    hue='status'\n",
    ")\n",
    "ax.set_xlabel('Week upon resolved')\n",
    "ax.set_ylabel('Duration (days)')\n",
    "ax.set_title('Evolution of duration for each status')\n",
    "plt.show()\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-04-20T14:29:26.107263Z",
     "end_time": "2023-04-20T14:29:28.656571Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}