diff --git a/jenkins-scripts/tools/statistics-analysis/node_timing.ipynb b/jenkins-scripts/tools/statistics-analysis/node_timing.ipynb
new file mode 100644
index 000000000..7b275f2c4
--- /dev/null
+++ b/jenkins-scripts/tools/statistics-analysis/node_timing.ipynb
@@ -0,0 +1,299 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "from datetime import datetime\n",
+    "sns.set(font_scale=1.2)\n",
+    "sns.set_style(\"whitegrid\")\n",
+    "\n",
+    "def load_data(file_path):\n",
+    "    columns = ['timestamp', 'node_name', 'status', 'labels', 'current_job']\n",
+    "    df = pd.read_csv(file_path, names=columns, header=0)\n",
+    "    df['timestamp'] = pd.to_datetime(df['timestamp'], format='%Y-%m-%d %H:%M:%S')\n",
+    "    df['current_job'] = df['current_job'].replace('None', np.nan)\n",
+    "    # Replace the labels using the logic: if docker and gpu-reliable exists in labels use linux-gpu\n",
+    "    def apply_label_rules(labels):\n",
+    "        if 'docker' in labels and 'gpu-reliable' in labels:\n",
+    "            return 'linux-gpu'\n",
+    "        elif 'docker' in labels and 'gpu-reliable' not in labels:\n",
+    "            return 'linux'\n",
+    "        elif 'win' in labels and 'gpu-reliable' in labels:\n",
+    "            return 'windows-gpu'\n",
+    "        elif 'win' in labels and 'gpu-reliable' not in labels:\n",
+    "            return 'windows'        \n",
+    "        elif 'osx' in labels:\n",
+    "            for label in labels.split(', '):\n",
+    "                if label.startswith('osx_'):\n",
+    "                    return label\n",
+    "        elif 'linux-arm64' in labels:\n",
+    "            return 'linux-arm64'          \n",
+    "        else:\n",
+    "            return labels\n",
+    "\n",
+    "    df['labels'] = df['labels'].apply(apply_label_rules)    \n",
+    "    #Filter rows that have status = 'Not Working'\n",
+    "    df = df[df['status'] != 'Not Working'] \n",
+    "    return df\n",
+    "\n",
+    "def calculate_node_stats(df):\n",
+    "    nodes = df['node_name'].unique()\n",
+    "    node_stats = {}\n",
+    "    \n",
+    "    for node in nodes:\n",
+    "        node_df = df[df['node_name'] == node].sort_values('timestamp')\n",
+    "        first_seen = node_df['timestamp'].min()\n",
+    "        last_seen = node_df['timestamp'].max()\n",
+    "        time_alive = (last_seen - first_seen).total_seconds() / 60\n",
+    "        \n",
+    "        busy_records = node_df[node_df['status'] == 'Busy']\n",
+    "        busy_periods = []\n",
+    "        if not busy_records.empty:\n",
+    "            node_df['status_changed'] = node_df['status'] != node_df['status'].shift(1)\n",
+    "            status_changes = node_df[node_df['status_changed']].copy()\n",
+    "            last_records = node_df.groupby('status').last().reset_index()\n",
+    "            status_change_points = pd.concat([status_changes, last_records]).sort_values('timestamp')\n",
+    "            \n",
+    "            current_status = None\n",
+    "            start_time = None\n",
+    "            \n",
+    "            for _, row in status_change_points.iterrows():\n",
+    "                if current_status == 'Busy' and start_time is not None:\n",
+    "                    duration = (row['timestamp'] - start_time).total_seconds() / 60\n",
+    "                    busy_periods.append({\n",
+    "                        'start': start_time,\n",
+    "                        'end': row['timestamp'],\n",
+    "                        'duration': duration,\n",
+    "                        'job': row['current_job']\n",
+    "                    })\n",
+    "                \n",
+    "                current_status = row['status']\n",
+    "                start_time = row['timestamp']\n",
+    "        \n",
+    "        total_busy_time = sum(period['duration'] for period in busy_periods)\n",
+    "        busy_percentage = (total_busy_time / time_alive * 100) if time_alive > 0 else 0\n",
+    "        \n",
+    "        node_stats[node] = {\n",
+    "            'first_seen': first_seen,\n",
+    "            'last_seen': last_seen,\n",
+    "            'time_alive': time_alive,\n",
+    "            'busy_time': total_busy_time,\n",
+    "            'idle_time': time_alive - total_busy_time,\n",
+    "            'busy_percentage': busy_percentage,\n",
+    "            'busy_periods': busy_periods,\n",
+    "            'status_history': node_df[['timestamp', 'status', 'current_job']].to_dict('records'),\n",
+    "            'labels': node_df['labels'].iloc[0]\n",
+    "        }\n",
+    "    \n",
+    "    return node_stats\n",
+    "\n",
+    "def generate_node_report(node_stats):\n",
+    "    sorted_nodes = sorted(node_stats.items(), key=lambda x: x[1]['busy_percentage'], reverse=True)\n",
+    "    report_data = []\n",
+    "    for node, stats in sorted_nodes:\n",
+    "        report_data.append({\n",
+    "            'Node Name': node,\n",
+    "            'Time Alive (min)': round(stats['time_alive'], 2),\n",
+    "            'Busy Time (min)': round(stats['busy_time'], 2),\n",
+    "            'Idle Time (min)': round(stats['idle_time'], 2),\n",
+    "            'Busy (%)': round(stats['busy_percentage'], 2),\n",
+    "            'First Seen': stats['first_seen'],\n",
+    "            'Last Seen': stats['last_seen'],\n",
+    "            'Number of Jobs': len(stats['busy_periods']),\n",
+    "            'Labels': stats['labels']\n",
+    "        })\n",
+    "    \n",
+    "    report_df = pd.DataFrame(report_data)\n",
+    "    return report_df\n",
+    "\n",
+    "def analyze_jenkins_nodes(df, title='Jenkins Nodes Activity'):\n",
+    "    node_stats = calculate_node_stats(df)\n",
+    "    report = generate_node_report(node_stats)\n",
+    "    display(report.style.set_caption(title).set_table_styles(\n",
+    "        [{'selector': 'thead th', 'props': [('background-color', '#f7f7f9'), ('color', '#333'), ('border', '1px solid #ddd')]},\n",
+    "         {'selector': 'tbody tr:nth-child(even)', 'props': [('background-color', '#f9f9f9')]},\n",
+    "         {'selector': 'tbody tr:nth-child(odd)', 'props': [('background-color', '#fff')]},\n",
+    "         {'selector': 'tbody td', 'props': [('border', '1px solid #ddd'), ('color', '#000')]}]\n",
+    "    ).set_properties(**{'text-align': 'center'}))    \n",
+    "    return df, node_stats, report\n",
+    "\n",
+    "\n",
+    "df = load_data(\"agent_data.csv\")\n",
+    "# Absolute\n",
+    "# df, node_stats, report = analyze_jenkins_nodes(df)\n",
+    "# filter data to show only workdays\n",
+    "df_workdays = df[df['timestamp'].dt.dayofweek < 5]\n",
+    "df_workdays, node_stats_workdays, report = analyze_jenkins_nodes(df_workdays, title='Jenkins Nodes Activity (Workdays)')\n",
+    "# filter data to show only weekends\n",
+    "df_weekends = df[df['timestamp'].dt.dayofweek >= 5]\n",
+    "df_weekends, node_stats_weekends, report = analyze_jenkins_nodes(df_weekends, title='Jenkins Nodes Activity (Weekends)')\n",
+    "\n",
+    "# Generate daily hourly activity report. Group the data by day and hour and calculate the busy/idle times\n",
+    "def calculate_hourly_stats(df):\n",
+    "    hourly_stats = {}\n",
+    "    for _, row in df.iterrows():\n",
+    "        day = row['timestamp'].date()\n",
+    "        hour = row['timestamp'].hour\n",
+    "        if day not in hourly_stats:\n",
+    "            hourly_stats[day] = {}\n",
+    "        \n",
+    "        if hour not in hourly_stats[day]:\n",
+    "            hourly_stats[day][hour] = {\n",
+    "                'busy_time': 0,\n",
+    "                'idle_time': 0,\n",
+    "                'not_working_time': 0\n",
+    "            }\n",
+    "        \n",
+    "        if row['status'] == 'Busy':\n",
+    "            hourly_stats[day][hour]['busy_time'] += 1\n",
+    "        elif row['status'] == 'Idle':\n",
+    "            hourly_stats[day][hour]['idle_time'] += 1\n",
+    "        elif row['status'] == 'Not Working':\n",
+    "            hourly_stats[day][hour]['not_working_time'] += 1\n",
+    "        else:\n",
+    "            raise ValueError(f\"Unknown status in node: {row['status']}\")\n",
+    "            \n",
+    "    \n",
+    "    return hourly_stats\n",
+    "\n",
+    "hourly_stats_workdays = calculate_hourly_stats(df_workdays)\n",
+    "hourly_stats_weekends = calculate_hourly_stats(df_weekends)\n",
+    "\n",
+    "# With the hourly stats calculate the percentage of busy time for each hour of the day\n",
+    "#f from all days\n",
+    "def calculate_hourly_percentage(hourly_stats, title='Jenkins Nodes Hourly Activity'):\n",
+    "    hourly_percentage = {}\n",
+    "    for day, stats in hourly_stats.items():\n",
+    "        for hour, values in stats.items():\n",
+    "            if hour not in hourly_percentage:\n",
+    "                hourly_percentage[hour] = {\n",
+    "                    'busy_time': 0,\n",
+    "                    'idle_time': 0\n",
+    "                }\n",
+    "            \n",
+    "            hourly_percentage[hour]['busy_time'] += values['busy_time']\n",
+    "            hourly_percentage[hour]['idle_time'] += values['idle_time']\n",
+    "    \n",
+    "    for hour, values in hourly_percentage.items():\n",
+    "        total_time = values['busy_time'] + values['idle_time']\n",
+    "        values['busy_percentage'] = (values['busy_time'] / total_time * 100) if total_time > 0 else 0\n",
+    "    \n",
+    "    # print the hourly percentage in a nice table\n",
+    "    hourly_percentage_df = pd.DataFrame(hourly_percentage).T\n",
+    "    hourly_percentage_df = hourly_percentage_df.rename_axis('Hour').reset_index()\n",
+    "    hourly_percentage_df = hourly_percentage_df[['Hour', 'busy_time', 'idle_time', 'busy_percentage']]\n",
+    "    display(hourly_percentage_df.style.set_caption(title).set_table_styles(\n",
+    "        [{'selector': 'thead th', 'props': [('background-color', '#f7f7f9'), ('color', '#333'), ('border', '1px solid #ddd')]},\n",
+    "         {'selector': 'tbody tr:nth-child(even)', 'props': [('background-color', '#f9f9f9')]},\n",
+    "         {'selector': 'tbody tr:nth-child(odd)', 'props': [('background-color', '#fff')]},\n",
+    "         {'selector': 'tbody td', 'props': [('border', '1px solid #ddd'), ('color', '#000')]}]\n",
+    "    ).set_properties(**{'text-align': 'center'}))\n",
+    "\n",
+    "\n",
+    "    \n",
+    "    return hourly_percentage\n",
+    "\n",
+    "\n",
+    "hourly_percentage_workdays = calculate_hourly_percentage(hourly_stats_workdays, title='Jenkins Nodes Hourly Activity (Workdays)')\n",
+    "hourly_percentage_weekends = calculate_hourly_percentage(hourly_stats_weekends, title='Jenkins Nodes Hourly Activity (Weekends)')\n",
+    "    \n",
+    "# Group by labels and recalculate the busy/idle times proportionally the time alive of each node\n",
+    "def calculate_label_stats(node_stats):\n",
+    "    label_stats = {}\n",
+    "    for node, stats in node_stats.items():\n",
+    "        label = stats['labels']\n",
+    "        if label not in label_stats:\n",
+    "            label_stats[label] = {\n",
+    "                'time_alive': 0,\n",
+    "                'busy_time': 0,\n",
+    "                'idle_time': 0\n",
+    "            }\n",
+    "        \n",
+    "        label_stats[label]['time_alive'] += stats['time_alive']\n",
+    "        label_stats[label]['busy_time'] += stats['busy_time']\n",
+    "        label_stats[label]['idle_time'] += stats['idle_time']\n",
+    "    \n",
+    "    for label, stats in label_stats.items():\n",
+    "        stats['busy_percentage'] = (stats['busy_time'] / stats['time_alive'] * 100) if stats['time_alive'] > 0 else 0\n",
+    "    \n",
+    "    return label_stats\n",
+    "\n",
+    "def generate_label_report(node_stats, title='Jenkins Nodes Activity by Labels'):\n",
+    "    label_stats = calculate_label_stats(node_stats)\n",
+    "    label_report = pd.DataFrame(label_stats).T\n",
+    "    label_report = label_report.sort_values('busy_percentage', ascending=False)\n",
+    "    label_report = label_report.rename_axis('Labels').reset_index()\n",
+    "    label_report = label_report[['Labels', 'time_alive', 'busy_time', 'idle_time', 'busy_percentage']]\n",
+    "    display(label_report.style.set_caption(title).set_table_styles(\n",
+    "        [{'selector': 'thead th', 'props': [('background-color', '#f7f7f9'), ('color', '#333'), ('border', '1px solid #ddd')]},\n",
+    "         {'selector': 'tbody tr:nth-child(even)', 'props': [('background-color', '#f9f9f9')]},\n",
+    "         {'selector': 'tbody tr:nth-child(odd)', 'props': [('background-color', '#fff')]},\n",
+    "         {'selector': 'tbody td', 'props': [('border', '1px solid #ddd'), ('color', '#000')]}]\n",
+    "    ).set_properties(**{'text-align': 'center'}))\n",
+    "    return label_report\n",
+    "\n",
+    "label_report_workdays = generate_label_report(node_stats_workdays, title='Jenkins Nodes Activity by Labels (workdays)')\n",
+    "label_report_weekends = generate_label_report(node_stats_weekends, title='Jenkins Nodes Activity by Labels (weekends)')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generate statistics for the busy periods\n",
+    "def generate_busy_periods_report(node_stats, title='Jenkins Nodes Busy Periods'):\n",
+    "    busy_periods_data = []\n",
+    "    for node, stats in node_stats.items():\n",
+    "        for period in stats['busy_periods']:\n",
+    "            busy_periods_data.append({\n",
+    "                'Node Name': node,\n",
+    "                'Start Time': period['start'],\n",
+    "                'End Time': period['end'],\n",
+    "                'Duration (min)': round(period['duration'], 2),\n",
+    "                'Job': period['job']\n",
+    "            })\n",
+    "    \n",
+    "    busy_periods_report = pd.DataFrame(busy_periods_data)\n",
+    "    busy_periods_report = busy_periods_report.sort_values('Start Time')\n",
+    "    display(busy_periods_report.style.set_caption(title).set_table_styles(\n",
+    "        [{'selector': 'thead th', 'props': [('background-color', '#f7f7f9'), ('color', '#333'), ('border', '1px solid #ddd')]},\n",
+    "         {'selector': 'tbody tr:nth-child(even)', 'props': [('background-color', '#f9f9f9')]},\n",
+    "         {'selector': 'tbody tr:nth-child(odd)', 'props': [('background-color', '#fff')]},\n",
+    "         {'selector': 'tbody td', 'props': [('border', '1px solid #ddd'), ('color', '#000')]}]\n",
+    "    ).set_properties(**{'text-align': 'center'}))\n",
+    "    return busy_periods_report\n",
+    "\n",
+    "generate_busy_periods_report(node_stats_workdays, title='Jenkins Nodes Busy Periods (workdays)')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "default",
+   "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": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/jenkins-scripts/tools/statistics-analysis/pixi.lock b/jenkins-scripts/tools/statistics-analysis/pixi.lock
new file mode 100644
index 000000000..eb2098503
--- /dev/null
+++ b/jenkins-scripts/tools/statistics-analysis/pixi.lock
@@ -0,0 +1,6905 @@
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diff --git a/jenkins-scripts/tools/statistics-analysis/pixi.toml b/jenkins-scripts/tools/statistics-analysis/pixi.toml
new file mode 100644
index 000000000..fcf0314ce
--- /dev/null
+++ b/jenkins-scripts/tools/statistics-analysis/pixi.toml
@@ -0,0 +1,16 @@
+[project]
+authors = ["Jose Luis Rivero <jrivero@openrobotics.com>"]
+channels = ["conda-forge"]
+description = "Add a short description here"
+name = "pixi_python_pandas"
+platforms = ["win-64", "linux-64"]
+version = "0.1.0"
+
+[tasks]
+
+[dependencies]
+python = "3.12.*"
+pandas = ">=2.2.3,<3"
+jupyter = ">=1.1.1,<2"
+matplotlib = ">=3.10.1,<4"
+seaborn = ">=0.13.2,<0.14"