diff --git a/examples/notebooks/importing_cycler_data_old.ipynb b/examples/notebooks/importing_cycler_data_old.ipynb
deleted file mode 100644
index 42d8487e..00000000
--- a/examples/notebooks/importing_cycler_data_old.ipynb
+++ /dev/null
@@ -1,67729 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Loading Battery Cycler Data to PyBOP\n",
- "\n",
- "This notebook provides example on how to load battery cycler data without any pre-processing and save it so that this data can be used to run simulations using PyBOP.\n",
- "\n",
- "### Setting up the Environment\n",
- "\n",
- "Before we begin, we need to ensure that we have all the necessary tools. In this example, we use Battery Data Toolkit to load cycler data. More information can be found here: https://github.com/ROVI-org/battery-data-toolkit."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
- "emmontopy 0.7.1 requires pandas<2.2,>=1.2, but you have pandas 2.2.3 which is incompatible.\u001b[0m\u001b[31m\n",
- "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n",
- "Note: you may need to restart the kernel to use updated packages.\n",
- "Note: you may need to restart the kernel to use updated packages.\n"
- ]
- }
- ],
- "source": [
- "%pip install --upgrade pip ipywidgets openpyxl pandas -q\n",
- "%pip install pybop -q\n",
- "#%pip uninstall bpx\n",
- "\n",
- "%pip install battery-data-toolkit -q\n",
- "\n",
- "import numpy as np\n",
- "import plotly.graph_objects as go\n",
- "import plotly.offline as pyo\n",
- "import pybamm\n",
- "from batdata.data import BatteryDataset\n",
- "\n",
- "import pybop"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "In this example, we use battery cycler data from Logan Ward et al. Please refer to DOI: 10.18126/fdxq-7yul for more details. The data is in H5 format. An H5 is one of the Hierarchical Data Formats (HDF) used to store large amount of data in the form of multidimensional arrays."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "data_path = r\"../data/cycler_data/batch_B6D_cell_6.h5\"\n",
- "dataset = BatteryDataset.from_batdata_hdf(data_path)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "To see the metadata which contains cell details, batch information etc., we can use the following commnad."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'name': 'CAMP_batch_B6D_cell_6',\n",
- " 'battery': {'layer_count': 13,\n",
- " 'anode': {'name': 'C',\n",
- " 'supplier': 'Commercial',\n",
- " 'product': 'Graphite',\n",
- " 'thickness': 100.0,\n",
- " 'loading': 7.3,\n",
- " 'porosity': 33.0},\n",
- " 'cathode': {'name': 'NMC111',\n",
- " 'supplier': 'Commercial',\n",
- " 'thickness': 67.0,\n",
- " 'area': 169.2,\n",
- " 'loading': 15.21,\n",
- " 'porosity': 29.0},\n",
- " 'electrolyte': {'name': 'Gen 2'},\n",
- " 'nominal_capacity': 0.3},\n",
- " 'dataset_name': 'camp_2023',\n",
- " 'authors': [('Logan', 'Ward'),\n",
- " ('Joseph', 'Kubal'),\n",
- " ('Susan J.', 'Babinec'),\n",
- " ('Wenquan', 'Lu'),\n",
- " ('Allison', 'Dunlop'),\n",
- " ('Steve', 'Trask'),\n",
- " ('Andrew', 'Jansen'),\n",
- " ('Noah H.', 'Paulson')],\n",
- " 'associated_ids': [Url('https://doi.org/10.1016/j.jpowsour.2022.231127')]}"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "dataset.metadata.model_dump(exclude_defaults=True)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The following code block gives a summary of the cycle statistics."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
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