fomightez · April 19, 2026 04:27
diff --git a/getting_started_plotlypowerpoint.ipynb b/getting_started_plotlypowerpoint.ipynb
 {
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# plotlyPowerpoint getting started on mybinder session\n",
    "Based on https://github.com/jonboone1/plotlyPowerpoint/blob/master/example/getting_started.ipynb\n",
    "And the readme there at https://github.com/jonboone1/plotlyPowerpoint/, too\n",
    "\n",
    "Run this notebook in sessions launched from [here](https://github.com/fomightez/3Dscatter_plot_mod_playground-binder)\n",
    "\n",
    "Direct launch:\n",
    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/fomightez/3Dscatter_plot_mod_playground-binder/main?urlpath=%2Flab%2Ftree%2Findex.ipynb)\n",
    "\n",
    "Or put https://mybinder.org/v2/gh/fomightez/3Dscatter_plot_mod_playground-binder/main?urlpath=%2Flab%2Ftree%2Findex.ipynb in your URL  bar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting plotlyPowerpoint\n",
      "  Downloading plotlyPowerpoint-1.3.39-py3-none-any.whl.metadata (6.2 kB)\n",
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      "Building wheels for collected packages: python-pptx, pydataset, numerize\n",
      "\u001b[33m  DEPRECATION: Building 'python-pptx' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'python-pptx'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
      "\u001b[0m  Building wheel for python-pptx (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for python-pptx: filename=python_pptx-0.6.19-py3-none-any.whl size=470020 sha256=a0400009269c6789285740f2ff47aea393d230dacf92a1d212185fcdf8709f48\n",
      "  Stored in directory: /home/jovyan/.cache/pip/wheels/27/10/f3/e564620750d9e3472a3627d6d1fdb8e04f9154dd3704d87288\n",
      "\u001b[33m  DEPRECATION: Building 'pydataset' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'pydataset'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
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      "  Stored in directory: /home/jovyan/.cache/pip/wheels/2b/83/5c/073c3755e8b7704e4677557b2055e61026c1a2342149214c13\n",
      "\u001b[33m  DEPRECATION: Building 'numerize' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'numerize'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
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      "  Stored in directory: /home/jovyan/.cache/pip/wheels/87/84/e1/9e30f2e3da6590acb0f1c03a806e2673d2f9e7f5bd2b11589a\n",
      "Successfully built python-pptx pydataset numerize\n",
      "Installing collected packages: parse, numerize, XlsxWriter, pyflakes, pycodestyle, pluggy, parse-type, mock, mccabe, lxml, iniconfig, cucumber-tag-expressions, cucumber-expressions, colorama, python-pptx, pytest, flake8, behave, pydataset, plotlyPowerpoint\n",
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      "\u001b[1A\u001b[2KSuccessfully installed XlsxWriter-3.2.9 behave-1.3.3 colorama-0.4.6 cucumber-expressions-19.0.0 cucumber-tag-expressions-9.1.0 flake8-7.3.0 iniconfig-2.3.0 lxml-6.1.0 mccabe-0.7.0 mock-5.2.0 numerize-0.12 parse-1.21.1 parse-type-0.6.6 plotlyPowerpoint-1.3.39 pluggy-1.6.0 pycodestyle-2.14.0 pydataset-0.2.0 pyflakes-3.4.0 pytest-9.0.3 python-pptx-0.6.19\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Collecting kaleido==0.2.1\n",
      "  Downloading kaleido-0.2.1-py2.py3-none-manylinux1_x86_64.whl.metadata (15 kB)\n",
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      "\u001b[?25hInstalling collected packages: kaleido\n",
      "Successfully installed kaleido-0.2.1\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install plotlyPowerpoint pydataset \n",
    "%pip install kaleido==0.2.1\n",
    "# \" kaleido 0.2.1 downgrade is a well-known fix for headless environments — good to have that in your back pocket for future Binder/JupyterHub work.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initiated datasets repo at: /home/jovyan/.pydataset/\n"
     ]
    }
   ],
   "source": [
    "from pptx import Presentation\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pydataset import data\n",
    "import plotlyPowerpoint as pp\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "############\n",
    "## Prepare Data\n",
    "############\n",
    "\n",
    "#load datasets\n",
    "global df\n",
    "df = data('InsectSprays')\n",
    "global df2\n",
    "df2 = data(\"JohnsonJohnson\")\n",
    "\n",
    "#Data transformation\n",
    "df['m2'] = df['count'] * 1.1\n",
    "df2['year'] = df2['time'].astype(int)\n",
    "df2 = df2.groupby(['year']).agg({'JohnsonJohnson': 'mean'}).reset_index()\n",
    "\n",
    "#form df3 to showcase faceting on line chart\n",
    "temp = df2.copy()\n",
    "temp['company'] = 'J&J'\n",
    "temp = temp.rename(columns={'JohnsonJohnson': 'price'})\n",
    "\n",
    "temp2 = temp.copy()\n",
    "temp2['company'] = 'Phizer'\n",
    "temp2['price'] = temp2['price'] * 1.1\n",
    "\n",
    "df3 = pd.concat([temp, temp2])\n",
    "\n",
    "#form df4 to showcase faceting and grouping by additional dimension\n",
    "df4 = df.copy()\n",
    "df4['category'] = df['spray']\n",
    "df4.loc[df4['category'].isin(['A','B','C']), 'category'] = 'A'\n",
    "df4.loc[df4['category'].isin(['D','E','F']), 'category'] = 'B'\n",
    "\n",
    "#form df for showcasing a table\n",
    "df5 = df.head()\n",
    "df5['m2'][2] = df5['m2'][2] / 2\n",
    "df5['m3'] = df5['m2'] / 100\n",
    "df5['m4'] = df5['m2']\n",
    "\n",
    "#setup color map for table\n",
    "colorDf = df5.copy()\n",
    "colorDf['m2'] = np.select(\n",
    "    [\n",
    "        colorDf['m2'] >= colorDf['count'],\n",
    "        colorDf['m2'] < colorDf['count']\n",
    "    ],\n",
    "    [\n",
    "        \"#5eed4e\",\n",
    "        \"#ed4e61\"\n",
    "    ],\n",
    "    default=\"\"  # <-- add this\n",
    ")\n",
    "\n",
    "colorDf['count'] = '#fffff2'\n",
    "colorDf['spray'] = '#fffff2'\n",
    "colorDf['m3'] = '#fffff2'\n",
    "colorDf['m4'] = '#fffff2'\n",
    "\n",
    "#final adjustments\n",
    "df5['m2'][3] = None #showing how the library handles NaN values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  8876  100  8876    0     0  52154      0 --:--:-- --:--:-- --:--:-- 52211\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  166k  100  166k    0     0   770k      0 --:--:-- --:--:-- --:--:--  768k\n"
     ]
    }
   ],
   "source": [
    "!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/example/getting_started.ipynb\n",
    "!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/assets/powerpoint_templates/template.pptx\n",
    "#!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/assets/example/template.pptx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "############\n",
    "## Setup Variableas\n",
    "############\n",
    "import plotly.express as px\n",
    "\n",
    "#define custom color palette\n",
    "# https://plotly.com/python/discrete-color/\n",
    "colors = px.colors.qualitative.Vivid\n",
    "\n",
    "#set template for funciton\n",
    "pp.setTemplate(\"template.pptx\")\n",
    "\n",
    "#set color palette\n",
    "pp.setColors(colors)\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "\n",
    "#setup each slide\n",
    "charts = [\n",
    "    { #Line Chart - stock prices\n",
    "        \"data\": df2,\n",
    "        \"type\": \"line\",\n",
    "        \"name\": \"Stock Prices by Company\",\n",
    "        \"metrics\": [\n",
    "            {\"name\": \"JohnsonJohnson\", \"prettyName\": \"Stock Price\", \"method\": \"mean\"}\n",
    "        ],\n",
    "        \"axis\": \"year\",\n",
    "        \"x-axis-title\": 'Year',\n",
    "        \"y-axis-title\": \"Average Stock Price\",\n",
    "        \"description\": \"Grouping by additional variables is easy\",\n",
    "        \"filters\": [\n",
    "            {\"variable\": \"year\", \"operation\": \">=\", \"value\": \"1970\", \"type\":\"int\"}\n",
    "        ],\n",
    "        \"item-index\": {\n",
    "            'slide': 0,\n",
    "            'title': 0,\n",
    "            'chart': 10,\n",
    "            'description': 11\n",
    "        }\n",
    "    },\n",
    "    { #Bar chart of insect sprays\n",
    "        \"data\": df,\n",
    "        \"type\": \"bar\",\n",
    "        \"name\": \"Avg Spray Effictiveness by Type\",\n",
    "        \"metrics\": [\n",
    "            {\"name\": \"count\", \"prettyName\": \"Effectiveness\", \"method\": \"mean\"},\n",
    "            {\"name\": \"m2\", \"prettyName\": \"Effectiveness 2\", \"method\": \"mean\"}\n",
    "        ],\n",
    "        \"axis\": \"spray\",\n",
    "        \"x-axis-title\": \"Effectiveness\",\n",
    "        \"size\": \"wide\",\n",
    "        \"description\": \"this slide has data on it!\",\n",
    "        'options': {\n",
    "            'orientation': 'horizontal',\n",
    "            'color-grouping': 'metric'\n",
    "        },\n",
    "        \"item-index\": {\n",
    "            'slide': 0,\n",
    "            'title': 0,\n",
    "            'chart': 10,\n",
    "            'description': 11\n",
    "        }\n",
    "    }\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 Title 1\n",
      "10 Picture Placeholder 2\n",
      "11 Text Placeholder 3\n"
     ]
    }
   ],
   "source": [
    "from pptx import Presentation\n",
    "\n",
    "prs = Presentation(\"template.pptx\")\n",
    "slide = prs.slides.add_slide(prs.slide_layouts[0])  # adjust layout index as needed\n",
    "\n",
    "for shape in slide.placeholders:\n",
    "    print('%d %s' % (shape.placeholder_format.idx, shape.name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "############\n",
    "## Run Function\n",
    "############\n",
    "#pp.createSlides(charts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "slides = [\n",
    "    {\n",
    "        \"title\": \"Your Slide Title\",\n",
    "        \"description\": \"Your description text\",\n",
    "        \"item-index\": {\n",
    "            \"slide\": 0,\n",
    "            \"title\": 0,\n",
    "            \"description\": 11\n",
    "        },\n",
    "        \"charts\": [                          # <-- charts nested inside each slide\n",
    "            {\n",
    "                \"name\": \"Avg Spray Effectiveness by Type\",\n",
    "                \"data\": df,\n",
    "                \"type\": \"bar\",\n",
    "                \"metrics\": [\n",
    "                    {\"name\": \"count\", \"prettyName\": \"Effectiveness\", \"method\": \"mean\"},\n",
    "                    {\"name\": \"m2\", \"prettyName\": \"Effectiveness 2\", \"method\": \"mean\"}\n",
    "                ],\n",
    "                \"axis\": \"spray\",\n",
    "                \"x-axis-title\": \"Effectiveness\",\n",
    "                \"item-index\": 10             # <-- chart index is just a plain int here\n",
    "            }\n",
    "        ]\n",
    "    }\n",
    "]\n",
    "\n",
    "pp.createSlides(slides)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
 }
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# plotlyPowerpoint getting started on mybinder session\n",
	"Based on https://github.com/jonboone1/plotlyPowerpoint/blob/master/example/getting_started.ipynb\n",
	"And the readme there at https://github.com/jonboone1/plotlyPowerpoint/, too\n",
	"\n",
	"Run this notebook in sessions launched from [here](https://github.com/fomightez/3Dscatter_plot_mod_playground-binder)\n",
	"\n",
	"Direct launch:\n",
	"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/fomightez/3Dscatter_plot_mod_playground-binder/main?urlpath=%2Flab%2Ftree%2Findex.ipynb)\n",
	"\n",
	"Or put https://mybinder.org/v2/gh/fomightez/3Dscatter_plot_mod_playground-binder/main?urlpath=%2Flab%2Ftree%2Findex.ipynb in your URL bar."
	]
	},
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"Collecting plotlyPowerpoint\n",
	" Downloading plotlyPowerpoint-1.3.39-py3-none-any.whl.metadata (6.2 kB)\n",
	"Collecting pydataset\n",
	" Downloading pydataset-0.2.0.tar.gz (15.9 MB)\n",
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	"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25ldone\n",
	"\u001b[?25hRequirement already satisfied: pandas>=1.2.4 in /srv/conda/envs/notebook/lib/python3.10/site-packages (from plotlyPowerpoint) (2.3.3)\n",
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	" Downloading numerize-0.12.tar.gz (2.7 kB)\n",
	" Preparing metadata (setup.py) ... \u001b[?25ldone\n",
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	"Collecting flake8>=2.0 (from plotlyPowerpoint)\n",
	" Downloading flake8-7.3.0-py2.py3-none-any.whl.metadata (3.8 kB)\n",
	"Collecting lxml>=3.1.0 (from plotlyPowerpoint)\n",
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	"Collecting mock>=1.0.1 (from plotlyPowerpoint)\n",
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	"Requirement already satisfied: Pillow>=3.3.2 in /srv/conda/envs/notebook/lib/python3.10/site-packages (from plotlyPowerpoint) (12.2.0)\n",
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	"Collecting pytest>=2.5 (from plotlyPowerpoint)\n",
	" Downloading pytest-9.0.3-py3-none-any.whl.metadata (7.6 kB)\n",
	"Collecting XlsxWriter>=0.5.7 (from plotlyPowerpoint)\n",
	" Downloading xlsxwriter-3.2.9-py3-none-any.whl.metadata (2.7 kB)\n",
	"Collecting python-pptx==0.6.19 (from plotlyPowerpoint)\n",
	" Downloading python-pptx-0.6.19.tar.gz (9.3 MB)\n",
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	"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25ldone\n",
	"\u001b[?25hCollecting cucumber-tag-expressions>=4.1.0 (from behave>=1.2.5->plotlyPowerpoint)\n",
	" Downloading cucumber_tag_expressions-9.1.0-py3-none-any.whl.metadata (4.7 kB)\n",
	"Collecting cucumber-expressions>=17.1.0 (from behave>=1.2.5->plotlyPowerpoint)\n",
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	"Collecting parse>=1.18.0 (from behave>=1.2.5->plotlyPowerpoint)\n",
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	"Collecting parse-type>=0.6.0 (from behave>=1.2.5->plotlyPowerpoint)\n",
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	"Requirement already satisfied: six>=1.15.0 in /srv/conda/envs/notebook/lib/python3.10/site-packages (from behave>=1.2.5->plotlyPowerpoint) (1.17.0)\n",
	"Collecting colorama>=0.3.7 (from behave>=1.2.5->plotlyPowerpoint)\n",
	" Downloading colorama-0.4.6-py2.py3-none-any.whl.metadata (17 kB)\n",
	"Requirement already satisfied: tomli>=1.1.0 in /srv/conda/envs/notebook/lib/python3.10/site-packages (from behave>=1.2.5->plotlyPowerpoint) (2.3.0)\n",
	"Collecting mccabe<0.8.0,>=0.7.0 (from flake8>=2.0->plotlyPowerpoint)\n",
	" Downloading mccabe-0.7.0-py2.py3-none-any.whl.metadata (5.0 kB)\n",
	"Collecting pycodestyle<2.15.0,>=2.14.0 (from flake8>=2.0->plotlyPowerpoint)\n",
	" Downloading pycodestyle-2.14.0-py2.py3-none-any.whl.metadata (4.5 kB)\n",
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	" Downloading iniconfig-2.3.0-py3-none-any.whl.metadata (2.5 kB)\n",
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	"Requirement already satisfied: pygments>=2.7.2 in /srv/conda/envs/notebook/lib/python3.10/site-packages (from pytest>=2.5->plotlyPowerpoint) (2.19.2)\n",
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	"Downloading xlsxwriter-3.2.9-py3-none-any.whl (175 kB)\n",
	"Building wheels for collected packages: python-pptx, pydataset, numerize\n",
	"\u001b[33m DEPRECATION: Building 'python-pptx' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'python-pptx'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
	"\u001b[0m Building wheel for python-pptx (setup.py) ... \u001b[?25ldone\n",
	"\u001b[?25h Created wheel for python-pptx: filename=python_pptx-0.6.19-py3-none-any.whl size=470020 sha256=a0400009269c6789285740f2ff47aea393d230dacf92a1d212185fcdf8709f48\n",
	" Stored in directory: /home/jovyan/.cache/pip/wheels/27/10/f3/e564620750d9e3472a3627d6d1fdb8e04f9154dd3704d87288\n",
	"\u001b[33m DEPRECATION: Building 'pydataset' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'pydataset'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
	"\u001b[0m Building wheel for pydataset (setup.py) ... \u001b[?25ldone\n",
	"\u001b[?25h Created wheel for pydataset: filename=pydataset-0.2.0-py3-none-any.whl size=15939459 sha256=65d2c62d1869a8753386ebb6fb58f2a7e2136f612c664a03717a7cb2c8459db1\n",
	" Stored in directory: /home/jovyan/.cache/pip/wheels/2b/83/5c/073c3755e8b7704e4677557b2055e61026c1a2342149214c13\n",
	"\u001b[33m DEPRECATION: Building 'numerize' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'numerize'. Discussion can be found at https://github.com/pypa/pip/issues/6334\u001b[0m\u001b[33m\n",
	"\u001b[0m Building wheel for numerize (setup.py) ... \u001b[?25ldone\n",
	"\u001b[?25h Created wheel for numerize: filename=numerize-0.12-py3-none-any.whl size=3191 sha256=3d5792e6b75664eee9c4cf66fe64be2a9b2270aceee56c5c7b73e05ae04e002b\n",
	" Stored in directory: /home/jovyan/.cache/pip/wheels/87/84/e1/9e30f2e3da6590acb0f1c03a806e2673d2f9e7f5bd2b11589a\n",
	"Successfully built python-pptx pydataset numerize\n",
	"Installing collected packages: parse, numerize, XlsxWriter, pyflakes, pycodestyle, pluggy, parse-type, mock, mccabe, lxml, iniconfig, cucumber-tag-expressions, cucumber-expressions, colorama, python-pptx, pytest, flake8, behave, pydataset, plotlyPowerpoint\n",
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	"\u001b[1A\u001b[2KSuccessfully installed XlsxWriter-3.2.9 behave-1.3.3 colorama-0.4.6 cucumber-expressions-19.0.0 cucumber-tag-expressions-9.1.0 flake8-7.3.0 iniconfig-2.3.0 lxml-6.1.0 mccabe-0.7.0 mock-5.2.0 numerize-0.12 parse-1.21.1 parse-type-0.6.6 plotlyPowerpoint-1.3.39 pluggy-1.6.0 pycodestyle-2.14.0 pydataset-0.2.0 pyflakes-3.4.0 pytest-9.0.3 python-pptx-0.6.19\n",
	"Note: you may need to restart the kernel to use updated packages.\n",
	"Collecting kaleido==0.2.1\n",
	" Downloading kaleido-0.2.1-py2.py3-none-manylinux1_x86_64.whl.metadata (15 kB)\n",
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	"\u001b[?25hInstalling collected packages: kaleido\n",
	"Successfully installed kaleido-0.2.1\n",
	"Note: you may need to restart the kernel to use updated packages.\n"
	]
	}
	],
	"source": [
	"%pip install plotlyPowerpoint pydataset \n",
	"%pip install kaleido==0.2.1\n",
	"# \" kaleido 0.2.1 downgrade is a well-known fix for headless environments — good to have that in your back pocket for future Binder/JupyterHub work.\""
	]
	},
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"initiated datasets repo at: /home/jovyan/.pydataset/\n"
	]
	}
	],
	"source": [
	"from pptx import Presentation\n",
	"import pandas as pd\n",
	"import numpy as np\n",
	"from pydataset import data\n",
	"import plotlyPowerpoint as pp\n",
	"import warnings\n",
	"warnings.filterwarnings('ignore')\n",
	"\n",
	"############\n",
	"## Prepare Data\n",
	"############\n",
	"\n",
	"#load datasets\n",
	"global df\n",
	"df = data('InsectSprays')\n",
	"global df2\n",
	"df2 = data(\"JohnsonJohnson\")\n",
	"\n",
	"#Data transformation\n",
	"df['m2'] = df['count'] * 1.1\n",
	"df2['year'] = df2['time'].astype(int)\n",
	"df2 = df2.groupby(['year']).agg({'JohnsonJohnson': 'mean'}).reset_index()\n",
	"\n",
	"#form df3 to showcase faceting on line chart\n",
	"temp = df2.copy()\n",
	"temp['company'] = 'J&J'\n",
	"temp = temp.rename(columns={'JohnsonJohnson': 'price'})\n",
	"\n",
	"temp2 = temp.copy()\n",
	"temp2['company'] = 'Phizer'\n",
	"temp2['price'] = temp2['price'] * 1.1\n",
	"\n",
	"df3 = pd.concat([temp, temp2])\n",
	"\n",
	"#form df4 to showcase faceting and grouping by additional dimension\n",
	"df4 = df.copy()\n",
	"df4['category'] = df['spray']\n",
	"df4.loc[df4['category'].isin(['A','B','C']), 'category'] = 'A'\n",
	"df4.loc[df4['category'].isin(['D','E','F']), 'category'] = 'B'\n",
	"\n",
	"#form df for showcasing a table\n",
	"df5 = df.head()\n",
	"df5['m2'][2] = df5['m2'][2] / 2\n",
	"df5['m3'] = df5['m2'] / 100\n",
	"df5['m4'] = df5['m2']\n",
	"\n",
	"#setup color map for table\n",
	"colorDf = df5.copy()\n",
	"colorDf['m2'] = np.select(\n",
	" [\n",
	" colorDf['m2'] >= colorDf['count'],\n",
	" colorDf['m2'] < colorDf['count']\n",
	" ],\n",
	" [\n",
	" \"#5eed4e\",\n",
	" \"#ed4e61\"\n",
	" ],\n",
	" default=\"\" # <-- add this\n",
	")\n",
	"\n",
	"colorDf['count'] = '#fffff2'\n",
	"colorDf['spray'] = '#fffff2'\n",
	"colorDf['m3'] = '#fffff2'\n",
	"colorDf['m4'] = '#fffff2'\n",
	"\n",
	"#final adjustments\n",
	"df5['m2'][3] = None #showing how the library handles NaN values"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 3,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	" % Total % Received % Xferd Average Speed Time Time Time Current\n",
	" Dload Upload Total Spent Left Speed\n",
	"100 8876 100 8876 0 0 52154 0 --:--:-- --:--:-- --:--:-- 52211\n",
	" % Total % Received % Xferd Average Speed Time Time Time Current\n",
	" Dload Upload Total Spent Left Speed\n",
	"100 166k 100 166k 0 0 770k 0 --:--:-- --:--:-- --:--:-- 768k\n"
	]
	}
	],
	"source": [
	"!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/example/getting_started.ipynb\n",
	"!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/assets/powerpoint_templates/template.pptx\n",
	"#!curl -OL https://raw.githubusercontent.com/jonboone1/plotlyPowerpoint/refs/heads/master/assets/example/template.pptx"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 4,
	"metadata": {},
	"outputs": [],
	"source": [
	"############\n",
	"## Setup Variableas\n",
	"############\n",
	"import plotly.express as px\n",
	"\n",
	"#define custom color palette\n",
	"# https://plotly.com/python/discrete-color/\n",
	"colors = px.colors.qualitative.Vivid\n",
	"\n",
	"#set template for funciton\n",
	"pp.setTemplate(\"template.pptx\")\n",
	"\n",
	"#set color palette\n",
	"pp.setColors(colors)\n"
	]
	},
	{
	"cell_type": "raw",
	"metadata": {},
	"source": [
	"\n",
	"#setup each slide\n",
	"charts = [\n",
	" { #Line Chart - stock prices\n",
	" \"data\": df2,\n",
	" \"type\": \"line\",\n",
	" \"name\": \"Stock Prices by Company\",\n",
	" \"metrics\": [\n",
	" {\"name\": \"JohnsonJohnson\", \"prettyName\": \"Stock Price\", \"method\": \"mean\"}\n",
	" ],\n",
	" \"axis\": \"year\",\n",
	" \"x-axis-title\": 'Year',\n",
	" \"y-axis-title\": \"Average Stock Price\",\n",
	" \"description\": \"Grouping by additional variables is easy\",\n",
	" \"filters\": [\n",
	" {\"variable\": \"year\", \"operation\": \">=\", \"value\": \"1970\", \"type\":\"int\"}\n",
	" ],\n",
	" \"item-index\": {\n",
	" 'slide': 0,\n",
	" 'title': 0,\n",
	" 'chart': 10,\n",
	" 'description': 11\n",
	" }\n",
	" },\n",
	" { #Bar chart of insect sprays\n",
	" \"data\": df,\n",
	" \"type\": \"bar\",\n",
	" \"name\": \"Avg Spray Effictiveness by Type\",\n",
	" \"metrics\": [\n",
	" {\"name\": \"count\", \"prettyName\": \"Effectiveness\", \"method\": \"mean\"},\n",
	" {\"name\": \"m2\", \"prettyName\": \"Effectiveness 2\", \"method\": \"mean\"}\n",
	" ],\n",
	" \"axis\": \"spray\",\n",
	" \"x-axis-title\": \"Effectiveness\",\n",
	" \"size\": \"wide\",\n",
	" \"description\": \"this slide has data on it!\",\n",
	" 'options': {\n",
	" 'orientation': 'horizontal',\n",
	" 'color-grouping': 'metric'\n",
	" },\n",
	" \"item-index\": {\n",
	" 'slide': 0,\n",
	" 'title': 0,\n",
	" 'chart': 10,\n",
	" 'description': 11\n",
	" }\n",
	" }\n",
	"]"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 5,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"0 Title 1\n",
	"10 Picture Placeholder 2\n",
	"11 Text Placeholder 3\n"
	]
	}
	],
	"source": [
	"from pptx import Presentation\n",
	"\n",
	"prs = Presentation(\"template.pptx\")\n",
	"slide = prs.slides.add_slide(prs.slide_layouts[0]) # adjust layout index as needed\n",
	"\n",
	"for shape in slide.placeholders:\n",
	" print('%d %s' % (shape.placeholder_format.idx, shape.name))"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 6,
	"metadata": {},
	"outputs": [],
	"source": [
	"############\n",
	"## Run Function\n",
	"############\n",
	"#pp.createSlides(charts)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 7,
	"metadata": {},
	"outputs": [],
	"source": [
	"slides = [\n",
	" {\n",
	" \"title\": \"Your Slide Title\",\n",
	" \"description\": \"Your description text\",\n",
	" \"item-index\": {\n",
	" \"slide\": 0,\n",
	" \"title\": 0,\n",
	" \"description\": 11\n",
	" },\n",
	" \"charts\": [ # <-- charts nested inside each slide\n",
	" {\n",
	" \"name\": \"Avg Spray Effectiveness by Type\",\n",
	" \"data\": df,\n",
	" \"type\": \"bar\",\n",
	" \"metrics\": [\n",
	" {\"name\": \"count\", \"prettyName\": \"Effectiveness\", \"method\": \"mean\"},\n",
	" {\"name\": \"m2\", \"prettyName\": \"Effectiveness 2\", \"method\": \"mean\"}\n",
	" ],\n",
	" \"axis\": \"spray\",\n",
	" \"x-axis-title\": \"Effectiveness\",\n",
	" \"item-index\": 10 # <-- chart index is just a plain int here\n",
	" }\n",
	" ]\n",
	" }\n",
	"]\n",
	"\n",
	"pp.createSlides(slides)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {},
	"outputs": [],
	"source": []
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {},
	"outputs": [],
	"source": []
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {},
	"outputs": [],
	"source": []
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python 3 (ipykernel)",
	"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": "3.10.19"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 4
	}
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