popmon/notebooks/popmon_tutorial_basic.ipynb

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    "# (optional) Adjust the jupyter notebook style for easier navigation of the reports\n",
    "from IPython.core.display import display, HTML\n",
    "\n",
    "# Wider notebook\n",
    "display(HTML(\"<style>.container { width:80% !important; }</style>\"))\n",
    "# Cells are higher by default\n",
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    "## Reporting given a histograms object (dict)"
   ]
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   "source": [
    "%%capture\n",
    "# install popmon (if not installed yet)\n",
    "import sys\n",
    "\n",
    "!\"{sys.executable}\" -m pip install popmon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import popmon\n",
    "from popmon import resources"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
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   "source": [
    "df = pd.read_csv(resources.data(\"test.csv.gz\"), parse_dates=[\"date\"])"
   ]
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    "df.head()"
   ]
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    "# first we generate histograms,\n",
    "# but we could load pre-generated histograms from a pickle or json file as well.\n",
    "hists = df.pm_make_histograms(\n",
    "    time_axis=\"date\",\n",
    "    time_width=\"2w\",\n",
    "    features=[\"date:age\", \"date:gender\", \"date:isActive\"],\n",
    ")"
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    "print(hists.keys())"
   ]
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   "outputs": [],
   "source": [
    "# generate report based on histograms\n",
    "report = popmon.stability_report(hists)"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "report  # or report_.to_notebook_iframe()"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "### Regenerate the report\n",
    "A short (limited) report will be generated since `extended_report` flag is set to `False`. \n",
    "If a user wants to configure which statistics she/he wants to see, `show_stats` argument has to be set accordingly."
   ]
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   "cell_type": "code",
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   "source": [
    "report.regenerate(extended_report=False)"
   ]
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   "cell_type": "markdown",
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   "source": [
    "## Reporting given a pandas.DataFrame"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "report_ = df.pm_stability_report(\n",
    "    time_axis=\"date\",\n",
    "    time_width=\"2w\",\n",
    "    features=[\"date:age\", \"date:isActive\", \"date:eyeColor\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "report_"
   ]
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