visualizations/seaborn/seaborn-interactive-bar-chart.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6cb57327-6e2c-4d4e-985d-510bb62b2589",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages \n",
    "import seaborn as sns \n",
    "import mercury as mr "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "90ab1315-d7b0-49ba-94c3-79748b9004da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/mercury+json": "{\n    \"widget\": \"Numeric\",\n    \"value\": 5.0,\n    \"min\": 4.0,\n    \"max\": 10.0,\n    \"step\": 1.0,\n    \"label\": \"How many bars?\",\n    \"model_id\": \"0d69bff82e144d94afb10fcfe562a536\",\n    \"code_uid\": \"Numeric.0.40.26.2-rand8356ea52\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0d69bff82e144d94afb10fcfe562a536",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "mercury.Numeric"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mercury widget\n",
    "number = mr.Numeric(value=5, min=4, max=10, label=\"How many bars?\", step=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "95b4ce07-319f-4e48-bac6-42b0a8b690ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create data \n",
    "all_y = [7, 10, 1, 3, 8, 5, 7, 9, 3, 2]\n",
    "y = all_y[0:int(number.value)]\n",
    "\n",
    "# plot \n",
    "_ = sns.barplot(y)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "venv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}