dragstar328/seaborn_plot_without_set.ipynb

## seaborn_plot_without_set.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7f2b74da2908>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b3c9a9b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "iris = sns.load_dataset('iris')\n",
    "sns.jointplot('sepal_width', 'petal_length', data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {
	"scrolled": false
	},
	"outputs": [
	{
	"data": {
	"text/plain": [
	"<seaborn.axisgrid.JointGrid at 0x7f2b74da2908>"
	]
	},
	"execution_count": 1,
	"metadata": {},
	"output_type": "execute_result"
	},
	{
	"data": {
	"image/png": 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\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x7f2b3c9a9b70>"
	]
	},
	"metadata": {},
	"output_type": "display_data"
	}
	],
	"source": [
	"%matplotlib inline\n",
	"import seaborn as sns\n",
	"\n",
	"iris = sns.load_dataset('iris')\n",
	"sns.jointplot('sepal_width', 'petal_length', data=iris)"
	]
	},
	{
	"cell_type": "code",
	"execution_count": null,
	"metadata": {},
	"outputs": [],
	"source": []
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python 3",
	"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": "3.6.1"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 2
	}