Bionomial distribution .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "from scipy.stats import binom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/home/.local/lib/python3.8/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "data_binom = binom.rvs(n=10, p=0.6, size=1000)\n",
    "ax = sns.distplot(data_binom,\n",
    "                  bins=100,\n",
    "                  kde=False,\n",
    "                 )\n",
    "_ = ax.set(xlabel='Binomial Distribution ', ylabel='Frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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