Histogram tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bccff31f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#import required libraries\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from matplotlib import style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3aac1b9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "age_men = 25,11,68,18,27,28,15,43,58,63,43,65,51,36,33,26,23,35,49,58"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b789ea5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3., 6., 4., 2., 5.]),\n",
       " array([11. , 22.4, 33.8, 45.2, 56.6, 68. ]),\n",
       " <BarContainer object of 5 artists>)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(age_men, bins=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4664301b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3., 5., 3., 3., 3., 3.]),\n",
       " array([10, 20, 30, 40, 50, 60, 70]),\n",
       " <BarContainer object of 6 artists>)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins =[10,20,30,40,50,60,70]\n",
    "plt.hist(age_men, bins=bins, edgecolor='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "07e9d45c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Age vs number of people')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#adding style to the plot\n",
    "style.use('ggplot')\n",
    "#plotting the histogram\n",
    "plt.hist(age_men, bins=10, edgecolor='black',\n",
    "         color='blue', rwidth=0.9)\n",
    "#plotting the xlabel\n",
    "plt.xlabel('age of people')\n",
    "#plotting the ylabel\n",
    "plt.ylabel('number of people')\n",
    "#plotting the title of the graph\n",
    "plt.title('Age vs number of people')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0e70d56c",
   "metadata": {},
   "outputs": [],
   "source": [
    "age_men = 25,11,68,18,27,28,15,43,58,63,43,65,51,36,33,26,23,35,49,58\n",
    "age_women = 48,57,59,25,19,37,18,56,22,25,56,25,14,49,53,45,46,19,28,70"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6296ac93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x145d70549a0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set the figure size\n",
    "plt.figure(figsize=(10,7))\n",
    "#add style to the plot\n",
    "style.use('ggplot')\n",
    "#plot the histogram\n",
    "plt.hist([age_men, age_women], bins=10, \n",
    "         color=['blue', 'orange'], histtype='barstacked',\n",
    "         rwidth=0.9, label=['men', 'women'])\n",
    "#add xlabel, ylabel and title\n",
    "plt.xlabel('age of people')\n",
    "plt.ylabel('number of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fbab752f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cf778b22e0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "style.use('ggplot')\n",
    "plt.figure(figsize=(10,7))\n",
    "plt.hist(age_men, bins=10, color='blue',\n",
    "         histtype='step', rwidth=0.8, label='Men')\n",
    "plt.hist(age_women, bins=10, color='orange',\n",
    "         histtype='step', rwidth=0.8, label = 'Women')\n",
    "plt.xlabel('Age of people')\n",
    "plt.ylabel('No. of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1c6d5476",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Age vs number of people')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "style.use('ggplot')\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.subplot(1,2,1)\n",
    "plt.hist(age_men, bins=10, color='blue',\n",
    "         histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of men')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.subplot(1,2,2)\n",
    "plt.hist(age_women, bins=10, color='blue',\n",
    "         histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of women')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5b682786",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Age vs number of people')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(2,2,1)\n",
    "plt.hist(age_men, bins=10, color='blue', histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of men')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.subplot(2,2,4)\n",
    "plt.hist(age_women, bins=10, color='blue', histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of women')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b150a689",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "os.chdir(r'D:\\visualizations\\histogram')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "af2d1f7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mens_age</th>\n",
       "      <th>Womens_age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>43</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Mens_age  Womens_age\n",
       "0        13          32\n",
       "1        41          66\n",
       "2        22          49\n",
       "3        43          28\n",
       "4        26          17"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_data = pd.read_csv('age_csv.csv')\n",
    "age_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b4d85554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Age vs number of people')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.subplot(1,2,1)\n",
    "plt.hist(age_data.Mens_age, bins=10, color='blue', histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of men')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.subplot(1,2,2)\n",
    "plt.hist(age_data.Womens_age, bins=10, color='blue', histtype='bar', rwidth=0.8)\n",
    "plt.xlabel('age of women')\n",
    "plt.ylabel('No of people')\n",
    "plt.title('Age vs number of people')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5d222d35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1609d781c10>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "plt.hist(age_data.Mens_age, bins=10, color='blue',histtype='step', rwidth=0.8, label='Men')\n",
    "plt.hist(age_data.Womens_age, bins=10, color='orange',histtype='step', rwidth=0.8, label = 'Women')\n",
    "plt.xlabel('Age of people')\n",
    "plt.ylabel('No. of people')\n",
    "plt.title('Age vs number of people')\n",
    "plt.legend(loc='upper right')"
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}