Stem plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0e2a7cd2-db84-4fe7-801c-74699693d895",
   "metadata": {},
   "outputs": [],
   "source": [
    "# STEM PLOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e561bfe-18f7-420b-93c0-5378ae0362be",
   "metadata": {},
   "outputs": [],
   "source": [
    "# syntax\n",
    "x=[]\n",
    "y=[]\n",
    "plt.stem(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32f3a262-5c23-4577-9fcd-0ac653f74ba9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[1,2,3,4,5,6]\n",
    "y=[2,3,4,3,7,1]\n",
    "plt.stem(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6344a86f-8c4f-4305-8953-7c560d15db3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lineformat\n",
    "\"-\" - solid line\n",
    "\"--\"-dashed line\n",
    "\"-.\":dash-dot line\n",
    "\":\"-Dotted line\n",
    "# markerfmt=\"g*\": Sets green circles ('g*') as markers for data points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6a7c7c03-f73a-4921-9fa8-1531beb9cd79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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U1/X19W15SiAj9J/TPzW2dOx/wPsP79fwBcNT9zuzuFwPHUunrLB+98Ov+F0GDEl7xqKyslKbN29WRUVFqx5fUVGhgoKC1C0Wi6VdJJApll69VJHQsX7/+PX+x/+MhCJaevVS32oDgNZIq7GoqanR9OnT9eSTT6pTp06t+p6ZM2eqrq4udaupqWlToUAmKCsp08ZbNp707zbeslFlJWWGKwKA9KR1KqS6ulr79u3TsGHDUvclk0mtX79ejz76qOLxuMLhEzc/iUajikaj7lQLZBRLkqOQQrLFgjd0XI3NSX17/muSpN98f7Q6ZbFJVpCl1Vhcfvnl2rJlywn33XTTTRowYIB+/OMff66pAJC+wtxC9crtpc8a8tUlMV79izeqtuEjFeYW+l0a0Ca24+jtj+pSYwRbWo1FXl6eBg8efMJ9ubm56t69++fuB9A2RflFeu+2D7Th/TpZlqVLzukhWwlFI8z8oWPKDof0/24ckRoj2NjSG2iHcqM5uvyCnL+7h9lAdFyRcEjjBvTyuwwYctqNxdq1a10oAwAABAEzFkA7lLQdvfreAUnSV77UQ+EQmwqh4+J4ziw0FkA7FE8kdcN/vi5J2n7/BHXO5p8qOi6O58zCqwu0QyHL0gV98lNjoCPjeM4sluOYvfanvr5eBQUFqqurU35+vsmnBgAAbdTa92+u+wEAAK6hsQAAAK6hsQDaocbmpK6b/5qum/+aGpuTfpcDnBaO58zC4k2gHbIdRxs/+FtqDHRkHM+ZhcYCaIeywyHN/YdhqTHQkXE8ZxYaC6AdioRDmljSx+8yAFdwPGcWWkcAAOAaZiyAdihpO3pj92eSpKH9zmALZHRoHM+ZhRkLoB2KJ5L61q9e07d+9ZriCVbRo2PjeM4szFgA7ZAlS/27d06NgY6M4zmzsKU3AABoEVt6AwAA42gsAACAa2gsgHaosTmpmxa9rpsWvc4WyOjwOJ4zC4s3gXbIdhyteWd/agx0ZBzPmYXGAmiHssIh/eJbJakx0JFxPGcWrgoBAAAt4qoQAABgHKdCgHYoaTv66956SdKA3vlsgYwOjeM5szBjAbRD8URSE3/5sib+8mW2QEaHx/GcWZixANohS5Z65UdTY6Aj43jOLCzeBAAALWLxJgAAMI7GAgAAuIbGAmiHGpuT+tGT1frRk9VsgYwOj+M5s9BYAO2Q7Tj6w5a9+sOWvWyBjA6P4zmzcFUI0A5lhUO6/6pBqTHQkXE8ZxauCgEAAC3iqhAAAGAcp0KAdsi2He362xFJUnG3zgqxBTI6MI7nzEJjAbRDjYmkxv7rWknS9vsnqHM2/1TRcXE8ZxZeXaCdyuvEP08EB8dz5mDxJgAAaJEnizfnzZunkpIS5efnKz8/X6NHj9bKlStPu1h0HFW1VRr3+DhV1Vb5XQrgCo5pwF1pNRZFRUWaPXu2qqurVVVVpXHjxumqq67Stm3bvKoP7cwTbz2hNR+u0ZK3lvhdCuAKjmnAXad9KqRbt276xS9+oWnTprXq8ZwK6Xh2HdylA0cOyLIslT5Zqn2H96kwt1Ary1bKcRz16NxDxV2L/S4zUOKJpO75/VZJ0kPfHKxoJOxzRcHCMW0Wx3MwtPb9u82raZLJpH7729/q8OHDGj169CkfF4/HFY/HTygMHUv/Of1TY0vHLhPbf3i/hi8YnrrfmcU2vW5K2o5+t/kjSdIDkwf5XE3wcEybxfGcWdLeIGvLli3q0qWLotGofvCDH2j58uUaOHDgKR9fUVGhgoKC1C0Wi51WwTBv6dVLFQkd60EdOSf8GQlFtPTqpb7VFlSRUEgzSwdoZukARULsY+c2jmmzOJ4zS9qnQpqamrR7927V1dXp6aef1mOPPaZ169adsrk42YxFLBbjVEgHs3nP5hN+mzuu+h+rNazPMB8qAk4PxzSQHs9OhWRnZ+ucc86RJA0fPlybNm3SnDlzNH/+/JM+PhqNKhqNpvs0aKdCCsmWnfoT6Og4pgF3nfaOJbZtnzAjgWAqzC1Ur9ze6t3lTP3DoBv12788ro8aPlJhbqHfpQWSbTva13Ds31VhXpQtkD3AMW0Ox3NmSauxmDlzpkpLS9WvXz81NDRo2bJlWrt2rVatWuVVfWgnivKL9Jcf7dRF96/R//3Q0rafvKpI2FY0wmyUFxoTSX254iVJbIHsFY5pczieM0tar+6+ffv03e9+V3v27FFBQYFKSkq0atUqff3rX/eqPrQj0UhUWf+98MqyLP4H7LEIv9V5jmPaHI7nzMGW3gAAoEWebOkNAADwRWgsAACAa1hBg1aLJ5J68Pm/SJL++coL2JbXQ2RtBjmbQc6ZhRkLtFrSdrRkwy4t2bBLSZvtjr1E1maQsxnknFmYsUCrRUIhTb/83NQY3iFrM8jZDHLOLFwVAgAAWsRVIQAAwDhOhaDVHMdRfWNCkpTfKSLLYsMbr5C1GeRsBjlnFhoLtNrR5qSG/OSPktiW12tkbQY5m0HOmYVTIQAAwDUs3kSrOY6jxH9fKhYJWUxneoiszSBnM8g5GFr7/s18FFrNsixlhfkfgglkbQY5m0HOmYVTIQAAwDXMWKDVmhK2/vWP70iS7hp/vrIj9KVeIWszyNkMcs4svLpotYRta8H697Vg/ftK2Lbf5QQaWZtBzmaQc2ZhxgKtFgmF9I+Xnp0awztkbQY5m0HOmYWrQgAAQIvY0hsAABjHqRC0Gteim0PWZpCzGeScWZixQKsdbU7q3H9aqXP/aaWONif9LifQyNoMcjaDnDMLjQUAAHANizfRanxCoTlkbQY5m0HOwcCW3nCdZVkqyMnyu4yMQNZmkLMZ5JxZOBUCAABcw4wFWq0pYWvump2SpPKx57Atr4fI2gxyNoOcMwuNBVotYdua89IOSdL3Lztb2Ux4eYaszSBnM8g5s9BYoNXCIUs3fLk4NYZ3yNoMcjaDnDMLV4UAAIAWsaU3AAAwjsYCAAC4hsYCrXakKaFz7vmDzrnnDzrSlPC7nEAjazPI2Qxyziws3kRajn+QELxH1maQsxnknDlYvIlWs21H+xrikqTCvKhCrO72DFmbQc5mkHMwsKU3XBcKWepd0MnvMjICWZtBzmaQc2ZhjQUAAHANMxZotaaErUWvfCBJumnMWWzL6yGyNoOczSDnzEJjgVZL2LYqVv5VknTD6GK25fUQWZtBzmaQc2ZJ69WtqKjQyJEjlZeXp8LCQk2ePFnvvPOOV7Wlpaq2SuMeH6eq2iq/SwmscMjSNcOKdM2wIrbl9RhZm0HOZpBzZknrqpBvfOMb+s53vqORI0cqkUjonnvu0datW7V9+3bl5ua26md4dVXI7Stv13+8/h+6/eLbNad0jms/FwAAtP79+7QuN92/f78KCwu1bt06XXrppa4W1hq7Du7SgSMHZFmWSp8s1b7D+1SYW6iVZSvlOI56dO6h4q7Fp/UcAADA0OWmdXV1kqRu3bqd8jHxeFzxePyEwtzSf07/1NjSsem1/Yf3a/iC4an7nVlsygIAgCltXkFj27buuOMOjRkzRoMHDz7l4yoqKlRQUJC6xWKxtj7l5yy9eqkioWO9kSPnhD8joYiWXr3UtefCsW15L7xvlS68bxXb8nqMrM0gZzPIObO0ubEoLy/X1q1bVVlZ+YWPmzlzpurq6lK3mpqatj7l55SVlGnjLRtP+ncbb9mospIy154LxzQ0JtTQyP8YTCBrM8jZDHLOHG06FXLrrbfq+eef1/r161VUVPSFj41Go4pGo20qLh2WQnJkK6SQbNmeP18m6hQJa81dX0uN4R2yNoOczSDnzJJWY+E4jm677TYtX75ca9eu1VlnneVVXa1WmFuo3l16K5Yf07Sh0/Sfb/ynauprVJhb6HdpgRMKWTqrR+uu/sHpIWszyNkMcs4saV0V8qMf/UjLli3TihUrdP7556fuLygoUE5OTqt+hheXm8YTcWWHs2VZlhzHUVOySdGI97MkAABkCk8uN7Wsk29ssmjRIt14442uFpaO5qStX7++W5I05eJ+ygqzq5sXyNkcsjaDnM0g52Dw5HJTw5+w3mrNSVv3rtgmSfrW8CIOWo+QszlkbQY5m0HOmSUQnxUSsiz9rwt7p8bwBjmbQ9ZmkLMZ5JxZTmvnzbbwaktvAADgnda+fzMfBQAAXENjAQAAXBOIxuJoU1KjHnpRox56UUebkn6XE1jkbA5Zm0HOZpBzZgnE4k1Hjj6pj6fG8AY5m0PWZpCzGeScWQKxeDNpO/rr3mOfmjqgd77CIVYde4GczSFrM8jZDHIOBk82yHIDV4UAANDxcFUIAAAwLhBrLJqTtp5542NJ0uShZ7Krm0fI2RyyNoOczSDnzBKYxuJ/P/22JGliSR8OWo+QszlkbQY5m0HOmSUQjUXIsjT2/J6pMbxBzuaQtRnkbAY5ZxYWbwIAgBaxeBMAABhHYwEAAFwTiMbiaFNSX/vFGn3tF2vYLtZD5GwOWZtBzmaQc2YJxOJNR44+/PRIagxvkLM5ZG0GOZtBzpklEI1FNBLW0z8YnRrDG+RsDlmbQc5mkHNm4aoQAADQIq4KAQAAxgXiVEgiaWvVtk8kSRMG9VKEXd08Qc7mkLUZ5GwGOWeWQDQWTUlb5cs2S5K23z+Bg9Yj5GwOWZtBzmaQc2YJRGMRsiyNOqtbagxvkLM5ZG0GOZtBzpmFxZsAAKBFLN4EAADG0VgAAADXBKKxaGxOqnTOn1U6589qbGa7WK+QszlkbQY5m0HOmSUQizdtx9Ff9tSnxvAGOZtD1maQsxnknFkC0VhEI2EtmXZxagxvkLM5ZG0GOZtBzpmFq0IAAECLuCoEAAAYF4hTIYmkrfU79kuSLj23J7u6eYSczSFrM8jZDHLOLIFoLJqStm5eXCWJ7WK9RM7mkLUZ5GwGOWeWQDQWIctSSVFBagxvkLM5ZG0GOZtBzpmFxZsAAKBFLN4EAADG0VgAAADXpN1YrF+/XpMmTVLfvn1lWZaeeeYZD8pKT2NzUtfMe1XXzHuV7WI9RM7mkLUZ5GwGOZtTVVulcY+PU1VtlW81pL148/DhwxoyZIhuvvlmffOb3/SiprTZjqPqXZ+lxvAGOZtD1maQsxnkbM4Tbz2hNR+u0ZK3lmhE3xG+1JB2Y1FaWqrS0lIvammz7HBI828YnhrDG+RsDlmbQc5mkLO3dh3cpQNHDsiyLD217SlJUuW2Sk29aKocx1GPzj1U3LXYWD2ndVWIZVlavny5Jk+efMrHxONxxePx1Nf19fWKxWJcFQIAgAusn/zPJbyWLDlyUn8e58w6/ZmidnNVSEVFhQoKClK3WCzm9VMCAJAxll69VJHQsRMQx5uJ439GQhEtvXqp0Xo8byxmzpypurq61K2mpsb150jajl5771O99t6nStqcv/MKOZtD1maQsxnk7K2ykjJtvGXjSf9u4y0bVVZSZrQez3fejEajikajnj5HPJHUlIUbJB3bLrZzdiA2FG13yNkcsjaDnM0gZ4McS7IchRSSLduXEgLx6lqydG5hl9QY3iBnc8jaDHI2g5y9V5hbqF65vXTkaFedmTVRud3W6+OGj1SYW2i8lrQXbx46dEg7d+6UJA0dOlQPP/ywxo4dq27duqlfv34tfj9begMA4L54Iq7scLYsy5LjOGpKNikace+MQWvfv9OesaiqqtLYsWNTX8+YMUOSNHXqVC1evDj9SgEAwGn7+ybCsixXm4p0pN1YfO1rX5Phzy0DAAAdRCB2KmlsTur6xzbq+sc2sl2sh8jZHLI2g5zNIGcz2kvOgVi8aTuOXt55IDWGN8jZHLI2g5zNIGcz2kvOgWgsssMhPXLdRakxvEHO5pC1GeRsBjmb0V5yPq0tvduCq0IAAOh42s2W3gAAIHME4lRI0na09eM6SdLgMwsUDrEBixfI2RyyNoOczSBnM9pLzoGYsYgnkrpq7iu6au4riidYcewVcjaHrM0gZzPI2Yz2knMgZiwsWTqza05qDG+QszlkbQY5m0HOZrSXnFm8CQAAWsTiTQAAYByNBQAAcE0gGovG5qS+90SVvvdEFdvFeoiczSFrM8jZDHI2o73kHIjFm7bjaPX2T1JjeIOczSFrM8jZDHI2o73kHIjGIiscUsU3L0yN4Q1yNoeszSBnM8jZjPaSM1eFAACAFnFVCAAAMC4Qp0Js29HO/YckSef07KIQ28V6gpzNIWszyNkMcjajveQciMaiMZHU+H9fL0nafv8Edc4OxH9Wu0PO5pC1GeRsBjmb0V5yDsyr2y032+8SMgI5m0PWZpCzGeRsRnvImcWbAACgRSzeBAAAxtFYAAAA1wSisWhsTmp65RuaXvkG28V6iJzNIWszyNkMcjajveQciMbCdhyteLNWK96sZbtYD5GzOWRtBjmbQc5mtJecA3FVSFY4pH+5cmBqDG+QszlkbQY5m0HOZrSXnLkqBAAAtIirQgAAgHGBOBVi244+PnhUknRm1xy2i/UIOZtD1maQsxnkbEZ7yTkQMxaNiaQu+fkaXfLzNWpMsOLYK+RsDlmbQc5mkLMZ7SXnQMxYSFJOVtjvEjICOZtD1maQsxnkbEZ7yJnFmwAAoEUs3gQAAMbRWAAAANcEorGIJ5K6+3dv6+7fva04C4M8Q87mkLUZ5GwGOZvRXnIORGORtB1VbqpR5aYaJW22i/UKOZtD1maQsxnkbEZ7yTkQV4VEQiHdNf681BjeIGdzyNoMcjaDnM1oLzlzVQgAAGiRp1eFzJ07V/3791enTp00atQovf76620uFAAABEfajcVTTz2lGTNmaNasWdq8ebOGDBmiCRMmaN++fV7U1yqO4+jTQ3F9eiguwxMwGYWczSFrM8jZDHI2o73knPapkFGjRmnkyJF69NFHJUm2bSsWi+m2227T3Xff3eL3e3Eq5HC8WcP+6TlJUvU/X6HO2YFYOtLuHGlKaPiDL0oiZ6+RtRnkbAY5m/H3OW/+6STlRrNc/fmtff9Oq7FoampS586d9fTTT2vy5Mmp+6dOnaqDBw9qxYoVn/ueeDyueDx+QmGxWMzVxuLQwXrVfHmUKz8LAICOLrZho7p0dXcdoydrLA4cOKBkMqlevXqdcH+vXr20d+/ek35PRUWFCgoKUrdYLJbOU7YK3S8AAP/Dz/dFz5955syZmjFjRurr4zMWbrJycnT+5mpXfyYAAB2VlZPj23On1Vj06NFD4XBYn3zyyQn3f/LJJ+rdu/dJvycajSoajba9wlawLEtW586ePgcAAGhZWqdCsrOzNXz4cL300kup+2zb1ksvvaTRo0e7XhwAAOhY0j4VMmPGDE2dOlUjRozQxRdfrEceeUSHDx/WTTfd5EV9AACgA0m7sbjuuuu0f/9+3Xvvvdq7d68uuugivfDCC59b0AkAADIPW3oDAIAWebqlNwAAwMnQWAAAANfQWAAAANfQWAAAANfQWAAAANfQWAAAANfQWAAAANfQWAAAANfQWAAAANcY/8D24xt91tfXm35qAADQRsfft1vasNt4Y9HQ0CBJisVipp8aAACcpoaGBhUUFJzy741/Voht26qtrVVeXp4sy3Lt59bX1ysWi6mmpobPIPEQOZtD1maQsxnkbIaXOTuOo4aGBvXt21eh0KlXUhifsQiFQioqKvLs5+fn53PQGkDO5pC1GeRsBjmb4VXOXzRTcRyLNwEAgGtoLAAAgGsC01hEo1HNmjVL0WjU71ICjZzNIWszyNkMcjajPeRsfPEmAAAIrsDMWAAAAP/RWAAAANfQWAAAANfQWAAAANd0+MZi/fr1mjRpkvr27SvLsvTMM8/4XVIgVVRUaOTIkcrLy1NhYaEmT56sd955x++yAmfevHkqKSlJbW4zevRorVy50u+yAm/27NmyLEt33HGH36UEzn333SfLsk64DRgwwO+yAunjjz/W9ddfr+7duysnJ0cXXnihqqqqjNfR4RuLw4cPa8iQIZo7d67fpQTaunXrVF5erg0bNmj16tVqbm7W+PHjdfjwYb9LC5SioiLNnj1b1dXVqqqq0rhx43TVVVdp27ZtfpcWWJs2bdL8+fNVUlLidymBNWjQIO3Zsyd1e/nll/0uKXA+++wzjRkzRllZWVq5cqW2b9+uf/u3f9MZZ5xhvBbjW3q7rbS0VKWlpX6XEXgvvPDCCV8vXrxYhYWFqq6u1qWXXupTVcEzadKkE77+6U9/qnnz5mnDhg0aNGiQT1UF16FDh1RWVqaFCxfqwQcf9LucwIpEIurdu7ffZQTaz372M8ViMS1atCh131lnneVLLR1+xgL+qKurkyR169bN50qCK5lMqrKyUocPH9bo0aP9LieQysvLNXHiRF1xxRV+lxJoO3bsUN++fXX22WerrKxMu3fv9rukwHn22Wc1YsQIXXvttSosLNTQoUO1cOFCX2rp8DMWMM+2bd1xxx0aM2aMBg8e7Hc5gbNlyxaNHj1ajY2N6tKli5YvX66BAwf6XVbgVFZWavPmzdq0aZPfpQTaqFGjtHjxYp1//vnas2ePfvKTn+iSSy7R1q1blZeX53d5gfH+++9r3rx5mjFjhu655x5t2rRJt99+u7KzszV16lSjtdBYIG3l5eXaunUr50k9cv755+vNN99UXV2dnn76aU2dOlXr1q2juXBRTU2Npk+frtWrV6tTp05+lxNof3+quqSkRKNGjVJxcbF+85vfaNq0aT5WFiy2bWvEiBF66KGHJElDhw7V1q1b9atf/cp4Y8GpEKTl1ltv1fPPP681a9aoqKjI73ICKTs7W+ecc46GDx+uiooKDRkyRHPmzPG7rECprq7Wvn37NGzYMEUiEUUiEa1bt06//OUvFYlElEwm/S4xsLp27arzzjtPO3fu9LuUQOnTp8/nfvm44IILfDntxIwFWsVxHN12221avny51q5d69uioExk27bi8bjfZQTK5Zdfri1btpxw30033aQBAwboxz/+scLhsE+VBd+hQ4f03nvv6YYbbvC7lEAZM2bM57YAePfdd1VcXGy8lg7fWBw6dOiEzveDDz7Qm2++qW7duqlfv34+VhYs5eXlWrZsmVasWKG8vDzt3btXklRQUKCcnByfqwuOmTNnqrS0VP369VNDQ4OWLVumtWvXatWqVX6XFih5eXmfWx+Um5ur7t27s27IZXfddZcmTZqk4uJi1dbWatasWQqHw5oyZYrfpQXKnXfeqa985St66KGH9O1vf1uvv/66FixYoAULFpgvxung1qxZ40j63G3q1Kl+lxYoJ8tYkrNo0SK/SwuUm2++2SkuLnays7Odnj17Opdffrnzxz/+0e+yMsJll13mTJ8+3e8yAue6665z+vTp42RnZztnnnmmc9111zk7d+70u6xAeu6555zBgwc70WjUGTBggLNgwQJf6uBj0wEAgGtYvAkAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFxDYwEAAFzz/wGhINAN3jssaAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[1,2,3,4,5,6]\n",
    "y=[2,3,4,3,7,1]\n",
    "plt.stem(x,y,linefmt=\":\",markerfmt=\"g*\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5836fcf6-dbc2-4882-adf0-92689eaeddd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bottom=5: Specifies the baseline of the stem plot as 5.\n",
    "# basefmt=\"black\": Sets the color of the baseline to black.\n",
    "# orientation='horizontal': Renders the stem plot horizontally.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5d998876-7d53-4d74-b3f2-256a0b7c3fca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[1,2,3,4,5,6]\n",
    "y=[2,3,4,3,7,1]\n",
    "plt.stem(x,y,linefmt=\":\",markerfmt=\"go\",bottom=5,basefmt=\"black\",label=\"python\",orientation='horizontal')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6df5d4e6-071c-4492-873b-9d9a722a137e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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