s1rat-dev/Matplotlip Grafik Türleri.ipynb

## Matplotlip Grafik Türleri.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "active-repository",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "numpyDizisi = np.linspace(0,10,10)\n",
    "numpyDizisi2 = np.linspace(0,10,10) ** 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afraid-portugal",
   "metadata": {},
   "source": [
    "## scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "downtown-blackberry",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2ab4a89da60>"
      ]
     },
     "execution_count": 18,
     "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.scatter(numpyDizisi,numpyDizisi2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "derived-buyer",
   "metadata": {},
   "source": [
    "## histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "warming-farming",
   "metadata": {},
   "outputs": [],
   "source": [
    "yeniDizi = np.random.randint(0,100,50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "derived-hindu",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([16, 15,  2, 45, 15, 98, 18, 68, 49, 39, 63, 70, 41, 33, 67, 77, 44,\n",
       "       33,  9, 57, 24, 69, 35, 11, 50, 21, 68, 22, 13, 92, 88, 19, 17,  9,\n",
       "       61, 86, 33, 61, 23, 77, 72, 91, 14, 75, 86, 86, 27, 56, 10, 89])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yeniDizi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "european-camcorder",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWsAAAEWCAYAAACg+rZnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAN9klEQVR4nO3dfYxlB1nH8e/PLm9tSVvshNht6ZQUwYKhbTZarEFSqmlZQo3BUGKVKriaqLRIJIuaoH8oRQkvJlrdtCBq0xKWqqRNiqW0UQxUdwtC2wV5W9tiSwehhfIHpfj4xz3rToednbu7c+/tM/f7SSYzZ+7Zuc+ZM/vNmTP33JuqQpL0xPYDsx5AkrQ2Yy1JDRhrSWrAWEtSA8Zakhow1pLUgLHWhpXkriQvOcjttyV53fQmkg7fplkPIB2uJI8sWzwa+A7wvWH516rq+cvW/QPg9Kq6ZHoTSuvHWKutqjp238dJ9gKvq6qPzG4iaXI8DaINK8neJOcnuQD4XeBVSR5J8h+rrP8rSfYk+UaSDyc5dboTS6sz1trwquom4I+B91fVsVX1wpXrJLmIUdB/DlgA/gW4dqqDSgdhrKWRXwfeWlV7quoxRnE/06NrPVEYa2nkVODdSR5K8hDwdSDA5plOJQ38A6PmxVpPL3kv8EdVdc00hpEOlUfWmhdfBRaTrPYz/5fAm5M8HyDJcUl+fmrTSWsw1poXHxje/0+SO1beWFV/D7wNuC7JN4E7gQunOJ90UPHFByTpic8ja0lqwFhLUgPGWpIaMNaS1MBEHmd94okn1uLi4iS+tCRtSLt37/5aVS2sdvtEYr24uMiuXbsm8aUlaUNK8l8Hu93TIJLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjDWktSAL+s1WNx+48zue+8VW2d235J68Mhakhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjDWktSAsZakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGxop1kjckuSvJnUmuTfLUSQ8mSdpvzVgn2Qy8HthSVS8AjgIunvRgkqT9xj0Nsgl4WpJNwNHAf09uJEnSSmvGuqq+ArwduAe4H3i4qv5p5XpJtiXZlWTX0tLS+k8qSXNsnNMgJwAXAacBJwHHJLlk5XpVtaOqtlTVloWFhfWfVJLm2DinQc4HvlxVS1X1XeB64CcmO5YkablxYn0PcE6So5MEeCmwZ7JjSZKWG+ec9e3ATuAO4DPDv9kx4bkkSctsGmelqnoL8JYJzyJJWoVXMEpSA8Zakhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjDWktSAsZakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgNjvVKMpCOzuP3Gmd333iu2zuy+tX48spakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ1YKwlqYGxYp3k+CQ7k3w2yZ4kL5r0YJKk/cZ9wdx3AzdV1SuTPBk4eoIzSZJWWDPWSY4DXgxcClBVjwKPTnYsSdJy45wGOQ1YAt6b5JNJrkpyzMqVkmxLsivJrqWlpXUfVJLm2Tix3gScDVxZVWcB3wa2r1ypqnZU1Zaq2rKwsLDOY0rSfBsn1vcB91XV7cPyTkbxliRNyZqxrqoHgHuTPHf41EuBuyc6lSTpccZ9NMhvAdcMjwT5EvDLkxtJkrTSWLGuqk8BWyY7iiRpNV7BKEkNGGtJasBYS1IDxlqSGjDWktSAsZakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDYz7sl5Ts7j9xlmPMDdm+b3ee8XWmd33vJnVfnYfry+PrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJamDsWCc5Ksknk9wwyYEkSd/vUI6sLwP2TGoQSdLqxop1kpOBrcBVkx1HknQgm8Zc713Am4Cnr7ZCkm3ANoBnPetZRzzYPFncfuOsR5i6WW3z3iu2zuR+59E8/lxP8udrzSPrJC8HHqyq3Qdbr6p2VNWWqtqysLCwbgNKksY7DXIu8Ioke4HrgPOS/N1Ep5IkPc6asa6qN1fVyVW1CFwMfLSqLpn4ZJKk/+fjrCWpgXH/wAhAVd0G3DaRSSRJq/LIWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjikV4qRulvcfuOsR5AOi0fWktSAsZakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ1sGask5yS5NYkdye5K8ll0xhMkrTfOC+Y+xjwxqq6I8nTgd1Jbq6quyc8myRpsOaRdVXdX1V3DB9/C9gDbJ70YJKk/Q7pnHWSReAs4PYD3LYtya4ku5aWltZpPEkSHEKskxwLfBC4vKq+ufL2qtpRVVuqasvCwsJ6zihJc2+sWCd5EqNQX1NV1092JEnSSuM8GiTA1cCeqnrH5EeSJK00zpH1ucAvAucl+dTw9rIJzyVJWmbNh+5V1ceATGEWSdIqvIJRkhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjDWktSAsZakBoy1JDVgrCWpAWMtSQ0Ya0lqwFhLUgPGWpIaMNaS1ICxlqQGjLUkNWCsJakBYy1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ1YKwlqQFjLUkNGGtJasBYS1IDxlqSGjDWktSAsZakBoy1JDVgrCWpgbFineSCJJ9L8oUk2yc9lCTp8daMdZKjgD8HLgTOAF6d5IxJDyZJ2m+cI+sfA75QVV+qqkeB64CLJjuWJGm5TWOssxm4d9nyfcCPr1wpyTZg27D4SJLPHeRrngh8bdwhN6B53v553naY7+3f8Nuet6160zjbfurBbhwn1mOpqh3AjnHWTbKrqras1313M8/bP8/bDvO9/W77kW37OKdBvgKcsmz55OFzkqQpGSfW/w48J8lpSZ4MXAx8aLJjSZKWW/M0SFU9luQ3gQ8DRwHvqaq7jvB+xzpdsoHN8/bP87bDfG+/234EUlXrMYgkaYK8glGSGjDWktTA1GM9T5euJzklya1J7k5yV5LLhs8/I8nNST4/vD9h1rNOSpKjknwyyQ3D8mlJbh/2//uHP1pvSEmOT7IzyWeT7EnyonnZ90neMPzM35nk2iRP3cj7Psl7kjyY5M5lnzvgvs7Inw3fh08nOXuc+5hqrOfw0vXHgDdW1RnAOcBvDNu7Hbilqp4D3DIsb1SXAXuWLb8NeGdVnQ58A3jtTKaajncDN1XV84AXMvo+bPh9n2Qz8HpgS1W9gNEDEy5mY+/7vwYuWPG51fb1hcBzhrdtwJXj3MG0j6zn6tL1qrq/qu4YPv4Wo/+smxlt8/uG1d4H/OxMBpywJCcDW4GrhuUA5wE7h1U28rYfB7wYuBqgqh6tqoeYk33P6JFmT0uyCTgauJ8NvO+r6p+Br6/49Gr7+iLgb2rkE8DxSX5orfuYdqwPdOn65inPMBNJFoGzgNuBZ1bV/cNNDwDPnNVcE/Yu4E3A/w7LPwg8VFWPDcsbef+fBiwB7x1OA12V5BjmYN9X1VeAtwP3MIr0w8Bu5mff77Pavj6sDvoHxilIcizwQeDyqvrm8ttq9NjJDff4ySQvBx6sqt2znmVGNgFnA1dW1VnAt1lxymMD7/sTGB09ngacBBzD958imCvrsa+nHeu5u3Q9yZMYhfqaqrp++PRX9/3aM7x/cFbzTdC5wCuS7GV0uus8Rudwjx9+NYaNvf/vA+6rqtuH5Z2M4j0P+/584MtVtVRV3wWuZ/TzMC/7fp/V9vVhdXDasZ6rS9eHc7RXA3uq6h3LbvoQ8Jrh49cA/zjt2Satqt5cVSdX1SKj/fzRqvoF4FbglcNqG3LbAarqAeDeJM8dPvVS4G7mYN8zOv1xTpKjh/8D+7Z9Lvb9Mqvt6w8BvzQ8KuQc4OFlp0tWV1VTfQNeBvwn8EXg96Z9/1Pe1p9k9KvPp4FPDW8vY3Tu9hbg88BHgGfMetYJfx9eAtwwfPxs4N+ALwAfAJ4y6/kmuN1nAruG/f8PwAnzsu+BPwQ+C9wJ/C3wlI2874FrGZ2f/y6j36peu9q+BsLoUXFfBD7D6FEza96Hl5tLUgP+gVGSGjDWktSAsZakBoy1JDVgrCWpAWOtloZnNPxykmcMyycMy4sHWPeR4f1JSXauvF3qwIfuqa0kbwJOr6ptSf4K2FtVbz3Aeo9U1bHTn1BaPx5Zq7N3MrpS7nJGFyC9/WArJ1nc93zDSS5Ncn2Sm4bnG/6TZev9TJKPJ7kjyQeG53aRZspYq60aPe/E7zCK9uXD8qE4E3gV8KPAq4ZTKycCvw+cX1VnM7oC8bfXb2rp8Kz56ubSE9yFjC7zfQFw8yH+21uq6mGAJHcDpwLHM3phjH8dPa0FTwY+vl7DSofLWKutJGcCP83oVXg+luS6GucJcfb7zrKPv8fo/0OAm6vq1es2qLQOPA2iloZnc7uS0emPe4A/ZY1z1mP6BHBuktOH+zkmyQ+vw9eVjoixVle/CtxTVftOffwF8CNJfupIvmhVLQGXAtcm+TSjUyDPO5KvKa0HH7onSQ14ZC1JDRhrSWrAWEtSA8Zakhow1pLUgLGWpAaMtSQ18H8XKc1IFaslPwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(yeniDizi)\n",
    "plt.xlabel('X line')\n",
    "plt.title('Title')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "massive-wonder",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgIAAAFZCAYAAADq5EdlAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAV9ElEQVR4nO3dfbRsZX0f8O8PrlyjcC+6ErmxaDCI2KoRgSiahKCEakqqWGPwpSnY1Vis1hLbKGgTjKQFTWuokVhNoyEpiU2XKcZQAiWVZRRKFMVAjFZTrkJ4FQWuCJcIT//Yc8IwORfOPWf2eeH5fNbaa87seWbv5zfPzDnfs19mV2stAECf9ljrDgAAa0cQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB3btNYdmFVVleTxSXasdV8AYAPaJ8n1bYlfFLTugkCGEHDdWncCADaw/ZP81VIarscgsCNJrr322mzZsmWt+wIAG8Ydd9yRJzzhCclubFVfj0EgSbJlyxZBAABG5mBBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMd2OwhU1ZFV9bGqur6qWlUdN/N4VdU7quqGqrqrqi6uqoPm1mMAYG6Ws0Xg0Uk+n+T1u3j8zUnemOSkJM9JcmeSC6vqkcvqIQAwmt3+iuHW2gVJLkiS4UKB95tcOfDkJL/UWvvoZN4/SXJTkuOSfHhFvQUA5mrexwg8Kcm2JBcvzGit3Z7k8iTPXewJVbW5qrYsTBkunwgArIJ5X3Ro2+T2ppn5N009NuvUJKfNuR/AKjvglPOX3Hb7mceO2BNgd6yHswbOSLJ1atp/bbsDAP2Y9xaBGye3+yW5YWr+fkmuXOwJrbWdSXYu3J897gAAGM+8twhckyEMHL0wY7Lf/zlJLpvzugCAFdrtLQJVtXeSJ0/NelJVHZLkG621r1XVWUn+bVV9OUMwOD3J9UnOW3FvAYC5Ws6ugcOTfHzq/rsnt+ckOTHJuzJ818AHkuyb5JNJXtRau3vZvQQARrGc7xG4JMkud+S31lqSX5hMAMA6th7OGgAA1oggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANCxuQeBqtqzqk6vqmuq6q6q+suq+vmqqnmvCwBYmU0jLPMtSV6X5IQkf57k8CQfSnJ7kveMsD4AYJnGCALPS/LR1tr5k/vbq+qVSZ49wroAgBUY4xiBS5McXVVPSZKqemaSH05ywWKNq2pzVW1ZmJLsM0KfAIBFjLFF4MwkW5J8saruTbJnkre11s7dRftTk5w2Qj8AgIcwxhaBn0ry6iSvSnJohmMF/k1VnbCL9mck2To17T9CnwCARYyxReCXk5zZWvvw5P5VVfV9Gf7zP2e2cWttZ5KdC/edXAAAq2eMLQKPSnLfzLx7R1oXALACY2wR+FiSt1XV1zKcPvisJG9K8sER1gUArMAYQeBfJjk9ya8leVyS65O8P8k7RlgXALACcw8CrbUdSU6eTADAOma/PQB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdGyUIVNXfqar/WlW3VtVdVXVVVR0+xroAgOXbNO8FVtVjknwqyceT/HiSW5IclOSb814XALAycw8CSd6S5NrW2mum5l0zwnoAgBUaY9fAi5N8pqr+e1XdXFWfq6qf2VXjqtpcVVsWpiT7jNAnAGARYwSB70/yuiRfTvLCJO9L8p6qOmEX7U9NcvvUdN0IfQIAFjFGENgjyWdba29trX2utfaBJL+e5KRdtD8jydapaf8R+gQALGKMYwRuSPKFmXl/keRlizVure1MsnPhflWN0CUAYDFjbBH4VJKDZ+Y9JclXR1gXALACYwSBX0lyRFW9taqeXFWvSvLaJGePsC4AYAXmHgRaa59O8tIkr0xydZKfT3Jya+3cea8LAFiZMY4RSGvtD5P84RjLBgDmx7UGAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAx0YPAlV1SlW1qjpr7HUBALtn1CBQVT+Y5J8n+bMx1wMALM9oQaCq9k5ybpKfSfLNsdYDACzfmFsEzk5yfmvt4gdrVFWbq2rLwpRknxH7BABM2TTGQqvqFUkOTfKDS2h+apLTxugHsLgDTjl/Se22n3nsyD15aEvta7I++ts747XxzH2LQFU9Icl/SvLq1trdS3jKGUm2Tk37z7tPAMDixtgicFiSxyX5bFUtzNszyZFV9YYkm1tr9y480FrbmWTnwv2p5wAAIxsjCPxxkmfMzPtQki8meed0CAAA1tbcg0BrbUeSq6fnVdWdSW5trV29+LMAgLXgmwUBoGOjnDUwq7V21GqsBwDYPbYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRMEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANCxuQeBqjq1qj5dVTuq6uaqOq+qDp73egCAlRtji8CPJjk7yRFJjknyiCQXVdWjR1gXALACm+a9wNbai6bvV9WJSW5OcliST8x7fQDA8s09CCxi6+T2G4s9WFWbk2yemrXP6D0CAJKMHASqao8kZyX5VGvt6l00OzXJaWP2AzaqA045f8ltt5957Ig9gYenMT5jG+1zO/ZZA2cneXqSVzxImzMybDVYmPYfuU8AwMRoWwSq6r1JfiLJka2163bVrrW2M8nOqeeN1SUAYMbcg0ANf8l/NclLkxzVWrtm3usAAOZjjC0CZyd5VZKXJNlRVdsm829vrd01wvoAgGUa4xiB12XY139JkhumpuNHWBcAsAJjfI+AnfwAsEG41gAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOjYprXuwEZ3wCnnL7nt9jOPHbEnwO5Y6mfX55aHO1sEAKBjggAAdEwQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANAxQQAAOiYIAEDHBAEA6JggAAAdEwQAoGOCAAB0TBAAgI4JAgDQMUEAADomCABAxwQBAOiYIAAAHRstCFTV66tqe1XdXVWXV9Wzx1oXALA8owSBqjo+ybuT/GKSQ5N8PsmFVfW4MdYHACzPppGW+6Ykv95a+1CSVNVJSY5N8k+TnDndsKo2J9k8NWufJLnjjjtG6tp83bfz20tuu1FqYv0Y6/211OWOscyNtlyf292z0X4njtHftXwNlrO8aq3NtRNVtVeSbyf5ydbaeVPzz0myb2vtJTPt357ktLl2AgD6tn9r7a+W0nCMLQLfnWTPJDfNzL8pyVMXaX9Ght0I0x6b5BvLXP8+Sa5Lsn+SHctcxnqkro3n4VqbujYWdW08K61tnyTXL7XxWLsGlqy1tjPJzpnZy95WUlULP+5ora39dqc5UdfG83CtTV0bi7o2njnUtlvPGeNgwa8nuTfJfjPz90ty4wjrAwCWae5BoLV2T5Irkhy9MK+q9pjcv2ze6wMAlm+sXQPvTnJOVX0myZ8mOTnJo5N8aKT1TduZ4bTF2d0NG526Np6Ha23q2ljUtfGsam1zP2vgbxZc9YYkP5dkW5Irk7yxtXb5KCsDAJZltCAAAKx/rjUAAB0TBACgY4IAAHRMEACAjq3LIFBVR1bVx6rq+qpqVXXczOP7VdVvTh7/dlX9UVUdNNNmW1X9dlXdWFV3VtVnq+plM20eW1XnVtUdVXVbVf1GVe39MKhr+2T509Mp67yuA6vqf1TVLZPx+L2q2m+mzaqO1yrXtmpjVlWnVtWnq2pHVd1cVedV1cEzbR5ZVWdX1a1V9a2q+sgifX5iVZ0/qfvmqvrlqto00+aoyXt0Z1V9papOHKOm1a5tUtfseLWq2rbO63pPVV0xGY8rd7GuH6iqP6nhEvLXVtWbx6hpNeuqqgN2MV5HrNe6quqZVfW7kzG4q6r+oqr+1SLrWvFnbF0GgQzfOfD5JK+ffaCqKsl5Sb4/yUuSPCvJV5NcXFWPnmr6W0kOTvLiJM9I8vtJfq+qnjXV5twkT0tyTJKfSHJkkg/MuZZpq1VXkvxCku+dmn51noXMWFFdk9uLkrQkL0jyQ0n2SvKxGr6MasFqj1eyerUlqzdmP5rk7CRHZHgtH5Hkopn32a8k+YdJXj5p//gM77UkSVXtmeT8DLU8L8kJSU5M8o6pNk+atPl4kkOSnJXkv1TVC0eparAqtU05OA8cs5vnWs39VlzXlA8m+W+LraSqtmR4v341yWEZTgF/e1W9dj5l/C2rUteUH8sDx+uKlXT+QcyjrsMyvJ/+cYbfe/8uyRk1nJqfZI6fsdbaup4y/AI9bur+UybznjY1b4/JC/bPpuZ9K8lPzyzr1oU2Sf7uZDmHTz3+oiT3JXn8Rq1rcn97kpM3yngl+fsZvpZ6y1SbrZOx+LH1MF5j1rYOxux7JnUcOdW/ezJcQXShzVMnbY6Y3P/xSV37TbU5KcntSfaa3H9nkqtn1vXhJH/0MKjtqMlz9t0oYzbz/LcnuXKR+a/LcMG3vabmnZnkixu8rgMmzzlkI47XVJuzk/zvqftz+Yyt1y0CD2bz5PbuhRmttfsyfAPTD0+1uzTJ8TVsTt6jql6R5JFJLpk8/twkt7XWPjP1nIsz/IJ+zkh9fzDzqmvBKZNNTp+rqp+rmU22q2gpdW3O8AGY/hatuzOMxUKb9TZeyfxqW7BWY7Z1crtwxc/DMvwHc/FCg9baF5N8LcM4ZHJ7VWtt+iqjFybZkuG/l4U2F+eBLpxaxmoYq7YFV1bVDVX1v6rqh+bd+QexnLqW4rlJPtGGr4pfcGGSg6vqMcvv7pKNVdeCP5hsqv9kVb14RT3dPfOqa2seeGXeuXzGNmIQWHixzqiqx1TVXlX1lgyXa/zeqXY/leGFvjXDL+H3J3lpa+0rk8e3ZWYzXmvtOxle5FH28z2EedWVJO9J8ookz588/tYk7xq/hEUtpa7/k+TOJO+sqkdNNp/9hwyXs15os97GK5lfbckajdlk98RZST7VWrt6Mntbkntaa7fNNL8p97/W27L4pcazhDZbquq7VtbzhzZybTdk2Erwssl0bZJLqurQefV/V1ZQ11IspfZRjFzXt5L86wyb4Y9N8skk561GGJhXXVX1vCTH54G7Q+fyGVvzyxDvrtbaX1fVP0ryGxn+CNybIRFdkKSmmp6eZN8M+4S+nuS4DPvSf6S1dtVq9nkp5llXa+3dU+3/rKruSfL+qjq1DZd9XjVLqau1dktVvTzJ+5K8McN/y7+b5LOTn9eleda2hmN2dpKn529vnXg4GK221tqXknxpatalVXVgkp9N8tPzXt+Mh+uYjTleX89wDZwFn66qx2c4BuIP5r2+GSuuq6qenuSjSX6xtXbRvDq2YMMFgSRprV2R5JCq2pphX9YtVXV5ks8kw1HaSd6Q5OmttT+fPO3zVfUjGQ76OinDJZEfN73cyabYx2aNLpc8p7oWc3mGsT4gD/zltSoeqq5Jm4uSHFhV353kO62126rqxiT/b9Jk3Y1XMrfaFjP6mFXVezM56LK1dt3UQzcm2auq9p35j2X6UuI3Jnn2zCL3m3ps4Xaxy5Hf0Vq7a4Xdf1CrUNti/jQj/3FeYV1LsasxW3hsFKtQ12Iuz3Ag32jmUVdV/b0kf5zkA621X5pZxVw+Yxtx18DfaK3dPvnFe1CSwzMkpiR51OR29r/Je3N/zZcl2beqDpt6/AWTx9f04kgrrGsxh0yeM9YRzUvyIHVNt/n65A/lCzL84V9I6+t2vJIV17aYQzLSmNXgvUlemuQFrbVrZppckeSv88BLiR+c5Im5/1LilyV5RlVNh7NjktyR5AtTbY7OAx2TES9Hvoq1LeaQDLsM5m5OdS3FZUmOrKpHTM07JsmXWmvfXFbnH8Qq1rWYQ7LOx6uqnpbhjIBzWmtvW2RV8/mMLfcoyDGnJHtnGKRDMhxo9bOTn584efzlGY7aXThta3uSj0w9/xFJvpzkExmS/YEZ9g/dl+QfTLW7IMMm2mdnOK3r/yb5nY1cV4aDRE5O8szJcl6d4Y/JOeu1rkmb12Q41ebADKfL3JrkP860WdXxWq3aVnvMkvxaktsynLK0bWr6rqk278twCtnzMxzYdGmSS6ce3zPJVRkOTHpmkhdO+vzvp9o8KcPxEe/KcET0v0jynSQvHHG8Vqu2kyfj/eQMm33PyhDIj16vdU3aPHny/v3PGbY0Lby3F86G2Jrhv8zfynBg5PGTMXztBq/rhCSvnLwPn5rhGJx7k7xmvdY1eV/dnOS3Z5bxPfP+jI3yYZzDi3hUhl+6s9NvTh5/Y4aDc+6ZvJCnZ+p0l0mbg5J8JMOBE3dmOBd89rS7xyb5nSQ7Mpwa9MEke2/kupIcmuEAtduS3JXhP5hTk2xe53WdmeEX0D0Z/sC/KZOrY67VeK1Wbas9ZruopyU5carNIzPs2/zG5H32+0m2zSzn+5L8zyTfTnJLhoMgNy3y+n0uw4Gtfzm9jo1cW5I3J/nKZLxuzfBf2/M3QF2X7GI5B0y1+YEkf5Lh7Jbrkrxlo9eVIQh8YfL82zNsRfzJ9VxXhlMhF1vG9nl/xlyGGAA6tqGPEQAAVkYQAICOCQIA0DFBAAA6JggAQMcEAQDomCAAAB0TBACgY4IAAHRMEACAjgkCANCx/w+9AZgewtQ8HAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "arabalar = [2000,1997,1998,1998,1999,1996,2001,2000,2000,2000,2000,2000,2000,2000,2000,2003,2004,2012,2013,2002,2012,2016,2018,2019,2002,1998,1982,2002,2013,2016]\n",
    "arabaModelGrubu = np.arange(1980,2022,2)\n",
    "\n",
    "plt.figure(dpi=100)\n",
    "#figure ile oluşacak figürümüz için 'dpi' gibi bazı ayarlamalar yapabiliriz.\n",
    "plt.hist(arabalar,arabaModelGrubu,rwidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unavailable-publicity",
   "metadata": {},
   "source": [
    "## boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "complicated-deployment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x2ac2657b850>,\n",
       "  <matplotlib.lines.Line2D at 0x2ac2657bbb0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x2ac2657bf10>,\n",
       "  <matplotlib.lines.Line2D at 0x2ac26589250>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x2ac2657b4f0>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x2ac265895b0>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x2ac26589910>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 118,
     "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.boxplot(yeniDizi)\n",
    "#boxplot dizinin hangi değerler arasında daha yoğun olduğunu gösterir.\n",
    "#standart sapmasının belirlenmesinde yardımcı olur."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "noticed-custody",
   "metadata": {},
   "source": [
    "## pie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "driving-reset",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "numpyDizi = np.array([5,10,15,20,25])\n",
    "myLabels = ['a','b','c','d','e']\n",
    "myExplode = [0.1,0.1,0.1,0.1,0.1]\n",
    "myFigure = plt.figure(dpi=100)\n",
    "plt.pie(numpyDizi,labels=myLabels,explode=myExplode,shadow=False)\n",
    "plt.legend(loc=2,labelspacing=0.1)\n",
    "myFigure.savefig('myfigure.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "tamil-drove",
   "metadata": {},
   "source": [
    "## bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "grateful-tower",
   "metadata": {},
   "outputs": [
    {
     "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": [
    "x = np.linspace(0,10,4)\n",
    "y = np.arange(4,8)\n",
    "plt.bar(x,y,width=2,color='orange',label=\"y'ye göre x\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "living-appendix",
   "metadata": {},
   "outputs": [
    {
     "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.barh(x,y,height=2,color='darkcyan',label=\"y'ye göre x\")\n",
    "plt.xlabel = 'y'\n",
    "plt.ylabel = 'x'\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confidential-hormone",
   "metadata": {},
   "source": [
    "## stackplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "placed-provider",
   "metadata": {},
   "outputs": [
    {
     "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": [
    "eat = [1,1.5,1,1,2]\n",
    "work = [3,3,4,4.5,3.5]\n",
    "play = [2,2.5,2,2,3]\n",
    "sleep = [8,7,7.5,8,6.5]\n",
    "\n",
    "myDays = ['m','t','w','th','f']\n",
    "\n",
    "plt.plot([],[],color='b',label='eat')\n",
    "plt.plot([],[],color='g',label='work')\n",
    "plt.plot([],[],color='y',label='play')\n",
    "plt.plot([],[],color='r',label='sleep')\n",
    "\n",
    "plt.stackplot(myDays,eat,work,play,sleep,colors=['b','g','y','r'])\n",
    "plt.title('5 Days Rutine')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "#Stackplot değerlerin belirtilen 'y'-> değeri üzerinde dağılımlarını\n",
    "#gözlemlemeye olanak sağlar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "applied-press",
   "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": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}