matplotlip_notes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "x=np.linspace(0,5,11)\n",
    "y=x**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Axes 2 title')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "\n",
    "axes1=fig.add_axes([0.1,0.1,0.8,0.8])\n",
    "axes2=fig.add_axes([0.2,0.5,0.4,0.3])\n",
    "\n",
    "#larger figure axes1\n",
    "axes1.plot(x,y,\"b\")\n",
    "axes1.set_xlabel(\"X_label_axes2\")\n",
    "axes1.set_ylabel('Y_label_axes2')\n",
    "axes1.set_title('Axes 2 Title')\n",
    "\n",
    "#insert figure axes 2\n",
    "axes2.plot(y,x,\"r\")\n",
    "axes2.set_xlabel(\"X_label_axes2\")\n",
    "axes2.set_ylabel('Y_label_axes2')\n",
    "axes2.set_title('Axes 2 title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'title')"
      ]
     },
     "execution_count": 15,
     "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": [
    "#use similar to plt.figure() except use tuple unpacking\n",
    "#to grab fig and axes\n",
    "fig,axes=plt.subplots()\n",
    "axes.plot(x,y,\"r\")\n",
    "\n",
    "axes.plot(x,y,'r')\n",
    "axes.set_xlabel(\"x\")\n",
    "axes.set_ylabel('y')\n",
    "axes.set_title('title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#empty canvas of 1 by subplots\n",
    "fig,axes=plt.subplots(nrows=1,ncols=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:>, <AxesSubplot:>], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for ax in axes:\n",
    "    ax.plot(x,y,\"b\")\n",
    "    ax.set_xlabel('x')\n",
    "    ax.set_ylabel('y')\n",
    "    ax.set_title('title')\n",
    "    \n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes=plt.subplots(nrows=1,ncols=2)\n",
    "\n",
    "axes[0].plot(x,y)\n",
    "axes[0].set_title('first plot')\n",
    "\n",
    "axes[1].plot(y,x)\n",
    "axes[1].set_title('second plot')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:title={'center':'first plot'}>,\n",
       "       <AxesSubplot:title={'center':'second plot'}>], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# figure size DPI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f69bfc9d0>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 216x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(3,2))\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f6a4354c0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(8,2))\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x144 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes=plt.subplots(nrows=2,ncols=1,figsize=(3,2))\n",
    "\n",
    "axes[0].plot(x,y)\n",
    "\n",
    "axes[1].plot(y,x)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# save figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 216x144 with 2 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('my_picture.png',dpi=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10f6c309fd0>"
      ]
     },
     "execution_count": 33,
     "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": [
    "fig=plt.figure()\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "\n",
    "ax.plot(x,y,label='x,y')\n",
    "ax.plot(x,x**4,label='x uzeri 4')\n",
    "ax.plot(x,x**3,label='x cubed')\n",
    "ax.plot(y,x,label='y,x')\n",
    "\n",
    "ax.legend(loc=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# plot colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10f6df0dee0>"
      ]
     },
     "execution_count": 55,
     "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": [
    "fig=plt.figure()\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "\n",
    "ax.plot(x,y,label='x,y',color='red',linewidth=3,alpha=0.6,linestyle='--')\n",
    "ax.plot(x,x**4,label='x uzeri 4',color=\"purple\",linewidth=6,alpha=0.5,linestyle='-.')\n",
    "ax.plot(x,x**3,label='x cubed',lw=2,ls=':')\n",
    "ax.plot(y,x,label='y,x',lw=15,ls='--',marker='o')\n",
    "\n",
    "ax.legend(loc=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f6e0d0160>]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(3,2))\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y,marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f6db91340>]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(5,2))\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y,marker='o',lw=2,markersize=20,\n",
    "       markerfacecolor='yellow',markeredgewidth=3,markeredgecolor='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# y and x limit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 2.0)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(5,2))\n",
    "\n",
    "ax=fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y,lw=2,markersize=20,\n",
    "       markerfacecolor='yellow',markeredgewidth=3,markeredgecolor='green')\n",
    "\n",
    "ax.set_xlim([0,1])\n",
    "ax.set_ylim([0,2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# special plot types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "scatter() missing 2 required positional arguments: 'x' and 'y'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-74-1516a20b26b1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: scatter() missing 2 required positional arguments: 'x' and 'y'"
     ]
    }
   ],
   "source": [
    "plt.scatter()"
   ]
  },
  {
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}