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    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#--------------------------#\n",
    "#When you make your iPython notebook,\n",
    "#add the following line at the top of your code\n",
    "#after your comments:\n",
    "# %matplotlib inline\n",
    "#--------------------------#\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "#Create arrays for your data\n",
    "\n",
    "theta_array = np.array([37.5,40.5,43.5,46.5,49.5])\n",
    "ymean_array = np.array([86.7,90.98,94.22,90.2,85.8])\n",
    "\n",
    "\n",
    "#Create and array for your y-axis uncertainties\n",
    "\n",
    "yerr_array = np.array([.05,.05,.05,.05,.05])\n",
    "\n",
    "#Reassign variables\n",
    "x = theta_array\n",
    "y = ymean_array\n",
    "dy = yerr_array\n",
    "\n",
    "#size the plot\n",
    "plt.figure(figsize=(15,10))\n",
    "\n",
    "#create scatter plot\n",
    "plt.scatter(x, y, color='blue', marker='o')\n",
    "\n",
    "#create labels\n",
    "plt.xlabel('$\\\\theta$ (degrees)')\n",
    "plt.ylabel('$y_{mean}$ (m)')\n",
    "plt.title('Height on wall vs Launcher Angle')\n",
    "\n",
    "#fitting to a 2nd degree polynomial\n",
    "c,b,a=np.polynomial.polynomial.polyfit(x,y,2,w=dy)\n",
    "\n",
    "#Annotate with values of A, B, C from best fit polynomial\n",
    "plt.annotate('A = {value:.{digits}E}'.format(value=a, digits=3),\n",
    "             (0.05, 0.9), xycoords='axes fraction')\n",
    "\n",
    "plt.annotate('B = {value:.{digits}E}'.format(value=b, digits=3),\n",
    "             (0.05, 0.85), xycoords='axes fraction')\n",
    "             \n",
    "plt.annotate('C = {value:.{digits}E}'.format(value=c, digits=3),\n",
    "             (0.05, 0.8), xycoords='axes fraction')\n",
    "#Create fit line\n",
    "xnew = np.linspace(x.min(), x.max(), 300)\n",
    "fit = a*xnew**2 + b*xnew +c\n",
    "\n",
    "plt.scatter(xnew, fit, color='red')\n",
    "plt.show()\n",
    "\n",
    "print \"C = \",c , \"B = \",b, \"A = \",a\n"
   ]
  }
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