220422_hariom singh_01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** * NOTE: ALL THE COMMANDS FOR PLOTTING A FIGURE SHOULD ALL GO IN THE SAME CELL. SEPARATING THEM OUT INTO MULTIPLE CELLS MAY CAUSE NOTHING TO SHOW UP. * **\n",
    "\n",
    "# Exercises\n",
    "\n",
    "Follow the instructions to recreate the plots using this data:\n",
    "\n",
    "## Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "x = np.arange(0,100)\n",
    "y = x*2\n",
    "z = x**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Import matplotlib.pyplot as plt and set %matplotlib inline if you are using the jupyter notebook. What command do you use if you aren't using the jupyter notebook?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 1\n",
    "\n",
    "** Follow along with these steps: **\n",
    "* ** Create a figure object called fig using plt.figure() **\n",
    "* ** Use add_axes to add an axis to the figure canvas at [0,0,1,1]. Call this new axis ax. **\n",
    "* ** Plot (x,y) on that axes and set the labels and titles to match the plot below:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'title')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax.plot(x,y)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_title('title')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 2\n",
    "** Create a figure object and put two axes on it, ax1 and ax2. Located at [0,0,1,1] and [0.2,0.5,.2,.2] respectively.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "\n",
    "ax1 = fig.add_axes([0,0,1,1])\n",
    "ax2 = fig.add_axes([0.2,0.5,.2,.2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Now plot (x,y) on both axes. And call your figure object to show it.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax1.plot(x,y)\n",
    "ax1.set_xlabel('x')\n",
    "ax1.set_ylabel('y')\n",
    "\n",
    "\n",
    "ax2.plot(x,y)\n",
    "ax2.set_xlabel('x')\n",
    "ax2.set_ylabel('y')\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 3\n",
    "\n",
    "** Create the plot below by adding two axes to a figure object at [0,0,1,1] and [0.2,0.5,.4,.4]**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax2 = fig.add_axes([0.2,0.5,.4,.4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Now use x,y, and z arrays to recreate the plot below. Notice the xlimits and y limits on the inserted plot:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.plot(x,z)\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Z')\n",
    "\n",
    "\n",
    "ax2.plot(x,y)\n",
    "ax2.set_xlabel('X')\n",
    "ax2.set_ylabel('Y')\n",
    "ax2.set_title('zoom')\n",
    "ax2.set_xlim(20,22)\n",
    "ax2.set_ylim(30,50)\n",
    "\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 4\n",
    "\n",
    "** Use plt.subplots(nrows=1, ncols=2) to create the plot below.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Now plot (x,y) and (x,z) on the axes. Play around with the linewidth and style**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes[0].plot(x,y,color=\"blue\", lw=3, ls='--')\n",
    "axes[1].plot(x,z,color=\"red\", lw=3, ls='-')\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** See if you can resize the plot by adding the figsize() argument in plt.subplots() are copying and pasting your previous code.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'z')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(12,2))\n",
    "\n",
    "axes[0].plot(x,y,color=\"blue\", lw=5)\n",
    "axes[0].set_xlabel('x')\n",
    "axes[0].set_ylabel('y')\n",
    "\n",
    "axes[1].plot(x,z,color=\"red\", lw=3, ls='--')\n",
    "axes[1].set_xlabel('x')\n",
    "axes[1].set_ylabel('z')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Great Job!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}