Created on Cognitive Class Labs

PY0101EN-5.1_notebook_quizz_numpy1d.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Get to Know a numpy Array </h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "cast the following list to a numpy array:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "a=[1,2,3,4,5]\n",
    "\n",
    "a = np.array(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) type using the function type "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2) the shape of the array "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5,)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3) the type of data in the array "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4) find the mean of the array "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Creating and Plotting Functions  </h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) create the following functions using the numpy array <code> x </code>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$y=sin(x)+2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.06346652, 0.12693304, 0.19039955, 0.25386607,\n",
       "       0.31733259, 0.38079911, 0.44426563, 0.50773215, 0.57119866,\n",
       "       0.63466518, 0.6981317 , 0.76159822, 0.82506474, 0.88853126,\n",
       "       0.95199777, 1.01546429, 1.07893081, 1.14239733, 1.20586385,\n",
       "       1.26933037, 1.33279688, 1.3962634 , 1.45972992, 1.52319644,\n",
       "       1.58666296, 1.65012947, 1.71359599, 1.77706251, 1.84052903,\n",
       "       1.90399555, 1.96746207, 2.03092858, 2.0943951 , 2.15786162,\n",
       "       2.22132814, 2.28479466, 2.34826118, 2.41172769, 2.47519421,\n",
       "       2.53866073, 2.60212725, 2.66559377, 2.72906028, 2.7925268 ,\n",
       "       2.85599332, 2.91945984, 2.98292636, 3.04639288, 3.10985939,\n",
       "       3.17332591, 3.23679243, 3.30025895, 3.36372547, 3.42719199,\n",
       "       3.4906585 , 3.55412502, 3.61759154, 3.68105806, 3.74452458,\n",
       "       3.8079911 , 3.87145761, 3.93492413, 3.99839065, 4.06185717,\n",
       "       4.12532369, 4.1887902 , 4.25225672, 4.31572324, 4.37918976,\n",
       "       4.44265628, 4.5061228 , 4.56958931, 4.63305583, 4.69652235,\n",
       "       4.75998887, 4.82345539, 4.88692191, 4.95038842, 5.01385494,\n",
       "       5.07732146, 5.14078798, 5.2042545 , 5.26772102, 5.33118753,\n",
       "       5.39465405, 5.45812057, 5.52158709, 5.58505361, 5.64852012,\n",
       "       5.71198664, 5.77545316, 5.83891968, 5.9023862 , 5.96585272,\n",
       "       6.02931923, 6.09278575, 6.15625227, 6.21971879, 6.28318531])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=np.linspace(0,2*np.pi,100)\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2)  plot the function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline  \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<small>Copyright &copy; 2018 IBM Cognitive Class. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license/).</small>"
   ]
  }
 ],
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