data-science-ipython-notebooks/numpy/numpy.ipynb

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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# NumPy\n",
      "\n",
      "* NumPy Arrays, dtype, and shape\n",
      "* Common Array Operations\n",
      "* Reshaping and In-Place Updating\n",
      "* Combining Arrays\n",
      "* Creating Fake Data and Adding Noise"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## NumPy Arrays, dtypes, and shapes"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a = np.array([1, 2, 3])\n",
      "print(a)\n",
      "print(a.shape)\n",
      "print(a.dtype)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[1 2 3]\n",
        "(3,)\n",
        "int64\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "b = np.array([[0, 2, 4], [1, 3, 5]])\n",
      "print(b)\n",
      "print(b.shape)\n",
      "print(b.dtype)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[[0 2 4]\n",
        " [1 3 5]]\n",
        "(2, 3)\n",
        "int64\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.zeros(5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "array([ 0.,  0.,  0.,  0.,  0.])"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.ones(shape=(3, 4), dtype=np.int32)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "array([[1, 1, 1, 1],\n",
        "       [1, 1, 1, 1],\n",
        "       [1, 1, 1, 1]], dtype=int32)"
       ]
      }
     ],
     "prompt_number": 5
    }
   ],
   "metadata": {}
  }
 ]
}