{ "metadata": { "name": "", "signature": "sha256:cb8fc4454a69123dcb745c323968d06c15444cee91494edb720893b06e98c249" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "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": {} } ] }