Book Image

NumPy Cookbook

Book Image

NumPy Cookbook

Overview of this book

Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity. "NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source. "Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library. You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples. "NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
Table of Contents (17 chapters)
NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Exporting a web notebook


Sometimes you will want to exchange notebooks with friends or colleagues. The web notebook provides several methods to export your data.

How to do it...

A web notebook can be exported using the following options:

  • The Print option: The Print button doesn't actually print the notebook, but allows you to export the notebook as PDF or HTML document.

  • Downloading the notebook: Download your notebook to a location chosen by you, using the Download button. We can specify whether we want to download the notebook as .py file, which is just a normal Python program, or in the JSON format as a .ipynb file. The notebook we created in the previous recipe looks like the following, after exporting:

    {
     "metadata": {
      "name": "Untitled1"
     }, 
     "nbformat": 2, 
     "worksheets": [
      {
        "cells": [
        {
          "cell_type": "code", 
          "collapsed": false, 
          "input": [
            "plot(sinc(a))"
          ], 
          "language": "python", 
          "outputs": [
          {
            "output_type": "pyout", 
            "prompt_number": 3, 
            "text": [
              "[<matplotlib.lines.Line2D at 0x103d9c690>]"
            ]
          }, 
          {
            "output_type": "display_data", 
            "png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAD9CAYAAABZVQdHAAAABHNCSVQICAgIf...
              mgkAAAAASUVORK5CYII=\n"
          }
          ], 
          "prompt_number": 3
        }
        ]
      }
      ]
    }

    Note

    Some of the text has been omitted for brevity. This file is not intended for editing or reading even, but it is pretty readable if you ignore the image representation part. For more information about JSON please see https://en.wikipedia.org/wiki/JSON.

  • Saving the notebook: Save the notebook using the Save button. This will automatically export a notebook in the native JSON .ipynb format. The file will be stored in the directory where you started IPython initially.