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jupyter tutorial
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‎jupyter-notebook.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## What is Jupyter Notebook?\n",
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"- The Jupyter Notebook is an **interactive computing environment** that enables users to author notebook documents that include: - Live code - Interactive widgets - Plots - Narrative text - Equations - Images - Video\n",
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"- Enables code and text combination for user convenient.\n",
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"### Components\n",
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"- **The notebook web application**: An interactive web application for writing and running code interactively and authoring notebook documents.\n",
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"- **Kernels**: Separate processes started by the notebook web application that runs users’ code in a given language and returns output back to the notebook web application.\n",
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"- **Notebook documents**: Self-contained documents that contain a representation of all content visible in the notebook web application, including inputs and outputs of the computations, narrative text, equations, images, and rich media representations of objects.\n",
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"### Notebook\n",
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"Notebook documents contain the only the **input and output** of the interactive session.\n",
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"When you run the notebook web application on your computer, notebook documents are just files on your local filesystem with a **```.ipynb```** extension. This format will serve us when submitting the HWs.\n",
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"These files are JSON files, which are rendered in the web browser"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 1. Open notebook dashboard\n",
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"**cmd -> type \"jupyter notebook\"** \n",
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"Open an existing ```.ipynb``` and create a new one \n",
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"File browser"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 2. Overview of the Notebook UI\n",
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"Consists of:\n",
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"- Menu (save, Insert cells, Kernel)\n",
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"- Toolbar \n",
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"- Notebook area and cells\n",
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"(It is recommended to try the interactive tour in the \"Help:User Interface Tour\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Cell types:\n",
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"1. Code cell: Input and output of code that is run in the kernel\n",
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"2. Markdown cells: Narrative text\n",
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"3. Raw cells"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Learn the keyboard shortbuts which you will find very useful, such as: Shift+Enter, a, b ..."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 3. Code cells\n",
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"- Cell menu\n",
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"- Kernel menu"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"print 'Hello world'"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Assigning variables"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"x = 5 #assignment\n",
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"y = x + 2\n",
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"x==4 #condition"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"x"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### importing"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"print np.random.random()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"#defining a function\n",
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"def fun(v):\n",
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" '''2nd power function'''\n",
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" return np.power(v,2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"for i in range(10): #for loop\n",
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" print i,fun(i)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 4. Markdown cells\n",
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"- Convert a cell to markdown\n",
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"- All HTML tabs are supported!\n",
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"- Nice tutorials to experience the md language: [md_toturial1](http://commonmark.org/help/tutorial/) [md_toturial2](http://www.markdowntutorial.com/)\n",
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"- And a couple of links about Markdown: [Link to markdown reference](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet) [Link to another markdown reference](https://daringfireball.net/projects/markdown/syntax)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# This is Heading1\n",
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"## This is Heading2\n",
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"\n",
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"some gray colored text:\n",
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"> This is where we can bring qoutes and present them nicely\n",
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"\n",
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"And this is the paragraph about something very important. Even math:\n",
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"\n",
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"$$y_{sub} = \\sqrt(x_{sub})$$\n",
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"\n",
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"Or python code example:\n",
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"```\n",
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"def foo():\n",
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" return \"foo\"\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To write a free-text (Markdown) in Ipython Notebook cell, select the cell and Press<b> M </b>. If the cell is entered (text input) press <b> ESC </b> first, to exit the cell. <br> To enter the cell again press <b> Enter </b><br>\n",
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"To execute the cell, Press <b> Shift+Enter </b>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To convert the cell back to code cell, press <b> Y"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To add new cell press **A** (above) or **B** (beneath) <br>\n",
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"To delete a cell press **DD**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 5. Matplotlib"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"x = np.linspace(0, 100)\n",
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"y = np.sqrt(x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"print x\n",
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"print y"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"plt.plot(x, y)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 6. Extra\n",
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"- Auto-completion using ```tab```\n",
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"- Function documantation using ```Shift+tab```\n",
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"- Download as .py or .ipynb\n",
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"- Restart kernel, Interrupt kernel"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"*based heavily on [link](http://jupyter-notebook.readthedocs.io/en/latest/examples/Notebook/What%20is%20the%20Jupyter%20Notebook.html)* \n",
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"*[Link for downloading Anaconda](https://www.continuum.io/downloads).* **Make sure to download the 2.7 version**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Saving and Exiting"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Ipython Notebook has AutoSaves. In order to properly save the notebook go to **File-> Save** and then **File->Close and Halt**. You can also export the code to regular Python file (**.py**) or even a pdf using **File-> Download as**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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