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Chart cloning 0
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| Week | cat | dog | fish | |
|---|---|---|---|---|
| 2012-01-01 - 2012-01-07 | 56 | 92 | 59 | |
| 2012-01-08 - 2012-01-14 | 59 | 91 | 56 | |
| 2012-01-15 - 2012-01-21 | 55 | 91 | 56 | |
| 2012-01-22 - 2012-01-28 | 56 | 89 | 54 | |
| 2012-01-29 - 2012-02-04 | 58 | 89 | 55 | |
| 2012-02-05 - 2012-02-11 | 60 | 94 | 54 | |
| 2012-02-12 - 2012-02-18 | 56 | 98 | 54 | |
| 2012-02-19 - 2012-02-25 | 58 | 91 | 58 | |
| 2012-02-26 - 2012-03-03 | 59 | 85 | 54 | |
| 2012-03-04 - 2012-03-10 | 56 | 86 | 56 | |
| 2012-03-11 - 2012-03-17 | 54 | 87 | 54 | |
| 2012-03-18 - 2012-03-24 | 54 | 87 | 55 | |
| 2012-03-25 - 2012-03-31 | 55 | 86 | 56 | |
| 2012-04-01 - 2012-04-07 | 57 | 89 | 59 | |
| 2012-04-08 - 2012-04-14 | 54 | 89 | 54 | |
| 2012-04-15 - 2012-04-21 | 55 | 91 | 55 | |
| 2012-04-22 - 2012-04-28 | 57 | 87 | 56 | |
| 2012-04-29 - 2012-05-05 | 61 | 92 | 57 | |
| 2012-05-06 - 2012-05-12 | 57 | 91 | 56 | |
| 2012-05-13 - 2012-05-19 | 55 | 85 | 57 | |
| 2012-05-20 - 2012-05-26 | 54 | 87 | 56 | |
| 2012-05-27 - 2012-06-02 | 54 | 88 | 56 | |
| 2012-06-03 - 2012-06-09 | 57 | 88 | 56 | |
| 2012-06-10 - 2012-06-16 | 55 | 87 | 55 | |
| 2012-06-17 - 2012-06-23 | 55 | 88 | 56 | |
| 2012-06-24 - 2012-06-30 | 57 | 92 | 57 | |
| 2012-07-01 - 2012-07-07 | 55 | 94 | 56 | |
| 2012-07-08 - 2012-07-14 | 58 | 94 | 59 | |
| 2012-07-15 - 2012-07-21 | 58 | 96 | 57 | |
| 2012-07-22 - 2012-07-28 | 58 | 92 | 56 | |
| 2012-07-29 - 2012-08-04 | 56 | 93 | 55 | |
| 2012-08-05 - 2012-08-11 | 57 | 94 | 55 | |
| 2012-08-12 - 2012-08-18 | 58 | 100 | 55 | |
| 2012-08-19 - 2012-08-25 | 58 | 99 | 56 | |
| 2012-08-26 - 2012-09-01 | 59 | 93 | 54 | |
| 2012-09-02 - 2012-09-08 | 59 | 92 | 57 | |
| 2012-09-09 - 2012-09-15 | 58 | 93 | 53 | |
| 2012-09-16 - 2012-09-22 | 59 | 91 | 52 | |
| 2012-09-23 - 2012-09-29 | 61 | 92 | 52 | |
| 2012-09-30 - 2012-10-06 | 59 | 91 | 52 | |
| 2012-10-07 - 2012-10-13 | 59 | 91 | 51 | |
| 2012-10-14 - 2012-10-20 | 58 | 89 | 50 | |
| 2012-10-21 - 2012-10-27 | 64 | 88 | 51 | |
| 2012-10-28 - 2012-11-03 | 62 | 85 | 47 | |
| 2012-11-04 - 2012-11-10 | 57 | 88 | 46 | |
| 2012-11-11 - 2012-11-17 | 60 | 89 | 48 | |
| 2012-11-18 - 2012-11-24 | 61 | 95 | 48 | |
| 2012-11-25 - 2012-12-01 | 64 | 92 | 49 | |
| 2012-12-02 - 2012-12-08 | 65 | 89 | 49 | |
| 2012-12-09 - 2012-12-15 | 66 | 89 | 48 | |
| 2012-12-16 - 2012-12-22 | 63 | 88 | 48 | |
| 2012-12-23 - 2012-12-29 | 67 | 97 | 54 | |
| 2012-12-30 - 2013-01-05 | 63 | 99 | 58 |
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| { | |
| "metadata": { | |
| "name": "" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "heading", | |
| "level": 1, | |
| "metadata": {}, | |
| "source": [ | |
| "Learning by cloning with matplotlib -2-" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "# An article from Asymco.com shows a graph where they try to show the\n", | |
| "# revenues of the Apple software sales.\n", | |
| "# I will try to clone the second graph [made with Numbers, as noted in the article]. \n", | |
| "from IPython.core.display import Image\n", | |
| "Image(url=\"http://www.asymco.com/wp-content/uploads/2013/10/Screen-Shot-2013-10-24-at-10-24-5.08.54-PM.png\")\n", | |
| "# Image Source: Asymco.com" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<img src=\"http://www.asymco.com/wp-content/uploads/2013/10/Screen-Shot-2013-10-24-at-10-24-5.08.54-PM.png\"/>" | |
| ], | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 1, | |
| "text": [ | |
| "<IPython.core.display.Image at 0x10ebc7710>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 1 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Source: <a href='http://www.asymco.com/2013/10/24/the-value-of-zero-priced-software/' target='_blank'>The value of zero-priced software</a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "# Imports are the same as last time\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "%matplotlib inline\n", | |
| "\n", | |
| "# this is a chart with four different bar plots overlapping.\n", | |
| "\n", | |
| "# first! the X and Y axis\n", | |
| "millions = [x*100 for x in range(10)]\n", | |
| "# I will be lazy here and compose the quarters in three steps\n", | |
| "quarters = ['Q' + qrt + '0' + str(year) for year in range(6, 10) for qrt in '1234']\n", | |
| "quarters += ['Q' + qrt + str(year) for year in range(10, 14) for qrt in '1234']\n", | |
| "quarters = ['Q405'] + quarters[:-2]\n", | |
| "# create the figure\n", | |
| "fig, axis1 = plt.subplots(figsize=(9, 6), dpi=75)\n", | |
| "\n", | |
| "# set the Y ticks and set the limits of the graph\n", | |
| "plt.yticks(millions, size=13)\n", | |
| "plt.ylim((0, 900))\n", | |
| "plt.xlim((0, len(quarters)))\n", | |
| "\n", | |
| "# set the X ticks\n", | |
| "plt.xticks(range(len(quarters)))\n", | |
| "axis1.set_xticklabels(quarters, rotation='270', ha='left', size=11)\n", | |
| "from matplotlib.ticker import FormatStrFormatter\n", | |
| "# This is the printf like formatter, I am using it to display the '$'\n", | |
| "currency_format = FormatStrFormatter('$%d')\n", | |
| "# ant tell it where to use apply it\n", | |
| "axis1.yaxis.set_major_formatter(currency_format)\n", | |
| "\n", | |
| "# set the horizontal grid along the Y axis\n", | |
| "axis1.yaxis.grid(True, linestyle='-', which='major', color='grey', alpha=0.5)\n", | |
| "# and we know this happens\n", | |
| "axis1.set_axisbelow(True)\n", | |
| "\n", | |
| "# name the graph\n", | |
| "plt.title('Components of Software Sales', size=14)\n", | |
| "\n", | |
| "# clean the spines\n", | |
| "axis1.spines['top'].set_visible(False)\n", | |
| "axis1.spines['right'].set_visible(False)\n", | |
| "axis1.spines['left'].set_visible(False)\n", | |
| "axis1.yaxis.set_ticks_position('none') # This is still great!\n", | |
| "axis1.xaxis.set_ticks_position('none')\n", | |
| "\n", | |
| "# the title needs to a few pixels up\n", | |
| "title_pos = axis1.title.get_position() # returns a pair (x,y)\n", | |
| "new_title_pos = (title_pos[0], title_pos[1]+0.05) # .05 was trial and error\n", | |
| "axis1.title.set_position(new_title_pos)\n", | |
| "\n", | |
| "# Here comes the part that got me thinking about cloning this graph,\n", | |
| "# since I don't have any data to reproduce it and the article does not\n", | |
| "# tell where to get it.\n", | |
| "x_range_len = float(len(quarters))\n", | |
| "\n", | |
| "from numpy import arange\n", | |
| "pro_apps = arange(100, 400, 300/x_range_len).tolist()\n", | |
| "os_x = arange(200, 550, 350/x_range_len).tolist()\n", | |
| "iwork = arange(250, 700, 450/x_range_len).tolist()\n", | |
| "ios_apps = arange(-100, 850, 950/x_range_len).tolist()\n", | |
| "\n", | |
| "x_range = range(len(quarters))\n", | |
| "plt.bar(x_range, ios_apps, color='#dd7533', zorder=1, edgecolor='none', width=1, label='iOS Apps (incl. iWork iOS)')\n", | |
| "plt.bar(x_range, iwork, color='#d8b624', zorder=2, edgecolor='none', width=1, label='iWork')\n", | |
| "plt.bar(x_range, os_x, color='#8abe60', zorder=3, edgecolor='none', width=1, label='OS X')\n", | |
| "plt.bar(x_range, pro_apps, color='#81a2b2', zorder=4, edgecolor='none', width=1, label='Pro Apps')\n", | |
| "\n", | |
| "# set the legend\n", | |
| "axis1.legend(loc='upper left', frameon=False, fontsize='medium',\n", | |
| " handlelength=0.9, handleheight=0.9) \n", | |
| "# modify handle length and height to create squares\n", | |
| "\n", | |
| "# add padding to the y\n", | |
| "axis1.yaxis.set_tick_params(pad=12)\n", | |
| "\n", | |
| "# place the copyright mark using LaTeX\n", | |
| "plt.text(1, 920, r'$\\copyright$ /\\symco', size=12) # position, trial and error\n", | |
| "\n", | |
| "plt.show()" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": 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37khLSwMATJ48Gba2thg2bBhWrVol3RMAevbsiX379tV5zkRE1LAYvNSDTCar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\ndR7oAAAAAElFTkSuQmCC\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x110397750>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 2 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# Things missing:\n", | |
| " 1. DATA!!!\n", | |
| " 2. The legend has some padding between the items, have to learn how to compact it a bit.\n", | |
| "\n", | |
| "## Still this thing missing:\n", | |
| " 1. figure out how to use the cells properly in the IPython notebook.\n", | |
| "\n", | |
| "I failed to clone this graph, I tried to get the looking but without the\n", | |
| "raw data there is nothing I can do to get that done.\n", | |
| "\n", | |
| "\n", | |
| "sbuj" | |
| ] | |
| } | |
| ], | |
| "metadata": {} | |
| } | |
| ] | |
| } |
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