transform.ipynb

interactive.ipynb

{
  "cells": [
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "cell_type": "code",
      "source": "import pandas as pd\nimport scipy as sp\nimport seaborn as sns\n\n%matplotlib inline",
      "execution_count": 86,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "- http://qiita.com/tanemaki/items/e965cd9c25acbeed860c\n- http://qiita.com/y__sama/items/654ed8ab7464718876f"
    },
    {
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "cell_type": "markdown",
      "source": "- conda install pivottablejs\n- conda install ipywidgets\n- https://github.com/damianavila/RISE\n\n```bash\nmkdir -p ~/.local/share/jupyter/nbextensions && cd $_\ngit clone [email protected]:damianavila/RISE.git && cd RISE\npython setup.py install\n```\n"
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true
      },
      "cell_type": "code",
      "source": "import bokeh\nimport ipywidgets\nimport pivottablejs\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n%matplotlib inline\n\niris = sns.load_dataset(\"iris\")",
      "execution_count": 57,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "import string\n\n[w for w in dir(ipywidgets) if w[0] in string.ascii_uppercase]",
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "['Accordion',\n 'BoundedFloatText',\n 'BoundedIntText',\n 'Box',\n 'Button',\n 'CallbackDispatcher',\n 'Checkbox',\n 'Color',\n 'ColorPicker',\n 'CommInfo',\n 'Controller',\n 'DOMWidget',\n 'Dropdown',\n 'EventfulDict',\n 'EventfulList',\n 'FlexBox',\n 'FloatProgress',\n 'FloatRangeSlider',\n 'FloatSlider',\n 'FloatText',\n 'HBox',\n 'HTML',\n 'Image',\n 'IntProgress',\n 'IntRangeSlider',\n 'IntSlider',\n 'IntText',\n 'Latex',\n 'Output',\n 'PlaceProxy',\n 'Proxy',\n 'RadioButtons',\n 'Select',\n 'SelectMultiple',\n 'Tab',\n 'Text',\n 'Textarea',\n 'ToggleButton',\n 'ToggleButtons',\n 'VBox',\n 'Valid',\n 'Widget']"
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "ipywidgets.Checkbox()",
      "execution_count": 70,
      "outputs": []
    },
    {
      "metadata": {
        "scrolled": false,
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "@ipywidgets.interact(\n    a=(-10, 10, 1),\n    b={'a': 1, 'b': 2.0, 'c': 5.0},\n    check=True,\n)\ndef plot_linear_func(a=10, b=1, check=False):\n    print(\"a =\", a)\n    print(\"b =\", b)\n    print(\"check =\", check)\n    \n    x = pd.Series(range(10))\n    y = a * x + check * b\n    plt.plot(y)",
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "stream",
          "text": "a = 1\nb = 5.0\ncheck = False\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x11c498ba8>",
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": false,
        "scrolled": false
      },
      "cell_type": "code",
      "source": "pivottablejs.pivot_ui(iris)",
      "execution_count": 41,
      "outputs": [
        {
          "execution_count": 41,
          "output_type": "execute_result",
          "data": {
            "text/html": "\n        <iframe\n            width=\"100%\"\n            height=\"500\"\n            src=\"pivottablejs.html\"\n            frameborder=\"0\"\n            allowfullscreen\n        ></iframe>\n        ",
            "text/plain": "<IPython.lib.display.IFrame at 0x11c06afd0>"
          },
          "metadata": {}
        }
      ]
    }
  ],
  "metadata": {
    "toc": {
      "toc_cell": false,
      "toc_window_display": false,
      "toc_number_sections": true,
      "toc_threshold": 6
    },
    "language_info": {
      "name": "python",
      "codemirror_mode": {
        "version": 3,
        "name": "ipython"
      },
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.5.1",
      "mimetype": "text/x-python",
      "file_extension": ".py"
    },
    "celltoolbar": "Slideshow",
    "hide_input": false,
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "gist": {
      "id": "",
      "data": {
        "description": "transform.ipynb",
        "public": true
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}