notebook/Zeppelin Tutorial/Matplotlib (Python, PySpark)_2C2AUG798.zpln

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      "text": "%md\n## Introduction\nIn this tutorial we will go through some of the basic features of Zeppelin\u0027s built-in matplotlib integration. \n\n### Prerequisites\n`matplotlib` must be installed to your local python installation. (use `pip install matplotlib` or `conda install matplotlib` if you have `conda`). Additionally, you will need Zeppelin\u0027s matplotlib backend files which are usually found in `$ZEPPELIN_HOME/lib/python`. Although Zeppelin should automatically find this directory, it might be a good idea to add it to your `PYTHONPATH` just in case. \n\n### Interpreters\nMost of the examples shown in this tutorial can be used interchangeably with either the `python` or `pyspark` interpreters. Iterative plotting using the Angular Display System is currently only available for `pyspark`, but this functionality will eventually be added to the base `python` interpreter. \n\n### macOS\nMake sure locale is set, to avoid `ValueError: unknown locale: UTF-8`\n\n### virtualenv\nIn case you want to use virtualenv or conda env:\n - configure python interpreter property -\u003e `absolute/path/to/venv/bin/python`\n - see *Working with Matplotlib in Virtual environments* in the [Matplotlib FAQ](http://matplotlib.org/faq/virtualenv_faq.html)\n \n### A simple example\nLet\u0027s start by making a very simple line plot:",
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            "data": "\u003cdiv class\u003d\"markdown-body\"\u003e\n\u003ch2\u003eIntroduction\u003c/h2\u003e\n\u003cp\u003eIn this tutorial we will go through some of the basic features of Zeppelin\u0026rsquo;s built-in matplotlib integration. \u003c/p\u003e\n\u003ch3\u003ePrerequisites\u003c/h3\u003e\n\u003cp\u003e\u003ccode\u003ematplotlib\u003c/code\u003e must be installed to your local python installation. (use \u003ccode\u003epip install matplotlib\u003c/code\u003e or \u003ccode\u003econda install matplotlib\u003c/code\u003e if you have \u003ccode\u003econda\u003c/code\u003e). Additionally, you will need Zeppelin\u0026rsquo;s matplotlib backend files which are usually found in \u003ccode\u003e$ZEPPELIN_HOME/interpreter/lib/python\u003c/code\u003e. Although Zeppelin should automatically find this directory, it might be a good idea to add it to your \u003ccode\u003ePYTHONPATH\u003c/code\u003e just in case. \u003c/p\u003e\n\u003ch3\u003eInterpreters\u003c/h3\u003e\n\u003cp\u003eMost of the examples shown in this tutorial can be used interchangeably with either the \u003ccode\u003epython\u003c/code\u003e or \u003ccode\u003epyspark\u003c/code\u003e interpreters. Iterative plotting using the Angular Display System is currently only available for \u003ccode\u003epyspark\u003c/code\u003e, but this functionality will eventually be added to the base \u003ccode\u003epython\u003c/code\u003e interpreter. \u003c/p\u003e\n\u003ch3\u003emacOS\u003c/h3\u003e\n\u003cp\u003eMake sure locale is set, to avoid \u003ccode\u003eValueError: unknown locale: UTF-8\u003c/code\u003e\u003c/p\u003e\n\u003ch3\u003evirtualenv\u003c/h3\u003e\n\u003cp\u003eIn case you want to use virtualenv or conda env:\u003cbr/\u003e - configure python interpreter property -\u0026gt; \u003ccode\u003eabsolute/path/to/venv/bin/python\u003c/code\u003e\u003cbr/\u003e - see \u003cem\u003eWorking with Matplotlib in Virtual environments\u003c/em\u003e in the \u003ca href\u003d\"http://matplotlib.org/faq/virtualenv_faq.html\"\u003eMatplotlib FAQ\u003c/a\u003e\u003c/p\u003e\n\u003ch3\u003eA simple example\u003c/h3\u003e\n\u003cp\u003eLet\u0026rsquo;s start by making a very simple line plot:\u003c/p\u003e\n\u003c/div\u003e"
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      "text": "%python\nimport matplotlib.pyplot as plt\nplt.plot([1, 2, 3])",
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      "text": "%python\n# Figure 1\nplt.plot([1, 2, 3])\n\n# Figure 2\nplt.figure()\nplt.plot([3, 2, 1])",
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      "text": "%md\n### Changing the default inline plotting behavior\nBoth the `python` and `pyspark` include a built-in function for changing some default inline plotting behavior. For example, we can change the default size of each figure in pixels to 400x300 in svg format using: ",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
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            "data": "\u003ch3\u003eChanging the default inline plotting behavior\u003c/h3\u003e\n\u003cp\u003eBoth the \u003ccode\u003epython\u003c/code\u003e and \u003ccode\u003epyspark\u003c/code\u003e include a built-in function for changing some default inline plotting behavior. For example, we can change the default size of each figure in pixels to 400x300 in svg format using:\u003c/p\u003e\n"
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      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
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      "text": "%python\nz.configure_mpl(width\u003d400, height\u003d300, fmt\u003d\u0027svg\u0027)\nplt.plot([1, 2, 3])",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
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gupFtaPfvQjffLJJ1q+fLlGR0f19ttva+HChSorK2Px4QQmc89OnTqlAwcOaNasWZo9e7ZOnDhhu2zrWOQamAfdN95rYzU2Nqq8vFwpKSlKS0uTx+PRRx99pCtXrrj+/cZCQgBAQEKqhQUAcA8CBAAQEAIEABAQAgQAEBACBAAQEAIEABAQAgQAEBACBAAQEAIEABAQAgQAEBACBAAQEAIEABAQAgQAEBACBAAQEAIEABAQAgQAEBACBAAQkP8FIFQxVkgtI/8AAAAASUVORK5CYII\u003d style\u003d\u0027width\u003dauto;height:auto\u0027\u003e\u003cdiv\u003e\n"
          }
        ]
      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "text": "%md\n### Iteratively updating a plot\n#### (a) Using multiple plots\nNow let\u0027s show an example where we update each element of the plot in a separate paragraph. However, you may have noticed that each matplotlib figure instance gets closed immediately after its shown. To fix this, we set the `close` property to `False` in our configuration:",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "editorMode": "ace/mode/markdown",
        "editorHide": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 394.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
            }
          }
        ]
      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627960_-1477396098",
      "id": "20160617-140439_1111727405",
      "results": {
        "code": "SUCCESS",
        "msg": [
          {
            "type": "HTML",
            "data": "\u003ch3\u003eIteratively updating a plot\u003c/h3\u003e\n\u003ch4\u003e(a) Using multiple plots\u003c/h4\u003e\n\u003cp\u003eNow let\u0027s show an example where we update each element of the plot in a separate paragraph. However, you may have noticed that each matplotlib figure instance gets closed immediately after its shown. To fix this, we set the \u003ccode\u003eclose\u003c/code\u003e property to \u003ccode\u003eFalse\u003c/code\u003e in our configuration:\u003c/p\u003e\n"
          }
        ]
      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "title": "First line",
      "text": "%python\nplt.close() # Added here to reset the first plot when rerunning the paragraph\nz.configure_mpl(width\u003d600, height\u003d400, fmt\u003d\u0027png\u0027, close\u003dFalse)\nplt.plot([1, 2, 3], label\u003dr\u0027$y\u003dx$\u0027)",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "title": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 389.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
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          }
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      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627960_-1477396098",
      "id": "20161101-195657_1336292109",
      "results": {
        "code": "SUCCESS",
        "msg": [
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\u003d\u003d 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      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "title": "Second line",
      "text": "%python\nplt.plot([3, 2, 1], label\u003dr\u0027$y\u003d3-x$\u0027)",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "editorMode": "ace/mode/python",
        "title": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 289.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
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        ]
      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627961_-1477780847",
      "id": "20161101-195937_907325325",
      "results": {
        "code": "SUCCESS",
        "msg": [
          {
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\u003d\u003d style\u003d\u0027width\u003dauto;height:auto\u0027\u003e\u003cdiv\u003e\n"
          }
        ]
      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "title": "Label axes",
      "text": "%python\nplt.xlabel(r\u0027$x$\u0027, fontsize\u003d20)\nplt.ylabel(r\u0027$y$\u0027, fontsize\u003d20)",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "editorMode": "ace/mode/python",
        "title": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 300.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
            }
          }
        ]
      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627962_-1476626600",
      "id": "20161101-200014_2113468597",
      "results": {
        "code": "SUCCESS",
        "msg": [
          {
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 style\u003d\u0027width\u003dauto;height:auto\u0027\u003e\u003cdiv\u003e\n"
          }
        ]
      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "title": "Add legend",
      "text": "%python\nplt.legend(loc\u003d\u0027upper center\u0027, fontsize\u003d20)",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "editorMode": "ace/mode/python",
        "title": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 86.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
            }
          }
        ]
      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627962_-1476626600",
      "id": "20161101-200141_1493024813",
      "results": {
        "code": "SUCCESS",
        "msg": [
          {
            "type": "HTML",
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\u003d\u003d style\u003d\u0027width\u003dauto;height:auto\u0027\u003e\u003cdiv\u003e\n"
          }
        ]
      },
      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
    },
    {
      "title": "Add title",
      "text": "%python\nplt.title(\u0027Inline plotting example\u0027, fontsize\u003d20)",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
      "config": {
        "colWidth": 12.0,
        "editorMode": "ace/mode/python",
        "title": true,
        "enabled": true,
        "results": [
          {
            "graph": {
              "mode": "table",
              "height": 300.0,
              "optionOpen": false,
              "keys": [],
              "values": [],
              "groups": [],
              "scatter": {}
            }
          }
        ]
      },
      "settings": {
        "params": {},
        "forms": {}
      },
      "apps": [],
      "jobName": "paragraph_1478123627963_-1477011349",
      "id": "20161101-200445_78775142",
      "results": {
        "code": "SUCCESS",
        "msg": [
          {
            "type": "HTML",
            "data": "\u003cdiv style\u003d\u0027width:auto;height:auto\u0027\u003e\u003cimg 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      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
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    {
      "text": "%md\n####(b) Using a single plot\nTo iteratively update a single plot, we can leverage Zeppelin\u0027s built-in Angular Display System. Currently this feature is only available for the `pyspark` interpreter for raster (png and jpg) formats. To enable this, we must set a special `angular` flag to `True` in our configuration:",
      "dateUpdated": "Nov 2, 2016 2:53:47 PM",
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      "apps": [],
      "jobName": "paragraph_1478123627963_-1477011349",
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        "msg": [
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            "data": "\u003ch4\u003e(b) Using a single plot\u003c/h4\u003e\n\u003cp\u003eTo iteratively update a single plot, we can leverage Zeppelin\u0027s built-in Angular Display System. Currently this feature is only available for the \u003ccode\u003epyspark\u003c/code\u003e interpreter for raster (png and jpg) formats. To enable this, we must set a special \u003ccode\u003eangular\u003c/code\u003e flag to \u003ccode\u003eTrue\u003c/code\u003e in our configuration.\u003c/p\u003e\n"
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      "dateCreated": "Nov 2, 2016 2:53:47 PM",
      "status": "READY",
      "errorMessage": "",
      "progressUpdateIntervalMs": 500
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    {
      "title": "First line (figure will be displayed here)",
      "text": "%pyspark\nimport matplotlib.pyplot as plt\nplt.close() # Added here to reset the plot when rerunning the paragraph\nz.configure_mpl(angular\u003dTrue, close\u003dFalse)\nplt.plot([1, 2, 3], label\u003dr\u0027$y\u003dx$\u0027)",
      "user": "anonymous",
      "dateUpdated": "Nov 2, 2016 2:55:37 PM",
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      "id": "20161101-200754_739212093",
      "results": {
        "code": "SUCCESS",
        "msg": [
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