http://git-wip-us.apache.org/repos/asf/zeppelin/blob/085efeb6/notebook/2C2AUG798/note.json ---------------------------------------------------------------------- diff --git a/notebook/2C2AUG798/note.json b/notebook/2C2AUG798/note.json deleted file mode 100644 index 23ab3df..0000000 --- a/notebook/2C2AUG798/note.json +++ /dev/null @@ -1,779 +0,0 @@ -{ - "paragraphs": [ - { - "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### virtu alenv\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:", - "user": "anonymous", - "dateUpdated": "Dec 17, 2016 3:33:25 PM", - "config": { - "tableHide": false, - "colWidth": 12.0, - "editorMode": "ace/mode/text", - "editorHide": true, - "enabled": true, - "results": [ - { - "graph": { - "mode": "table", - "height": 300.0, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - } - } - ], - "editorSetting": { - "language": "text", - "editOnDblClick": false - } - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "jobName": "paragraph_1478123627954_-1473548609", - "id": "20160614-174657_1772993700", - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "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\u003eMo st 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/virtual env_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" - } - ] - }, - "dateCreated": "Nov 2, 2016 2:53:47 PM", - "dateStarted": "Dec 17, 2016 3:33:25 PM", - "dateFinished": "Dec 17, 2016 3:33:25 PM", - "status": "FINISHED", - "progressUpdateIntervalMs": 500 - }, - { - "text": "%python\nimport matplotlib.pyplot as plt\nplt.plot([1, 2, 3])", - "dateUpdated": "Nov 2, 2016 2:53:47 PM", - "config": { - "colWidth": 12.0, - "editorMode": "ace/mode/python", - "enabled": true, - "results": [ - { - "graph": { - "mode": "table", - "height": 300.0, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - } - } - ] - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "jobName": "paragraph_1478123627958_-1475087605", - "id": "20161101-192232_289486976", - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "\u003cdiv style\u003d\u0027width:auto;height:auto\u0027\u003e\u003cimg 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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", - "config": { - "tableHide": false, - "colWidth": 12.0, - "editorMode": "ace/mode/markdown", - "editorHide": true, - "enabled": true, - "results": [ - { - "graph": { - "mode": "table", - "height": 300.0, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - } - } - ] - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "jobName": "paragraph_1478123627959_-1475472354", - "id": "20160614-174421_274483707", - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "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" - } - ] - }, - "dateCreated": "Nov 2, 2016 2:53:47 PM", - "status": "READY", - "errorMessage": "", - "progressUpdateIntervalMs": 500 - }, - { - "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", - "config": { - "colWidth": 12.0, - "editorMode": "ace/mode/scala", - "enabled": true, - "results": [ - { - "graph": { - "mode": "table", - "height": 300.0, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - } - } - ] - }, - "settings": { - "params": { - "f1": "defaultValue" - }, - "forms": {} - }, - "apps": [], - "jobName": "paragraph_1478123627959_-1475472354", - "id": "20160616-234947_579056637", - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "\u003cdiv 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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": {} - } - } - ] - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "jobName": "paragraph_1478123627960_-1477396098", - "id": 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