Just tried to import pixiedust and hit the error. I tried restarting the kernel still the same error.

ImportErrorTraceback (most recent call last)
<ipython-input-1-fa75a171b8de> in <module>()
      1 get_ipython().system(u'pip install --user --upgrade --quiet pixiedust')
----> 2 import pixiedust
      3 
      4 jars = ["http://central.maven.org/maven2/org/apache/kafka/kafka-clients/0.9.0.0/kafka-clients-0.9.0.0.jar",
      5         "http://central.maven.org/maven2/org/apache/kafka/kafka_2.10/0.9.0.0/kafka_2.10-0.9.0.0.jar",

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/__init__.pyc in <module>()
     29 uninstallPackage=packageManager.uninstallPackage
     30 
---> 31 import display
     32 import services
     33 

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/display/__init__.py in <module>()
     16 
     17 from .display import *
---> 18 import chart,graph,table,tests,download
     19 from pixiedust.utils.printEx import *
     20 import traceback

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/display/chart/__init__.py in <module>()
     15 # -------------------------------------------------------------------------------
     16 
---> 17 from .barChartDisplay import BarChartDisplay
     18 from .lineChartDisplay import LineChartDisplay
     19 from .scatterPlotDisplay import ScatterPlotDisplay

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/display/chart/barChartDisplay.py in <module>()
     16 
     17 from .display import ChartDisplay
---> 18 from .mpld3ChartDisplay import Mpld3ChartDisplay
     19 import matplotlib.pyplot as plt
     20 import numpy as np

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/display/chart/mpld3ChartDisplay.py in <module>()
     15 # -------------------------------------------------------------------------------
     16 
---> 17 from .baseChartDisplay import BaseChartDisplay
     18 from .display import ChartDisplay
     19 from .plugins.chart import ChartPlugin

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/pixiedust/display/chart/baseChartDisplay.py in <module>()
     22 from pyspark.sql.types import StructType
     23 import matplotlib.cm as cm
---> 24 import matplotlib.pyplot as plt
     25 import mpld3
     26 import mpld3.plugins as plugins

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/pyplot.py in <module>()
    112 
    113 from matplotlib.backends import pylab_setup
--> 114 _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
    115 
    116 _IP_REGISTERED = None

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/backends/__init__.pyc in pylab_setup()
     30     # imports. 0 means only perform absolute imports.
     31     backend_mod = __import__(backend_name,
---> 32                              globals(),locals(),[backend_name],0)
     33 
     34     # Things we pull in from all backends

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/backends/backend_tkagg.py in <module>()
      4 
      5 from matplotlib.externals import six
----> 6 from matplotlib.externals.six.moves import tkinter as Tk
      7 from matplotlib.externals.six.moves import tkinter_filedialog as FileDialog
      8 

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/externals/six.pyc in load_module(self, fullname)
    197         mod = self.__get_module(fullname)
    198         if isinstance(mod, MovedModule):
--> 199             mod = mod._resolve()
    200         else:
    201             mod.__loader__ = self

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/externals/six.pyc in _resolve(self)
    111 
    112     def _resolve(self):
--> 113         return _import_module(self.mod)
    114 
    115     def __getattr__(self, attr):

/gpfs/fs01/user/xxxxxx/.local/lib/python2.7/site-packages/matplotlib/externals/six.pyc in _import_module(name)
     78 def _import_module(name):
     79     """Import module, returning the module after the last dot."""
---> 80     __import__(name)
     81     return sys.modules[name]
     82 

/usr/local/src/bluemix_jupyter_bundle.v22/notebook/lib/python2.7/lib-tk/Tkinter.py in <module>()
     37     # Attempt to configure Tcl/Tk without requiring PATH
     38     import FixTk
---> 39 import _tkinter # If this fails your Python may not be configured for Tk
     40 tkinter = _tkinter # b/w compat for export
     41 TclError = _tkinter.TclError

ImportError: No module named _tkinter

Edit Display(API) topic to explain how to work with chart options

mpld3 uses Python json library which does not support serialization of Decimal types.

Potential fixes:

1. Override default json encoder (if possible)
2. Convert all incoming Decimals to Doubles (may cause issues with precision)

Matplotlib allows us to give specific text as titles. Pixiedust should offer same.

add/edit help topic

The charts appear to be the same when this option is enabled or disabled.

I have a dataframe with column A, B and C.
I want A to be the x-axis.
I want B to be the size of the bar or the height of the line.
I want C to be the category, to have an other bar or an other line for each C attribute with a different color.

From the options of PixieDust, I can see the "keys" and "values" but I see nothing for the categories.

Exploring some of the sample notebooks I realized that more often than not the default options don't work for many chart types. For example, pick million dollar homes and google as the renderer. An error is displayed incompatible data table: Error: table contains more columns than expected. If I want to change the chart options I have to manually remove each pre-selected field, which is rather labor intensive for data sets with many fields. A reset/clear button that resets the options would be nice to have.

Not part of 1.0, make sure Scala mentions explain the feature, (link to video demo?) and specify that it's coming soon.

It's currently possible to only specify a key (but no value) in the options. I can't think of a scenario where this kind of setting would result in a useful chart. Can you?

Posted on SO: http://stackoverflow.com/questions/41990549/dsx-images-generated-by-pixiedust-display-command-are-ugly

Expected behavior

Plot raw data via line and scatter plot. When user selects line or scatter, do not display aggregate option. For scatter in matplotlib, Options dialog does not show aggregtation.

Actual behavior

Currently pixiedust 'Options' dialog aggregates values into SUM, AVG, MIN, MAX and COUNT which are helpful with bar, pie and histograms but not for scatter and line, in fact that changes the course of analysis as raw data is also important to look at.

Steps to reproduce the behavior

Select type of chart, open Options dialog.

I've tried Chrome and Safari on Mac.

It would be nice to select plotting options before rendering since it can take a while to render large amounts of data. Sitting around waiting for the default behavior to finish before being able to select options. Perhaps a modal window can pop up when you select the chart option before it begins.

Currently, row with a complex type (e.g nested structure) are not handled correctly by the chart option dialog. The schema tab of table visualization should also display nested structure more clearly (currently display as json)
@markwatsonatx @vabarbosa

Hi,

I am working in Zeppelin, it has support to visualize that but its visualization is limited. Is it possible to add pixiedust to Zeppelin, i had tried to integrate it Zeppelin but when i call display(dataframe). It display the following:

{"data": {"text/plain": "<IPython.core.display.HTML object>", "text/html": "\n<script>\n //Marker 706ab2be\n setTimeout(function(){\n var cells=IPython.notebook.get_cells().filter(function(cell){\n if(!cell.output_area || !cell.output_area.outputs){\n return false;\n }\n return cell.output_area.outputs.filter(function(output){\n if (output.output_type===\"display_data\"&&output.data&&output.data[\"text/html\"]){\n return output.data[\"text/html\"].includes(\"//Marker 706ab2be\")\n }\n return false;\n }).length > 0;\n });\n if(cells.length>0){\n var cell=cells[0];\n var cellId=cell.cell_id;\n var cellMetadata=cell._metadata.pixiedust;\n //cell.output_area.clear_output(false, true);\n var old_msg_id = cell.last_msg_id;\n if (old_msg_id) {\n cell.kernel.clear_callbacks_for_msg(old_msg_id);\n }\n var snifferOptions = [];\n \n snifferOptions.push({'nostore_bokeh':!!window.Bokeh})\n \n \n \n \n !\nfunction() {\n cellId = typeof cellId === \"undefined\" ? \"\" : cellId;\n var curCell=IPython.notebook.get_cells().filter(function(cell){\n return cell.cell_id==\"cellId\".replace(\"cellId\",cellId);\n });\n curCell=curCell.length>0?curCell[0]:null;\n console.log(\"curCell\",curCell);\n var startWallToWall;\n //Resend the display command\n var callbacks = {\n shell : {\n payload : {\n set_next_input : function(payload){\n if (curCell){\n curCell._handle_set_next_input(payload);\n }\n }\n }\n },\n iopub:{\n output:function(msg){\n console.log(\"msg\", msg);\n if (true){\n curCell.output_area.handle_output.apply(curCell.output_area, arguments);\n curCell.output_area.outputs=[];\n return;\n }\n var msg_type=msg.header.msg_type;\n var content = msg.content;\n var executionTime = $(\"#execution706ab2be\");\n if(msg_type===\"stream\"){\n $('#wrapperHTML706ab2be').html(content.text);\n }else if (msg_type===\"display_data\" || msg_type===\"execute_result\"){\n var html=null;\n if (!!content.data[\"text/html\"]){\n html=content.data[\"text/html\"];\n }else if (!!content.data[\"image/png\"]){\n html=html||\"\";\n html+=\"<img src='data:image/png;base64,\" +content.data[\"image/png\"]+\"'></img>\";\n }\n \n if (!!content.data[\"application/javascript\"]){\n try {\n eval(content.data[\"application/javascript\"]);\n } catch(err) {\n curCell.output_area.handle_output.apply(curCell.output_area, arguments);\n } \n return;\n }\n \n if (html){\n try{\n $('#wrapperHTML706ab2be').html(html);\n }catch(e){\n console.log(\"Invalid html output\", e, html);\n $('#wrapperHTML706ab2be').html( \"Invalid html output. <pre>\" \n + html.replace(/>/g,'&gt;').replace(/</g,'&lt;').replace(/\"/g,'&quot;') + \"<pre>\");\n }\n\n if(curCell&&curCell.output_area&&curCell.output_area.outputs){\n setTimeout(function(){\n var data = JSON.parse(JSON.stringify(content.data));\n if(!!data[\"text/html\"])data[\"text/html\"]=html;\n function savedData(data){\n \n var markup='<style type=\"text/css\">.pd_warning{display:none;}</style>';\n markup+='<div class=\"pd_warning\"><em>Hey, there\\'s something awesome here! To see it, open this notebook outside GitHub, in a viewer like Jupyter</em></div>';\n nodes = $.parseHTML(data[\"text/html\"], null, true);\n var s = $(nodes).wrap(\"<div>\").parent().find(\".pd_save\").not(\".pd_save .pd_save\")\n s.each(function(){\n var found = false;\n if ( $(this).attr(\"id\") ){\n var n = $(\"#\" + $(this).attr(\"id\"));\n if (n.length>0){\n found=true;\n n.each(function(){\n $(this).addClass(\"is-viewer-good\");\n });\n markup+=n.wrap(\"<div>\").parent().html();\n }\n }else{\n $(this).addClass(\"is-viewer-good\");\n }\n if (!found){\n markup+=$(this).parent().html();\n }\n });\n data[\"text/html\"] = markup;\n return data;\n }\n curCell.output_area.outputs.push({\"data\": savedData(data),\"metadata\":content.metadata,\"output_type\":msg_type});\n },2000);\n }\n }\n }else if (msg_type === \"error\") {\n require(['base/js/utils'], function(utils) {\n var tb = content.traceback;\n console.log(\"tb\",tb);\n if (tb && tb.length>0){\n var data = tb.reduce(function(res, frame){return res+frame+'\\\\n';},\"\");\n console.log(\"data\",data);\n data = utils.fixConsole(data);\n data = utils.fixCarriageReturn(data);\n data = utils.autoLinkUrls(data);\n $('#wrapperHTML706ab2be').html(\"<pre>\" + data +\"</pre>\");\n }\n });\n }\n\n //Append profiling info\n if (executionTime.length > 0 && $(\"#execution706ab2be\").length == 0 ){\n $('#wrapperHTML706ab2be').append(executionTime);\n }else if (startWallToWall && $(\"#execution706ab2be\").length > 0 ){\n $(\"#execution706ab2be\").append($(\"<div/>\").text(\"Wall to Wall time: \" + ( (new Date().getTime() - startWallToWall)/1000 ) + \"s\"));\n }\n }\n }\n }\n \n if (IPython && IPython.notebook && IPython.notebook.session && IPython.notebook.session.kernel){\n var command = \",cell_id='cellId'\".replace(\"cellId\",cellId);\n function addOptions(options){\n function getStringRep(v) {\n return \"'\" + v + \"'\";\n }\n for (var key in (options||{})){\n var value = options[key];\n var hasValue = value != null && typeof value !== 'undefined' && value !== '';\n var replaceValue = hasValue ? (key+\"=\" + getStringRep(value) ) : \"\";\n var pattern = (hasValue?\"\":\",\")+\"\\\\s*\" + key + \"\\\\s*=\\\\s*'(\\\\\\\\'|[^'])*'\";\n var rpattern=new RegExp(pattern);\n var n = command.search(rpattern);\n if ( n >= 0 ){\n command = command.replace(rpattern, replaceValue);\n }else if (hasValue){\n var n = command.lastIndexOf(\")\");\n command = [command.slice(0, n), (command[n-1]==\"(\"? \"\":\",\") + replaceValue, command.slice(n)].join('')\n } \n }\n }\n if(typeof cellMetadata != \"undefined\" && cellMetadata.displayParams){\n addOptions(cellMetadata.displayParams);\n addOptions({\"showchrome\":\"true\"});\n }else if ('False'=='True' && curCell && curCell._metadata.pixiedust ){\n addOptions(curCell._metadata.pixiedust.displayParams || {} );\n }\n addOptions({});\n \n \n \n for (var o in snifferOptions){\n addOptions(snifferOptions[o]);\n }\n \n \n var pattern = \"\\\\w*\\\\s*=\\\\s*'(\\\\\\\\'|[^'])*'\";\n var rpattern=new RegExp(pattern,\"g\");\n var n = command.match(rpattern);\n var displayParams={}\n for (var i = 0; i < n.length; i++){\n var parts=n[i].split(\"=\");\n var key = parts[0].trim();\n var value = parts[1].trim()\n if (!key.startsWith(\"nostore_\") && key != \"showchrome\" && key != \"prefix\" && key != \"cell_id\"){\n displayParams[key] = value.substring(1,value.length-1);\n }\n }\n if(curCell&&curCell.output_area){\n curCell._metadata.pixiedust = curCell._metadata.pixiedust || {}\n curCell._metadata.pixiedust.displayParams=displayParams\n curCell.output_area.outputs=[];\n var old_msg_id = curCell.last_msg_id;\n if (old_msg_id) {\n curCell.kernel.clear_callbacks_for_msg(old_msg_id);\n }\n }else{\n console.log(\"couldn't find the cell\");\n }\n $('#wrapperJS706ab2be').html(\"\")\n $('#wrapperHTML706ab2be').html('<div style=\"width:100px;height:60px;left:47%;position:relative\"><i class=\"fa fa-circle-o-notch fa-spin\" style=\"font-size:48px\"></i></div>'+\n '<div style=\"text-align:center\">Loading your data. Please wait...</div>');\n startWallToWall = new Date().getTime();\n \n console.log(\"Running command2\",command);\n IPython.notebook.session.kernel.execute(command, callbacks, {silent:true,store_history:false,stop_on_error:true});\n }\n}\n()\n }else{\n alert(\"An error occurred, unable to access cell id\");\n }\n },500);\n</script>"}, "metadata": {}}

Any help related to this issue? Or anyone had tried pixiedust with Zeppelin?

Hola! @rajrsingh has created a ZenHub account for the ibm-cds-labs organization. ZenHub is the only project management tool integrated natively in GitHub – created specifically for fast-moving, software-driven teams.

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export graphics to SVG for editing in a graphics program -- changing fonts, moving overlapping text, etc.

Add topic with command and info

Expected behavior

Actual behavior

Steps to reproduce the behavior

Would be nice to have axis on log10 scale.

@vabarbosa : Get following error in the browser console:
main.min.js:23119 Couldn't process kernel message TypeError: Failed to execute 'appendChild' on 'Node': parameter 1 is not of type 'Node'.

Add topic re:

• data download options
  -Stash to Cloudant is currently Beta feature
  -cover download SVG too

Expected behavior

Proper support for pixiedust? and help(pixiedust)

Steps to reproduce the behavior

import pixiedust and run pixiedust? or help(pixiedust) or help(pixiedust.packageManager) ...

Expected behavior

Actual behavior

Steps to reproduce the behavior

Example: I opened the million dollar homes sample notebook. Visualization wasn't working because

1. I was using an unsupported browser

2. I didn't know that for mapbox the chart options need to be customized (an access token must be provided)

3. I didn't know where to obtain the token

Expected behavior

sampleData() should link to the curated public sample data set so a user can make an informed decision which set to pick:

Id 	Name 	Topic 	Publisher
1 	[car performance data](link-to-public-data-set) 	transportation 	IBM

Even better, let the user somehow pick from any of the public data sets available on the exchange.

Actual behavior (0.80)

pixiedust.sampleData() currently displays

Id 	Name 	Topic 	Publisher
1 	Car performance data 	transportation 	IBM

Steps to reproduce the behavior

import pixiedust
pixiedust.sampleData()

Expected behavior

When user clicks on Options dialog, display type of chart (or even type of renderer, optional though as it is seen on the right hand side) as the drop down of type of chart does not store last selected type of chart.

Actual behavior

Options does not display type of chart, so it is difficult to remember most suitable aggregate, x and y values for the chart.

Steps to reproduce the behavior

Select type of chart. Click Options button.

As a <user type>, I want to <task> so that <goal> (make this the title)

Expected behavior

Actual behavior

Steps to reproduce the behavior

Expected behavior

Actual behavior

Steps to reproduce the behavior

When passing a DataFrame from Python to Scala using the Scala Bridge, the DataFrame comes across as null in Scala.

These stories will highlight Mapbox, CartoDB, geopandas, etc.

Expected behavior

Actual behavior

Steps to reproduce the behavior

I get the following errors upon installation:

>>> import pixiedust
>>> Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/esafak/Library/Python/3.5/lib/python/site-packages/pixiedust/__init__.py", line 19, in <module>
    import packageManager
ImportError: No module named 'packageManager'

>>> from pixiedust.packageManager import PackageManager
>>> Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/esafak/Library/Python/3.5/lib/python/site-packages/pixiedust/__init__.py", line 19, in <module>
    import packageManager
ImportError: No module named 'packageManager'

I think you have an issue with relative imports.

As a data-scientist, scala Variables from one %%scala cell are need to be accessible in other %%scala cell so that the code looks cleaner.

Expected behavior

%%scala Should not loose context or variables defined in other or previous %%scala cells.

Actual behavior

%%scala __df.show()
Output:-
pixiedustRunner.scala:20: error: not found: value __df
__df.show()
^
pixiedustRunner.scala:22: error: not found: value __df
Map( "__df"->__df )
^
two errors found
In [ ]:

Steps to reproduce the behavior

Create a new notebook with Python
Run below in one cell
%%scala
import org.apache.spark.sql._

print(sc.version)

val sqlContext = new org.apache.spark.sql.SQLContext(sc)

val (__df) = sqlContext.read.json("people.json")

__df.show()

Next Cell, Use Python display() to visualize __df
display(__df)

Now in next cell run below:-
%%scala __df.show()

Thanks,
Charles.

I'd like to be able to set histogram bin sizes in some way.

I've tried several data sets using PD v0.80 on DSX.

in [6] pixiedust.sampleData(6)

Downloading 'Million dollar home sales in NE Mass late 2016' from https://openobjectstore.mybluemix.net/misc/milliondollarhomes.csv

Creating pySpark DataFrame for 'Million dollar home sales in NE Mass late 2016'. Please wait...

Even for a small data set like the one listed above (~100k) data frame creation never completes.

Fill in gaps in Developer section, specify (coming soon) within topic titles.
Review and align for what's ready in 1.0 release.

This might sound a bit nit-picky, but one thing I'd like to see changed would be to avoid using
from XX import *, like from pixidust.display import display in examples and documentation. I'm not sure what's in pixiedust (though I could look at the code), but there are probably a lot of modules that potentially have the same names as other graphing packages. Something better might be import pixiedust.display as pixd or just use the full path import pixiedust.diplay.

It would make it easier for folks to straight copy example code without worrying about namespace collisions.

Feel free to close this issue if you think I'm being an arse.

Expected behavior

Actual behavior

Steps to reproduce the behavior

See:

The full stacktrace:

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-19-1128de37cfc4> in <module>()
----> 1 get_ipython().run_cell_magic(u'scala', u'', u'\nprintln(bootstrap_servers_string)\n\nimport org.apache.spark.streaming.Duration\nimport org.apache.spark.streaming.Seconds\nimport org.apache.spark.streaming.StreamingContext\nimport com.ibm.cds.spark.samples.config.MessageHubConfig\nimport com.ibm.cds.spark.samples.dstream.KafkaStreaming.KafkaStreamingContextAdapter\nimport org.apache.kafka.common.serialization.Deserializer\nimport org.apache.kafka.common.serialization.StringDeserializer\n\nval kafkaProps = new MessageHubConfig\n\nkafkaProps.setConfig("bootstrap.servers", bootstrap_servers_string.toString())\nkafkaProps.setConfig("kafka.user.name", sasl_plain_username.toString())\nkafkaProps.setConfig("kafka.user.password", sasl_plain_password.toString())\nkafkaProps.setConfig("kafka.topic", messagehub_topic_name.toString())\nkafkaProps.setConfig("api_key", api_key.toString())\nkafkaProps.setConfig("kafka_rest_url", kafka_rest_url.toString())\n\nkafkaProps.createConfiguration()\n\nval ssc = new StreamingContext( sc, Seconds(2) )\n\nval stream = ssc.createKafkaStream[String, String, StringDeserializer, StringDeserializer](\n                     kafkaProps,\n                     List(kafkaProps.getConfig("kafka.topic"))\n                     );\n\nstream.print()\nssc.start()\nssc.awaitTermination()')

/usr/local/src/bluemix_jupyter_bundle.v22/notebook/lib/python2.7/site-packages/IPython/core/interactiveshell.pyc in run_cell_magic(self, magic_name, line, cell)
   2118             magic_arg_s = self.var_expand(line, stack_depth)
   2119             with self.builtin_trap:
-> 2120                 result = fn(magic_arg_s, cell)
   2121             return result
   2122 

<decorator-gen-125> in scala(self, line, cell)

/usr/local/src/bluemix_jupyter_bundle.v22/notebook/lib/python2.7/site-packages/IPython/core/magic.pyc in <lambda>(f, *a, **k)
    191     # but it's overkill for just that one bit of state.
    192     def magic_deco(arg):
--> 193         call = lambda f, *a, **k: f(*a, **k)
    194 
    195         if callable(arg):

/gpfs/fs01/user/s85d-88ebffb000cc3e-39ca506ba762/.local/lib/python2.7/site-packages/pixiedust/utils/scalaBridge.pyc in scala(self, line, cell)
    166                 runnerObject.callMethod("set" + key[0].upper() + key[1:], val["initValue"])
    167 
--> 168         varMap = runnerObject.callMethod("runCell")
    169 
    170         #capture the return vars and update the interactive shell

/gpfs/fs01/user/s85d-88ebffb000cc3e-39ca506ba762/.local/lib/python2.7/site-packages/pixiedust/utils/javaBridge.pyc in callMethod(self, methodName, *args)
    145                             break;
    146                 if match:
--> 147                     return m.invoke(self.jHandle, jMethodArgs)
    148 
    149         raise ValueError("Method {0} that matches the given arguments not found".format(methodName) )

/usr/local/src/spark160master/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
    811         answer = self.gateway_client.send_command(command)
    812         return_value = get_return_value(
--> 813             answer, self.gateway_client, self.target_id, self.name)
    814 
    815         for temp_arg in temp_args:

/usr/local/src/spark160master/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
     43     def deco(*a, **kw):
     44         try:
---> 45             return f(*a, **kw)
     46         except py4j.protocol.Py4JJavaError as e:
     47             s = e.java_exception.toString()

/usr/local/src/spark160master/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    306                 raise Py4JJavaError(
    307                     "An error occurred while calling {0}{1}{2}.\n".
--> 308                     format(target_id, ".", name), value)
    309             else:
    310                 raise Py4JError(

Py4JJavaError: An error occurred while calling o513.invoke.
: java.lang.NullPointerException
    at com.ibm.pixiedust.PixiedustScalaRun$.runCell(pixiedustRunner.scala:125)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:95)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:55)
    at java.lang.reflect.Method.invoke(Method.java:507)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:95)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:55)
    at java.lang.reflect.Method.invoke(Method.java:507)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:785)

The notebook:

https://apsportal.ibm.com/analytics/notebooks/c94ee063-dab3-4440-9b90-125347ff80af/view?access_token=1c752de564c7c2df3fe924ce4122e71e658e73ff64160c80b667844527a8df88

I can't get this notebook to render.

https://github.com/ibm-cds-labs/pixiedust/blob/master/notebook/Flight%20Predict%20with%20Pixiedust.ipynb

For fresh installation of pixiedust installPixiedustJar() needs ./data/libs to exist in the home directory otherwise fails with 'No such file or directory':

Cell code:
import pixiedust
pixiedust.installPackage("graphframes:graphframes:0")
pixiedust.printAllPackages()

Output:
Pixiedust database opened successfully
Pixiedust version 0.60

IOError Traceback (most recent call last)
in ()
----> 1 import pixiedust
2 pixiedust.installPackage("graphframes:graphframes:0")
3 pixiedust.printAllPackages()

/Users/chetnadwarade/pixiedust/pixiedust/init.py in ()
20 warnings.simplefilter("ignore")
21 #shortcut to logging
---> 22 import utils
23 import utils.pdLogging
24 logger = utils.pdLogging.getPixiedustLogger()

/Users/chetnadwarade/pixiedust/pixiedust/utils/init.py in ()
44
45 if copyFile:
---> 46 installPixiedustJar()

/Users/chetnadwarade/pixiedust/pixiedust/utils/init.py in installPixiedustJar()
32 def installPixiedustJar():
33 with pkg_resources.resource_stream(name, "resources/pixiedust.jar") as resJar:
---> 34 with open( jarFilePath, 'w+' ) as installedJar:
35 shutil.copyfileobj(resJar, installedJar)
36 print("Pixiedust runtime updated. Please restart kernel")

IOError: [Errno 2] No such file or directory: '/Users/chetnadwarade/data/libs/pixiedust.jar'

Expected behavior

Actual behavior

Steps to reproduce the behavior

Label name is missing for a section of the pie chart

Need to visualize a multi-series bar chart. A common requirement to visualize say, quarterly aggregated sales across year. Can this support be added.