问题
I came across this discussion (from a year ago): https://github.com/bokeh/bokeh/issues/2392
I also saw the white screen without any errors..and then i tried to take a small subset of 2 columns and tried the below:
Since pandas just gets a bunch of rows with empty data in there as well, I tried dropna.. this resulted in there being no data at all. So instead I just specified the rows that should go into the df (hence the df = df.head(n=19) line)
import pandas as pd
from bokeh.plotting import figure, output_file, show
df = pd.read_excel(path,sheetname,parse_cols="A:B")
df = df.head(n=19)
print(df)
rtngs = ['iAAA','iAA+','iAA','iAA-','iA+','iA','iA-','iBBB+','iBBB','iBBB-','iBB+','iBB','iBB-','iB+','iB','iB-','NR','iCCC+']
x= df['Score']
output_file("line.html")
p = figure(plot_width=400, plot_height=400, x_range=(0,100),y_range=rtngs)
# add a circle renderer with a size, color, and alpha
p.circle(df['Score'], df['Rating'], size=20, color="navy", alpha=0.5)
# show the results
#output_notebook()
show(p)
df:
Rating Score
0 iAAA 64.0
1 iAA+ 33.0
2 iAA 7.0
3 iAA- 28.0
4 iA+ 36.0
5 iA 62.0
6 iA- 99.0
7 iBBB+ 10.0
8 iBBB 93.0
9 iBBB- 91.0
10 iBB+ 79.0
11 iBB 19.0
12 iBB- 95.0
13 iB+ 26.0
14 iB 9.0
15 iB- 26.0
16 NR 49.0
17 iCCC+ 51.0
18 iAAA 18.0
The above is showing me an output within the notebook, but still throws : ValueError: Out of range float values are not JSON compliant
And also it doesn't (hence?) produce the output file as well. How do I get rid of this error for this small subset? Is it related to NaN values? Would that also solve the 'white screen of death' issue for the larger dataset?
Thanks vm for taking a look!
In case you would like to see the entire error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-12-4fa6b88aa415> in <module>()
16 # show the results
17 #output_notebook()
---> 18 show(p)
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\io.py in show(obj, browser, new)
300 if obj not in _state.document.roots:
301 _state.document.add_root(obj)
--> 302 return _show_with_state(obj, _state, browser, new)
303
304
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\io.py in _show_with_state(obj, state, browser, new)
310
311 if state.notebook:
--> 312 comms_handle = _show_notebook_with_state(obj, state)
313 shown = True
314
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\io.py in _show_notebook_with_state(obj, state)
334 comms_target = make_id()
335 publish_display_data({'text/html': notebook_div(obj, comms_target)})
--> 336 handle = _CommsHandle(get_comms(comms_target), state.document, state.document.to_json())
337 state.last_comms_handle = handle
338 return handle
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\document.py in to_json(self)
792 # this is a total hack to go via a string, needed because
793 # our BokehJSONEncoder goes straight to a string.
--> 794 doc_json = self.to_json_string()
795 return loads(doc_json)
796
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\document.py in to_json_string(self, indent)
785 }
786
--> 787 return serialize_json(json, indent=indent)
788
789 def to_json(self):
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\site-packages\bokeh\core\json_encoder.py in serialize_json(obj, encoder, indent, **kwargs)
97 indent = 2
98
---> 99 return json.dumps(obj, cls=encoder, allow_nan=False, indent=indent, separators=separators, sort_keys=True, **kwargs)
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\json\__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
235 check_circular=check_circular, allow_nan=allow_nan, indent=indent,
236 separators=separators, default=default, sort_keys=sort_keys,
--> 237 **kw).encode(obj)
238
239
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\json\encoder.py in encode(self, o)
197 # exceptions aren't as detailed. The list call should be roughly
198 # equivalent to the PySequence_Fast that ''.join() would do.
--> 199 chunks = self.iterencode(o, _one_shot=True)
200 if not isinstance(chunks, (list, tuple)):
201 chunks = list(chunks)
C:\Users\x\AppData\Local\Continuum\Anaconda3\lib\json\encoder.py in iterencode(self, o, _one_shot)
255 self.key_separator, self.item_separator, self.sort_keys,
256 self.skipkeys, _one_shot)
--> 257 return _iterencode(o, 0)
258
259 def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
ValueError: Out of range float values are not JSON compliant
回答1:
I had the same error and I debugged the problem: I had NaN values in my plotted dataset and bokeh's serialize_json() function (in /core/json_encoder.py) does not allow NaN values (I don't know why...). In the return part of this function there is the allow_nan=False argument in json.dumps() :(( The problem occurs only at the io part of bokeh process when the output file is generated (it calls the above serialize_json() function).
So you have to replace NaN values in your dataframe, eg.:
df = df.fillna('')
Nice day! :)
回答2:
NaN support will be better supported when this Pull Request to add a binary array serialization option is merged. This should be available in Bokeh 0.12.4 in January 2017. Bokeh does not use allow_nan in the python JSON encoder, because that is not standard — nan and inf are not part of the official JSON specification (an egregious oversight IMO, but out of our control)
回答3:
Well it isn't exactly an answer to your question it's more like my experience working with bokeh for a week. In my case trying to make a plot like the Texas example from bokeh..... After a lot of frustration i noticed that bokeh or json or whatever when encounters the first value of the list (myList) to be plotted to be a NaN it refuses to plot giving the message
ValueError: Out of range float values are not JSON compliant
if i change the first value of the list (myList[0]) to float it works fine even if it contains NaN's to other positions. Taking this in account someone who understands how these things work will propose an answer. Mine is to restruct your data so that the first value isn't a nan.
回答4:
After removing the NAN values, there might be infinite value,
Trace the whole dataset it might have some infinite values as inf remove those infinite values some how, then it should work.
df['column'].describe()
then if you find any inf value remove those rows with
df = df[~df.isin([np.nan, np.inf, -np.inf]).any(1)]
reference: solution here
回答5:
I bumped into this problem and I realized it was happening because one column of my Dataframe was filled only with NaNs.
You could instead put it to another value, e.g.:
df['column'] = np.zeros(len(df))
来源：https://stackoverflow.com/questions/38821132/bokeh-valueerror-out-of-range-float-values-are-not-json-compliant