Like the title says, I’m only seeing half of the expected y-value in hovertools, despite the bar showing the true value:
Here is my code:
from bokeh.charts import Bar, show
from bokeh.models import HoverTool
from bokeh.models.ranges import FactorRange
from bokeh.io import output_notebook
output_notebook()
zip_counts = pd.DataFrame(df.zipcode.value_counts())
hover = HoverTool(tooltips=[
('Count', "@y")
])
p = Bar(zip_counts, title="abc", width=800, tools=[hover])
p.x_range = FactorRange(factors=zip_counts.index.tolist())
show(p)
``
Data sample:
index zipcode
10019 3414
10003 3196
10001 2719
10011 2561
10014 2523
10002 2486
10036 2451
10009 2282
10013 1822
10012 1641
10018 1575
I know those column headers are counterintuitive but please look beyond it for now
Bryan
May 12, 2016, 5:51pm
2
Seems like a bug, can you file an issue on GitHub with this information?
Bryan
···
On May 12, 2016, at 18:45, [email protected] wrote:
Like the title says, I’m only seeing half of the expected y-value in hovertools, despite the bar showing the true value:
Here is my code:
from bokeh.charts import Bar, show
from bokeh.models import HoverTool
from bokeh.models.ranges import FactorRange
from bokeh.io import output_notebook
output_notebook()
zip_counts = pd.DataFrame(df.zipcode.value_counts())
hover = HoverTool(tooltips=[
('Count', "@y")
])
p = Bar(zip_counts, title="abc", width=800, tools=[hover])
p.x_range = FactorRange(factors=zip_counts.index.tolist())
show(p)
``
Data sample:
index zipcode
10019 3414
10003 3196
10001 2719
10011 2561
10014 2523
10002 2486
10036 2451
10009 2282
10013 1822
10012 1641
10018 1575
I know those column headers are counterintuitive but please look beyond it for now
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Nevermind, I’m just an idiot and didn’t read far enough in this post . Needed to use @height , not @y
Great, yes, bar does a lot of data manipulation behind the scene.
···
On 5/12/16 10:56 AM,
wrote:
[email protected]
Nevermind, I’m just an idiot and didn’t read far enough
in this post . Needed to use @height , not @y
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