CODEWITHSUNDEEP
bokeh
euri10
euri10

Reputation: 2626

basic bokeh Bar chart

In[21]: from bokeh.charts import Bar, output_file, show
In[22]: dict = {'sec': {u'A': 10, u'B': 20}}
In[23]: df = pd.DataFrame(dict)
In[24]: df
Out[24]: 
   sec
A   10
B   20
In[25]: output_file("bar.html")
In[26]: p = Bar(df)
In[27]: show(p)

I'd like a bar chart with A and B the labels, the 2 bars of size 10 & 20: enter image description here

This example renders nothing.

I tried various variations with values=, labels= etc but it seems data is always aggregated by default (agg='sum')

Is Bar object too high level to plot what I'd like (2 bars, size 10 & 20 named A and B ) or am I using the object incorrectly ? Has the DataFrame I'm using the wrong 'format', should i put the index in a column ? if someone could provide an exemple of that very simple chart that would be awesome !

Edit: got it working with this, too bad index of the DataFrame cant be the labels, that seemed logical to me :)

import pandas as pd
from bokeh.charts import Bar
from bokeh.io import output_notebook, show
output_notebook()
dict = {'values': {u'A': 10, u'B': 20}}
df = pd.DataFrame(dict)
df['label'] = df.index
df
p = Bar(df, values='values',label='label')
show(p)

Upvotes: 11

Views: 19420

Answers (3)

bigreddot
bigreddot

Reputation: 34568

The other answers are outdated. The bokeh.charts API has been deprecated and removed, it should no longer be used. For basic (and not-so-basic) bar charts, users should now use the stable bokeh.plotting API as described in Handling Categorical Data. As an example:

from bokeh.io import show, output_file
from bokeh.plotting import figure

output_file("bars.html")

fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']

p = figure(x_range=fruits, plot_height=250, title="Fruit Counts")
p.vbar(x=fruits, top=[5, 3, 4, 2, 4, 6], width=0.9)

p.xgrid.grid_line_color = None
p.y_range.start = 0

show(p)

Which yields:

enter image description here

There are many more examples in the User's Guide link above showing how to achieve sorted, colormapped, stacked, grouped and nested bars, or work directly from Pandas DataFrames and GroupBys.

Upvotes: 22

bob-in-columbia
bob-in-columbia

Reputation: 85

tk's answer gave me a run error. I added an import for plotting and changed the last statement from save to show. This worked for me.

from bokeh.plotting import figure, show, output_file
from bokeh.charts import Bar

import pandas as pd
dict = {'values':[10,20], 'names':['A','B']}
df = pd.DataFrame(dict)

p = Bar(df, 'names', values='values', title="test chart")
show(p)

Upvotes: -1

tk.
tk.

Reputation: 332

if you look at Bokeh docs you see that Bar aggregates data. So easier is to better redifine your dataframe. There may be other widgets than Bar to work with, but at least example below is quite easy to understand, and more importantly works:

from bokeh.charts import Bar
from bokeh.io import save
import pandas as pd
dict = {'values':[10,20], 'names':['A','B']}
df = pd.DataFrame(dict)

p = Bar(df, 'names', values='values', title="test chart")
save(p,'test3.html')

I let you do all the styling you need.

Hope this helps, t.

Upvotes: 0

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