I am adapting this answer for my case, where I want an interactive, standalone graph where the slider selects which column of the data to plot in a bar chart. (Standalone is crucial, I cannot run a Bokeh server, thus the need for JavaScript callbacks.)
The data is a rectangle of floats with 100 rows in each of the 38 columns, which all have string labels like '40'
etc. (This is how pandas .read_csv()
handles numerics in the header by default.) Here is a sample from the top left corner (3x3, plus the row and column labels):
# , 40, 41, 42,
1.00000, 1.00000, 0.99287, 0.98489,
2.00000, 1.00000, 0.99348, 0.98626,
3.00000, 1.00000, 0.99433, 0.98922,
The code below produces the graph for the first column but does not update the graph upon moving the slider.
By poking at it, I suspect the issue is with the JavaScript code, though ColumnDataSource remains a bit mysterious to me. (A more straightforward dictionary of numeric column labels to lists of the numbers in the column does not work as datasource_available
, though corresponds to the linked answer's use case.)
datadf = pd.read_csv('male_survival_by_pctile.csv')
datadf.set_index('# ',inplace=True)
years = range(40,77)
data = {}
data_available = {}
for year in years:
data[year] = {'top':datadf[str(year)],'x':range(1,101)}
data_available = ColumnDataSource.from_df(datadf)
from bokeh.core.properties import field
from bokeh.io import curdoc, output_notebook, show
from bokeh.layouts import layout, column
from bokeh.models import (ColumnDataSource, HoverTool, SingleIntervalTicker,
Slider, Button, Label, CustomJS)
from bokeh.plotting import figure
output_notebook()
source_visible = ColumnDataSource(data=dict(x=range(1,101),top=data_available[str(years[0])]))
source_available = ColumnDataSource(data=data_available)
plot = figure(output_backend="webgl")
plot.xaxis.ticker = SingleIntervalTicker(interval=.01)
plot.xaxis.axis_label = "Income percentile"
plot.yaxis.ticker = SingleIntervalTicker(interval=.05)
plot.yaxis.axis_label = "Survival rate"
label = Label(x=1.1, y=18, text=str(years[0]), text_font_size='70pt', text_color='#eeeeee')
plot.add_layout(label)
plot.vbar(top='top',x='x',width=1,source=source_visible)
slider = Slider(start=years[0], end=years[-1], value=years[0], step=1, title="Age")
slider.callback = CustomJS(
args=dict(source_visible=source_visible,
source_available=source_available), code="""
var selected_function = cb_obj.get('value').toString();
// Get the data from the data sources
var data_visible = source_visible.get('data');
var data_available = source_available.get('data');
// Change bar height to the selected value
data_visible.top = data_available[selected_function];
// Update the plot
source_visible.trigger('change');
""")
layout = column(slider, plot)
show(layout)