How do I create a Bokeh Select menu for a line plot for an indeterminate number of options? - python-3.x

Question

I've been working on getting a select menu and Bokeh plot up and running on a dataset I'm working with. The dataset can be found here. I have no experience with JavaScript, but I believe my select menu isn't connected/-ing to my plot. Therefore, I have a plot outline, but no data displayed. As I run the script from the console with bokeh serve --show test.py, I get the first 7 notifications in my JS console. The last three (those in the red bracket in the screenshot) occur when I try and change to a different item in my select menu.
Goal: Display the plot of data for rows those id number ('ndc' in this example) is selected in the Select menu.
Here's my code (modified from this post) that I used to get started. This one was also used, as were a handful of others, and the Bokeh documentation itself.
import pandas as pd
from bokeh.io import curdoc, output_notebook, output_file
from bokeh.layouts import row, column
from bokeh.models import Select, DataRange1d, ColumnDataSource
from bokeh.plotting import figure
# output_notebook()
output_file('test.html')
def get_dataset(src, drug_id):
src.drop('Unnamed: 0', axis = 1, inplace = True)
df = src[src.ndc == drug_id].copy()
df['date'] = pd.to_datetime(df['date'])
df = df.set_index(['date'])
df.sort_index(inplace=True)
source = ColumnDataSource(data=df)
return source
def make_plot(source, title):
plot = figure(plot_width=800, plot_height = 800, tools="", x_axis_type = 'datetime', toolbar_location=None)
plot.xaxis.axis_label = 'Time'
plot.yaxis.axis_label = 'Price ($)'
plot.axis.axis_label_text_font_style = 'bold'
plot.x_range = DataRange1d(range_padding = 0.0)
plot.grid.grid_line_alpha = 0.3
plot.title.text = title
plot.line(x= 'date', y='nadac_per_unit', source=source)
return plot
def update_plot(attrname, old, new):
ver = vselect.value
plot.title.text = "Drug Prices"
src = get_dataset(df, ver)
source.date.update(src.date)
df = pd.read_csv('data/plotting_data.csv')
ver = '54034808' #Initial id number
cc = df['ndc'].astype(str).unique() #select-menu options
vselect = Select(value=ver, title='Drug ID', options=sorted((cc)))
source = get_dataset(df, ver)
plot = make_plot(source, "Drug Prices")
vselect.on_change('value', update_plot)
controls = row(vselect)
curdoc().add_root(row(plot, controls))

Answer 1

There were some problems in your code:
You want to drop the Unnamed: 0 column. This can only be done once and when you try this again it will throw an error since this column does not exist anymore.
The way you tried to filter the dataframe didn't work and would result in an empty dataframe. You can select rows based on a column value like this: df.loc[df['column_name'] == some_value]
Updating the ColumnDataSource object can be done by replacing source.data with the new data.
import pandas as pd
from bokeh.io import curdoc, output_notebook, output_file
from bokeh.layouts import row, column
from bokeh.models import Select, DataRange1d, ColumnDataSource
from bokeh.plotting import figure
output_notebook()
output_file('test.html')
def get_dataset(src, drug_id):
src.drop('Unnamed: 0', axis = 1, inplace = True)
df = src.loc[src['ndc'] == int(drug_id)]
df['date'] = pd.to_datetime(df['date'])
df = df.set_index(['date'])
df.sort_index(inplace=True)
source = ColumnDataSource(data=df)
return source
def make_plot(source, title):
plot = figure(plot_width=800, plot_height = 800, tools="", x_axis_type = 'datetime', toolbar_location=None)
plot.xaxis.axis_label = 'Time'
plot.yaxis.axis_label = 'Price ($)'
plot.axis.axis_label_text_font_style = 'bold'
plot.x_range = DataRange1d(range_padding = 0.0)
plot.grid.grid_line_alpha = 0.3
plot.title.text = title
plot.line(x= 'date', y='nadac_per_unit', source=source)
return plot
def update_plot(attrname, old, new):
ver = vselect.value
df1 = df.loc[df['ndc'] == int(new)]
df1['date'] = pd.to_datetime(df1['date'])
df1 = df1.set_index(['date'])
df1.sort_index(inplace=True)
newSource = ColumnDataSource(df1)
source.data = newSource.data
df = pd.read_csv('data/plotting_data.csv')
ver = '54034808' #Initial id number
cc = df['ndc'].astype(str).unique() #select-menu options
vselect = Select(value=ver, title='Drug ID', options=sorted((cc)))
source = get_dataset(df, ver)
plot = make_plot(source, "Drug Prices")
vselect.on_change('value', update_plot)
controls = row(vselect)
curdoc().add_root(row(plot, controls))