Qfyilyi

From a Pandas dataframe like the one below, I'm simply trying to create a multi_line plot plus HoverTool; however, I can't find any examples similar to my specific case. Here is my sample code:

import pandas as pd

import numpy as np



# Dataframe (just toy data, this will be an import of a much larger dataset)

index = ['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30', '2018-05-31', 

         '2018-06-30', '2018-07-31', '2018-08-31', '2018-09-30', '2018-10-31']



columns = ['Argentina', 'Turkey', 'Mexico']



np.random.seed(123)

data = np.random.rand(10, 3)



df = pd.DataFrame(index=index, columns=columns, data=data)

df.index = pd.to_datetime(df.index)

df.index.name = 'Date'



# Attempt at plot (obviously doesn't work)

from bokeh.plotting import figure

from bokeh.models import ColumnDataSource, HoverTool

from bokeh.io import output_notebook, show

output_notebook()



source = ColumnDataSource(df)



p = figure(plot_height=400)

p.multi_line(xs='Date', ys=columns, source=source)



p.add_tools(HoverTool(tooltips=[('Country', '@???'),

                                ('Date', '@Date'),

                                ('Value', '@???')]))



show(p)

Multi lines xs and ys should be a list of lists, that's why it didn't work.
I replaced the multiline for 3 normal lines and it should work fine now.
If you really want to use multi line, you should format your data like this:

index = ['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30', '2018-05-31', 

         '2018-06-30', '2018-07-31', '2018-08-31', '2018-09-30', '2018-10-31']

source = ColumnDataSource(dict(

"xs": [index, index, index],

"ys": np.random.rand(3, 10).tolist()

)) 

Working code with line instead of multiline:

from bokeh.plotting import figure

from bokeh.models import ColumnDataSource, HoverTool

from bokeh.io import output_notebook, show

import pandas as pd

import numpy as np



index = ['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30', '2018-05-31', 

         '2018-06-30', '2018-07-31', '2018-08-31', '2018-09-30', '2018-10-31']



columns = ['Argentina', 'Turkey', 'Mexico']



np.random.seed(123)

data = np.random.rand(10, 3)



df = pd.DataFrame(index=index, columns=columns, data=data)

df['Date'] = index



output_notebook() 

source = ColumnDataSource(df)



p = figure(plot_height=400, x_range=index)

p.line(x='Date', y='Argentina', source=source, color='red', legend='Argentina ', name='Argentina')

p.line(x='Date', y='Turkey', source=source, color='blue', legend='Turkey ', name='Turkey')

p.line(x='Date', y='Mexico', source=source, color='green', legend='Mexico ', name='Mexico')

p.xaxis.major_label_orientation = 0.90

p.legend.click_policy="hide"

p.add_tools(HoverTool(tooltips=[('Country', '$name'),

                                ('Date', '@Date'),

                                ('Value', '$y')]))



show(p)

Version with multiline:

from bokeh.plotting import figure

from bokeh.models import ColumnDataSource, HoverTool

from bokeh.io import show, output_notebook

import pandas as pd

import numpy as np



index = ['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30', '2018-05-31', 

         '2018-06-30', '2018-07-31', '2018-08-31', '2018-09-30', '2018-10-31']



columns = ['Argentina', 'Turkey', 'Mexico']



np.random.seed(123)

data = np.random.rand(10, 3)

df = pd.DataFrame(index=index, columns=columns, data=data)

df_transposed = df.transpose()

source = ColumnDataSource({"xs": [df.index.values.tolist()]*len(list(df.columns.values)), "ys": df_transposed.values.tolist(), "colors": ["red", "green", "blue"], "names": list(df.columns.values)})



output_notebook()

p = figure(plot_height=400, x_range=index)

p.multi_line(xs='xs', ys='ys', color = "colors", name="names", legend="names", source=source)

p.xaxis.major_label_orientation = 0.90

p.legend.click_policy="hide"

p.add_tools(HoverTool(tooltips=[('Country', '@names'),

                                ('Date', '$x'),

                                ('Value', '$y')]))



show(p)

I only had one problem with the hover tool. It doesn't display the correct date. (Now it shows the x position, if I replaced this for "xs" it would show the whole date list)