bqplot | Plotting library for IPython/Jupyter notebooks | Data Visualization library

I'm trying to plot a time series forecast, surrounded by a shaded uncertainty interval timeseries, and have tooltips work for both the line and the perimeter of the uncertainty.

I am trying to plot a dynamic portfolio performance that changes as the weights of the portfolio change

Assume a portfolio has 2 components with a 50% weighting each. I want to show a chart of the portfolio with sliders representing the weights of the components. I then want to be able to slide the values of the weights around and have the portfolio chart dynamically update.

I have done this for a portfolio that consists of one weight but cant figure out how to amend for more than 1 weight - maybe I need a different approach.

Example below substitutes a random df with 1 column in place of my portfolio df - process should be the same.

In terms of this example if the df had 2 columns - how can I get it working with 2 sliders controlling each weight ?

from bqplot import DateScale, LinearScale, Axis, Figure, Lines

from ipywidgets import FloatSlider, VBox

import pandas as pd

import numpy as np

slider = FloatSlider(value=1, min = 0, max = 1, step = .01, description = 'Weight A')

df = pd.DataFrame(np.random.randint(0,100,size=(100, 1)), columns=list('A'))

x_sc = LinearScale()

y_sc = LinearScale()

ax_x = Axis(label='Date', scale=x_sc, grid_lines='solid')

ax_y = Axis(label='Price', scale=y_sc, orientation='vertical', grid_lines='solid')

line = Lines(y=df['A'],x=df.index , scales={'x': x_sc, 'y': y_sc}, colors = ['#FF0000'])

line2 = Lines(y=df['A'],x=df.index , scales={'x': x_sc, 'y': y_sc})

fig = Figure(axes=[ax_x, ax_y], marks=[line, line2], title='Price Chart')

def new_chart(value):

If I run this code on a jupyter notebook

I'm attempting to put together a Jupyter Notebook that allows a user to input a state in a dropdown, which would change the result in the second dropdown to only show cities from that state. Once the city is selected, a button could be pressed to refresh the graph (I realize there's you can use manual with interact, but was unable to get this to function properly) and show the resultant data (covid cases over time). I've had some success making the widgets, but I can't get the data to plot correctly.

This is my first time using widgets in Jupyter and I'm a bit lost what with interact, interactivity, display, and observe (not to mention the deprecated on_trait_change). Here's what I have so far...

Today I've been trying to install the module bqplot and use jupyter lab for the very first time.

However, I've not been able to obtain the desired output when using the basic examples as shown on their website.

The code I'm trying to execute is as following:

Is it possible to use Jupyter Widgets in Google Colaboratory?

I followed the instructions here, both with ipyleaflet and bqplot

But I got this error message.

Failed to display Jupyter Widget of type Map.

If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean that the widgets JavaScript is still loading. If this message persists, it likely means that the widgets JavaScript library is either not installed or not enabled. See the Jupyter Widgets Documentation for setup instructions.

If you're reading this message in another frontend (for example, a static rendering on GitHub or NBViewer), it may mean that your frontend doesn't currently support widgets.

Is it possible to use these widgets? Or did I make a mistake somewhere?

I am having trouble getting my tooltip data to show up in my line chart. Here is some very simple code that reproduces the error. When I hover over the line all that shows up is NaN. Can someone please help me? Thank you!

from bqplot import (Axis, LinearScale, Lines, Figure, Tooltip)

x = [1,2,3,4,5]

y = [1,2,3,4,5]

x_sc = LinearScale()

y_sc = LinearScale()

def_tt = Tooltip(fields=['x', 'y'], formats=['.1f', '.1f'])

line_chart = Lines(x=x, y=y, scales= {'x': x_sc, 'y': y_sc}, line_style='solid',default_colors=['dodgerblue'], tooltip=def_tt)

ax_x = Axis(scale=x_sc)

ax_y = Axis(scale=y_sc, orientation='vertical', tick_format='0.2f')

Figure(marks=[line_chart], axes=[ax_x, ax_y])

I am doing a little experiment to debug my project. I am trying to manipulate the hue value on HSV colorspace to see the effect on it when I change it back to RGB.

I have a simple image with whole blue background and a single red circle inside of it. I convert it from RGB to HSV and then change one of the values, and then revert it back to the previous value (please see the code, I can't explain it well by using just words). I was expecting the image to remain the same but to my surprise, when I changed it back from HSV to RGB it gives different image.

Use widget to display snippets from a csv file/dataframe and feed to tooltip attribute of bqplot

I am trying to display certain info (statistics such as age group, income, obesity levels etc.) for each state in the US using bqplot. I am able to plot the US map using examples provided on bqplot github. But the tooltip constructor is using columns names from a json file, which is also used to actually display the map. I do not know how to override that so, I decided to use a widget (ideally a container widget) to hold the data I want to display for each state and use the on_hover() method provided in bqplot.map; In fact, I just modified the code in the link below:

Container as tooltip doesn't show contents

to display info for a particular state