Creating Pandas DataFrame from the data points selected on the Plotly Scatter Plot

Question

Plotly Figure Widget helps me create a scatter plot which is interactive, ie., I can select data points on the scatter plot and based on the selection my table widget shows the records. I wanted help with converting this table to a pandas dataframe.

import plotly.graph_objs as go
import plotly.offline as py

import pandas as pd
import numpy as np
from ipywidgets import interactive, HBox, VBox

py.init_notebook_mode()

df = pd.read_csv('https://raw.githubusercontent.com/jonmmease/plotly_ipywidget_notebooks/master/notebooks/data/cars/cars.csv')

f = go.FigureWidget([go.Scatter(y = df['City mpg'], x = df['City mpg'], mode = 'markers')])
scatter = f.data[0]
N = len(df)
scatter.x = scatter.x + np.random.rand(N)/10 *(df['City mpg'].max() - df['City mpg'].min())
scatter.y = scatter.y + np.random.rand(N)/10 *(df['City mpg'].max() - df['City mpg'].min())
scatter.marker.opacity = 0.5

def update_axes(xaxis, yaxis):
    scatter = f.data[0]
    scatter.x = df[xaxis]
    scatter.y = df[yaxis]
    with f.batch_update():
        f.layout.xaxis.title = xaxis
        f.layout.yaxis.title = yaxis
        scatter.x = scatter.x + np.random.rand(N)/10 *(df[xaxis].max() - df[xaxis].min())
        scatter.y = scatter.y + np.random.rand(N)/10 *(df[yaxis].max() - df[yaxis].min())

axis_dropdowns = interactive(update_axes, yaxis = df.select_dtypes('int64').columns, xaxis = df.select_dtypes('int64').columns)

# Create a table FigureWidget that updates on selection from points in the scatter plot of f
t = go.FigureWidget([go.Table(
    header=dict(values=['ID','Classification','Driveline','Hybrid'],
                fill = dict(color='#C2D4FF'),
                align = ['left'] * 5),
    cells=dict(values=[df[col] for col in ['ID','Classification','Driveline','Hybrid']],
               fill = dict(color='#F5F8FF'),
               align = ['left'] * 5))])

def selection_fn(trace,points,selector):
    t.data[0].cells.values = [df.loc[points.point_inds][col] for col in ['ID','Classification','Driveline','Hybrid']]

scatter.on_selection(selection_fn)

# Put everything together
VBox((HBox(axis_dropdowns.children),f,t))

Just expecting the table created after selecting points on the scatter plot to a pandas dataframe.

Output

Are you trying to take the points selected via the plot and then move them to a separate DataFrame? — Nathan
– Nathan, Commented Sep 25, 2019 at 16:27

user88484 · Accepted Answer · 2019-11-02 12:25:29Z

1

Probably not the most elegant way to solve it, but after you select your points, you can type:

d = t.to_dict()
df = pd.DataFrame(d['data'][0]['cells']['values'], index =d['data'][0]['header']['values']).T

t is of type plotly.graph_objs._figurewidget.FigureWidget

I use jupyter notebook, so I wrote these lines of code one cell below your code, and I get a new df with the selected events

answered Nov 2, 2019 at 12:25

user88484

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1 Comment

Atmani Saad Over a year ago

This is the correct answer, just make sure to not overwrite your initial dataframe (df) as I did.

Nathan · Accepted Answer · 2019-09-26 18:17:25Z

0

Assuming the following piece of code highlights the points you care about:

def selection_fn(trace,points,selector):
    t.data[0].cells.values = [df.loc[points.point_inds][col] for col in ['ID','Classification','Driveline','Hybrid']]

Change it to return a dataframe:

def selection_fn(trace,points,selector):
    return pd.df([df.loc[points.point_inds][col] for col in ['ID','Classification','Driveline','Hybrid'] if col in {selection}])

The list comprehension needs to be changed to loop over only the points you want to return. Example list comphrension from the documentation:

[(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]

edited Sep 26, 2019 at 18:17

answered Sep 25, 2019 at 20:28

Nathan

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5 Comments

Rohan Thorat Over a year ago

I tried the above code but after making a selection on the scatter plot only those specific records should be returned back whereas with the above code all the records are getting returned

Nathan Over a year ago

You will need to tweak it. The for loop in the list comprehension either needs to be the points you want or have an conditional statement added.

Rohan Thorat Over a year ago

Oh I see, Thank you soo much, I will try to work on it and get back

Nathan Over a year ago

Did you figure anything new out @rohan?

Rohan Thorat Over a year ago

not as of now but I am still trying, but I will post my findings shortly

Atmani Saad · Accepted Answer · 2022-03-17 15:26:36Z

0

A better solution:

    def selection_fn(trace, points, selector):
    
        t.data[0].cells.values = [
            df.loc[points.point_inds][col]
            for col in ["ID", "Classification", "Driveline", "Hybrid"]]
        
        selection_fn.df1 = df.loc[points.point_inds]


    print(selection_fn.df1)

Access a function variable outside the function without using "global"

answered Mar 17, 2022 at 15:26

Atmani Saad

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