Plotly library of Python can be very useful for data visualization and understanding the data simply and easily.
Plotly.figure_factory.create_2d_density
This function is used to create 2d density.
Syntax: plotly.figure_factory.create_2d_density(x, y, colorscale=’Earth’, ncontours=20, hist_color=(0, 0, 0.5), point_color=(0, 0, 0.5), point_size=2, title=’2D Density Plot’, height=600, width=600)
Parameters:
x: x-axis data for plot generation
y: y-axis data for plot generation
colorscale: An rgb or hex color, a color tuple or a list or tuple of colors.
hist_color: the color of the plotted histograms
point_color: the color of the scatter points
point_size: the color of the scatter points
title: set the title for the plot
height: the height of the chart
width: the width of the chart
Example 1:
Python3
from plotly.figure_factory import create_2d_density import numpy as np t = np.linspace( - 1 , 1.2 , 2000 ) x = (t * * 3 ) + ( 0.3 * np.random.randn( 2000 )) y = (t * * 6 ) + ( 0.3 * np.random.randn( 2000 )) fig = create_2d_density(x, y) fig.show() |
Output:
Example 2:
Python3
from plotly.figure_factory import create_2d_density import numpy as np # Make data points t = np.linspace( - 1 , 1.2 , 2000 ) x = (t * * 3 ) + ( 0.3 * np.random.randn( 2000 )) y = (t * * 6 ) + ( 0.3 * np.random.randn( 2000 )) # Create custom colorscale colorscale = [ '#7A4579' , '#D56073' , 'rgb(236,158,105)' , ( 1 , 1 , 0.2 ), ( 0.98 , 0.98 , 0.98 )] # Create a figure fig = create_2d_density(x, y, colorscale = colorscale, hist_color = 'rgb(255, 237, 222)' , point_size = 3 ) # Plot the data fig.show() |
Output: