Create Pictorial Stacked Chart with SVG image in plotly python

The pictorial stacked chart is an improved variation of a column or bar chart. Use an image related to the topic, natively plotly does not implement a similar graph but here I propose an example of how to do it with SVG files from Free Icons | Font Awesome.

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import PIL
import cairosvg
import plotly.express as px
import io
import numpy as np
import pandas as pd

#Function generate color scale in array svg
def genCategoryColor(matrix,start = 0, end = 1, color_rgb=[255,0,0]):
    for x in range(int(round(matrix.shape[0]*start,0)), int(round(matrix.shape[0]*end,0))):
        if (np.any(matrix[x,:,:])):  
            for y in range(matrix.shape[1]): 
                if (np.any(matrix[x][y])):
                    if x>=matrix.shape[0]*start and x < matrix.shape[0]*end:
                        matrix[x][y] = [color_rgb[0],color_rgb[1],color_rgb[2],list(matrix[x][y])[-1]]
    return matrix

#Function generate annotation in chart
def addAnnotation(fig,shape, start= 0, end = 1, text='Annotation'):
     fig.add_annotation(
        x=0,
        y=shape[0]*((start+end)/2),
        text=text,
        showarrow=True,
        xanchor="right",
        ax=-50,
        ay=0,
        arrowsize=0.5,
    )


#data example:
pc_1 = {'name':'Amazon Web Services (AWS)', 'start':0, 'end': 0.34, 'color':[255, 161, 6]}
pc_2 = {'name':'Microsoft Azure', 'start':0.34, 'end': 0.57, 'color':[6, 142, 255]}
pc_3 = {'name':'Google Cloud Platform (GCP)', 'start':0.57, 'end': 0.67, 'color':[255, 56, 7]}
pc_4 = {'name':'Otros', 'start':0.67, 'end': 1, 'color':[7, 217, 255]}
df = pd.DataFrame([pc_1,pc_2,pc_3,pc_4])

# svg icon from https://fontawesome.com/search?m=free&o=r and generate matrix
svg = '<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 640 512"><!--!Font Awesome Free 6.6.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free Copyright 2024 Fonticons, Inc.--><path d="M0 336c0 79.5 64.5 144 144 144l368 0c70.7 0 128-57.3 128-128c0-61.9-44-113.6-102.4-125.4c4.1-10.7 6.4-22.4 6.4-34.6c0-53-43-96-96-96c-19.7 0-38.1 6-53.3 16.2C367 64.2 315.3 32 256 32C167.6 32 96 103.6 96 192c0 2.7 .1 5.4 .2 8.1C40.2 219.8 0 273.2 0 336z"/></svg>'
im = PIL.Image.open(io.BytesIO(cairosvg.svg2png(bytestring=svg))).convert("RGBA")
matrix = np.array(im)

for index, row in df.iterrows():
  matrix = genCategoryColor(matrix,row['start'],row['end'],list(row['color']))

fig = px.imshow(matrix,height=400,width=800,template='none')

for index, row in df.iterrows():
    addAnnotation(fig,matrix.shape,row['start'],row['end'],str(round((row['end']-row['start'])*100,2))+'% '+row['name'])
fig.update_xaxes(title = 'Time', showticklabels=False, visible = False)
fig.update_yaxes(visible=False, type='linear', showticklabels=False)
fig.update_layout(coloraxis_showscale=False,margin=dict(l=20,r=20,b=20,t=20))
fig.show()

Use the available icons replacing the viable SVG to generate visualizations. here some examples: