plotly.figure_factory.create_bullet() in Python

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Plotly library of Python can be very useful for data visualization and understanding the data simply and easily.

plotly.figure_factory.create_bullet

This method is used to create bullet charts. This function can take both dataframes or a sequence of dictionaries.

Syntax: plotly.figure_factory.create_bullet(data, markers=None, measures=None, ranges=None, subtitles=None, titles=None, orientation=’h’, **layout_options)

Parameters:

data: either a list/tuple of dictionaries or a pandas DataFrame.

markers: the column name or dictionary key for the markers in each subplot.

measures: This bar usually represents the quantitative measure of performance, usually a list of two values [a, b] and are the blue bars in the foreground of each subplot by default.

ranges: This parameter is usually a 3-item list [bad, okay, good]. They correspond to the grey bars in the background of each chart.

subtitles: the column name or dictionary key for the subtitle of each subplot chart.

titles ((str)) – the column name or dictionary key for the main label of each subplot chart.

Example 1:

Python3

import plotly.figure_factory as ff 
  
  
data = [ 
  {"label": "revenue",  
   "sublabel": "us$, in thousands", 
   "range": [150, 225, 300],  
   "performance": [220,270], 
   "point": [250]}, 
    
  {"label": "Profit",  
   "sublabel": "%",  
   "range": [20, 25, 30], 
   "performance": [21, 23],  
   "point": [26]}, 
    
  {"label": "Order Size",  
   "sublabel":"US$, average", 
   "range": [350, 500, 600], 
   "performance": [100,320], 
   "point": [550]}, 
    
  {"label": "New Customers",  
   "sublabel": "count", 
   "range": [1400, 2000, 2500], 
   "performance": [1000, 1650], 
   "point": [2100]}, 
    
  {"label": "Satisfaction",  
   "sublabel": "out of 5", 
   "range": [3.5, 4.25, 5], 
   "performance": [3.2, 4.7], 
   "point": [4.4]} 
] 
  
fig = ff.create_bullet( 
    data, titles='label', 
    subtitles='sublabel',  
    markers='point', 
    measures='performance', 
    ranges='range',  
    orientation='h', 
    title='my simple bullet chart'
) 
  
fig.show()

Output:

Example 2: Using a Dataframe with colors

Python3

import plotly.figure_factory as ff 
import pandas as pd 
  
  
data = [ 
    {"title": "Revenue", 
     "subtitle": "US$, in thousands", 
     "ranges": [150, 225, 300], 
     "measures":[220, 270], 
     "markers":[250]}, 
  
    {"title": "Profit", 
     "subtitle": "%", 
     "ranges": [20, 25, 30], 
     "measures":[21, 23], 
     "markers":[26]}, 
      
    {"title": "Order Size", 
     "subtitle": "US$, average",  
     "ranges": [350, 500, 600], 
     "measures":[100, 320], 
     "markers":[550]}, 
      
    {"title": "New Customers",  
     "subtitle": "count", 
     "ranges": [1400, 2000, 2500], 
     "measures":[1000, 1650],  
     "markers":[2100]}, 
      
    {"title": "Satisfaction",  
     "subtitle": "out of 5", 
     "ranges": [3.5, 4.25, 5],  
     "measures":[3.2, 4.7], 
     "markers":[4.4]} 
] 
  
fig = ff.create_bullet( 
    data, titles='title',  
    markers='markers', 
    measures='measures', 
    orientation='v', 
    measure_colors=['rgb(14, 52, 75)', 'rgb(31, 141, 127)'], 
    scatter_options={'marker': {'symbol': 'circle'}}, 
  width=700) 
  
fig.show()