plotly.figure_factory.create_bullet() in Python

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()

Output: