Waterfall Charts in Python

How to make waterfall plots in Python with Plotly.


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Simple Waterfall Chart

In [1]:
import plotly.graph_objects as go

fig = go.Figure(go.Waterfall(
    name = "20", orientation = "v",
    measure = ["relative", "relative", "total", "relative", "relative", "total"],
    x = ["Sales", "Consulting", "Net revenue", "Purchases", "Other expenses", "Profit before tax"],
    textposition = "outside",
    text = ["+60", "+80", "", "-40", "-20", "Total"],
    y = [60, 80, 0, -40, -20, 0],
    connector = {"line":{"color":"rgb(63, 63, 63)"}},
))

fig.update_layout(
        title = "Profit and loss statement 2018",
        showlegend = True
)

fig.show()

Multi Category Waterfall Chart

This example uses the waterfallgroupgap attribute, which sets a gap between bars.

In [2]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Waterfall(
    x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
        ["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
    measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
    y = [1, 2, 3, -1, None, 1, 2, -4, None],
    base = 1000
))

fig.add_trace(go.Waterfall(
    x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
        ["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
    measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
    y = [1.1, 2.2, 3.3, -1.1, None, 1.1, 2.2, -4.4, None],
    base = 1000
))

fig.update_layout(
    waterfallgroupgap = 0.5,
)

fig.show()

Setting Marker Size and Color

This example uses decreasing, increasing, and total attributes to customize the bars.

In [3]:
import plotly.graph_objects as go

fig = go.Figure(go.Waterfall(
    x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
       ["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
    measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
    y = [10, 20, 30, -10, None, 10, 20, -40, None], base = 300,
    decreasing = {"marker":{"color":"Maroon", "line":{"color":"red", "width":2}}},
    increasing = {"marker":{"color":"Teal"}},
    totals = {"marker":{"color":"deep sky blue", "line":{"color":'blue', "width":3}}}
))

fig.update_layout(title = "Profit and loss statement", waterfallgap = 0.3)

fig.show()

Horizontal Waterfall Chart

In [4]:
import plotly.graph_objects as go

fig = go.Figure(go.Waterfall(
    name = "2018", orientation = "h", measure = ["relative", "relative", "relative", "relative", "total", "relative",
                                              "relative", "relative", "relative", "total", "relative", "relative", "total", "relative", "total"],
    y = ["Sales", "Consulting", "Maintenance", "Other revenue", "Net revenue", "Purchases", "Material expenses",
       "Personnel expenses", "Other expenses", "Operating profit", "Investment income", "Financial income",
       "Profit before tax", "Income tax (15%)", "Profit after tax"],
    x = [375, 128, 78, 27, None, -327, -12, -78, -12, None, 32, 89, None, -45, None],
    connector = {"mode":"between", "line":{"width":4, "color":"rgb(0, 0, 0)", "dash":"solid"}}
))

fig.update_layout(title = "Profit and loss statement 2018")

fig.show()

Reference

See https://plotly.com/python/reference/#waterfall for more information and chart attribute options!

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter