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¶
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.
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 totals attributes to customize the bars.
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¶
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( ... )
from dash import Dash, dcc, html
app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter