Introduction to Data Visualization with Plotly in Python
Alex Scriven
Data Scientist
How to customize plots:
color)update_layout()fig.update_layout({"title":{"text":"A New Title"}})
Customizing color can help:

Computers use RGB encoding to specify colors:
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See more in this article

color argument (DataFrame column)
fig = px.bar(data_frame=student_scores,
x="student_name",
y="score",
title="Student Scores by Student"
color="city")
fig.show()
The plot before:

Our plot after:

Using plotly.express color argument with univariate (bar, histogram) plots:


color_discrete_map: A dictionary that maps categorical values to colors"red", "green" etc.$$
fig = px.bar( data_frame=student_scores, x="student_name", y="score", title="Student Scores by Student",color_discrete_map={ "Melbourne": "rgb(0,0,128)", "Sydney": "rgb(235, 207, 52)"},color="city")


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color_continuous_scale argument for color scales.
fig = px.bar(data_frame=weekly_temps,
x="day", y="temp",
color="temp",
color_continuous_scale="inferno")
fig.show()
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my_scale=[("rgb(242, 238, 10)"), ("rgb(242, 95, 10)"), ("rgb(255,0,0)")]fig = px.bar(data_frame=weekly_temps, x="day", y="temp",color_continuous_scale=my_scale, color="temp")

Introduction to Data Visualization with Plotly in Python