Editing plot axes

Introduction to Data Visualization with Plotly in Python

Alex Scriven

Data Scientist

Our dataset

fig = px.bar(penguin_flippers, 
            x="spec", 
            y="av_flip_length")
fig.show()

Simple bar chart of penguin flipper size by species

fig.update_xaxes(title_text="Species")
fig.update_yaxes(title_text="Average Flipper Length")

fig.update_layout(dict(
    xaxis=dict(title=dict(text="Species")),
    yaxis=dict(title=dict(text="Average Flipper Length"))
))

Simple bar chart with updated axes titles

⭐⭐ Use the update_layout() method for more control:
- Can adjust font size, style, color, angle

Simple bar chart with updated axes titles

fig.update_layout(dict(
    yaxis=dict(range=[150, penguin_flippers["av_flip_length"].max() + 30]
    )))

Simple bar chart with specific shortened range

What happens when some data points are much larger than others?

Table of number billionaires by country

fig = px.bar(billionaire_data, 
            x="Country", 
            y="Number Billionaires")
fig.show()

Basic bar chart of bar graph of billionaire numbers

Log plot example

fig = px.bar(billionaire_data, 
            x="Country", 
            y="Number Billionaires",
            log_y=True)

fig.show()

Log scale bar chart of billionaire data

💡 Always consider the audience when choosing how to visualize data

Presenting a graph to the audience

Introduction to Data Visualization with Plotly in Python