Plotly Express: Remove Trendline from Marginal Distribution Figures

Are you tired of those pesky trendlines ruining the aesthetics of your marginal distribution figures? Well, you’re in luck because today we’re going to dive into the world of Plotly Express and learn how to remove trendlines from those figures, making them look sleek and professional.

What are Marginal Distribution Figures?

Before we dive into the solution, let’s quickly cover what marginal distribution figures are. In Plotly Express, marginal distribution figures refer to the small plots that appear on the margins of a scatter plot, showing the distribution of the x and y variables. These plots provide a more detailed view of the data, but sometimes, the trendlines can be distracting.

Why Remove Trendlines?

So, why would you want to remove trendlines from your marginal distribution figures? Well, here are a few reasons:

• Aesthetics: Trendlines can make your plots look cluttered and messy, detracting from the overall visualization.
• Distraction: Trendlines can draw attention away from the actual data, making it harder to focus on the important patterns and trends.
• Overemphasis: Trendlines can overemphasize the relationship between the variables, making it seem more significant than it actually is.

Removing Trendlines with Plotly Express

Now, let’s get to the good stuff! To remove trendlines from your marginal distribution figures using Plotly Express, you can use the trendline argument. Here’s an example:

import plotly.express as px
import pandas as pd

# Create a sample dataset
df = pd.DataFrame({
    "x": [1, 2, 3, 4, 5],
    "y": [2, 3, 5, 7, 11]
})

# Create a scatter plot with marginal distribution figures
fig = px.scatter(df, x="x", y="y", marginal_x="histogram", marginal_y="histogram")

# Remove trendlines from marginal distribution figures
fig.update_layout(
    margin_x=dict(trendline=dict(visible=False)),
    margin_y=dict(trendline=dict(visible=False))
)

# Show the plot
fig.show()

In this example, we create a scatter plot with marginal distribution figures using Plotly Express. We then use the update_layout method to remove the trendlines from the marginal distribution figures. The trendline argument is set to dict(visible=False), which hides the trendlines.

Customizing the Marginal Distribution Figures

But wait, there’s more! You can also customize the marginal distribution figures to your heart’s content. Here are a few options:

Changing the Bin Size

You can adjust the bin size of the histogram using the bin_size argument. For example:

fig = px.scatter(df, x="x", y="y", marginal_x="histogram", marginal_y="histogram", marginal_x_options=dict(bin_size=0.5), marginal_y_options=dict(bin_size=0.5))

This sets the bin size to 0.5, which can affect the appearance of the histogram.

Changing the Histogram Type

You can also change the type of histogram using the histnorm argument. For example:

fig = px.scatter(df, x="x", y="y", marginal_x="histogram", marginal_y="histogram", marginal_x_options=dict(histnorm="probability"), marginal_y_options=dict(histnorm="probability"))

This sets the histogram type to probability, which normalizes the histogram to show probabilities rather than frequencies.

Troubleshooting

So, what if you’re having trouble removing trendlines from your marginal distribution figures? Here are a few common issues and their solutions:

Issue	Solution
Trendlines still visible after setting trendline to visible=False	Make sure you’re using the latest version of Plotly Express. If you’re using an older version, try updating to the latest version.
Trendlines not removed from marginal distribution figures	Check that you’re applying the trendline argument to the correct axis (e.g., margin_x or margin_y). Also, make sure you’re using the correct syntax for the trendline argument.

Conclusion

And that’s it! With these simple steps, you can remove trendlines from your marginal distribution figures using Plotly Express. Remember, by customizing your plots, you can create more effective visualizations that communicate your insights clearly and effectively. Happy plotting!

By following this guide, you should now be able to create stunning marginal distribution figures without trendlines, making your plots look more professional and visually appealing. If you have any more questions or need further assistance, feel free to ask!

Don’t forget to explore the extensive range of features and options available in Plotly Express to take your data visualization skills to the next level. Happy plotting, and we’ll see you in the next tutorial!

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