Adding Colorbars for Multiple DataFrames in Hvplot

2 min read 09-11-2024

Adding Colorbars for Multiple DataFrames in Hvplot

When working with multiple DataFrames in Python using Hvplot, adding colorbars can enhance the visual representation of the data. Colorbars provide a reference for interpreting the color mappings of plots, especially in scatter and heatmap visualizations. This article will guide you through the process of adding colorbars to multiple DataFrames.

Understanding Hvplot

Hvplot is a high-level plotting API built on HoloViews, designed to work seamlessly with Pandas DataFrames. It enables quick and easy visualizations while allowing for customization and interactivity.

Prerequisites

Before you start, ensure you have the necessary libraries installed:

pip install holoviews hvplot pandas

Creating Sample DataFrames

Let’s create two sample DataFrames that we can visualize:

import pandas as pd
import numpy as np

# Create DataFrame 1
df1 = pd.DataFrame({
    'x': np.random.rand(100),
    'y': np.random.rand(100),
    'value': np.random.rand(100) * 100
})

# Create DataFrame 2
df2 = pd.DataFrame({
    'x': np.random.rand(100),
    'y': np.random.rand(100),
    'value': np.random.rand(100) * 100
})

Plotting with Colorbars

Plotting the First DataFrame

You can create a scatter plot with a colorbar for the first DataFrame as follows:

import hvplot.pandas

plot1 = df1.hvplot.scatter(x='x', y='y', c='value', colorbar=True, cmap='viridis')

Plotting the Second DataFrame

Now, create a scatter plot with a colorbar for the second DataFrame:

plot2 = df2.hvplot.scatter(x='x', y='y', c='value', colorbar=True, cmap='plasma')

Displaying Both Plots Together

To display both plots in a single view, you can use the + operator:

combined_plot = plot1 + plot2
combined_plot

Customizing Colorbars

Hvplot allows you to customize colorbars easily. You can set limits, labels, and more:

plot1 = df1.hvplot.scatter(x='x', y='y', c='value', colorbar=True, cmap='viridis', clim=(0, 100), title='DataFrame 1')
plot2 = df2.hvplot.scatter(x='x', y='y', c='value', colorbar=True, cmap='plasma', clim=(0, 100), title='DataFrame 2')

combined_plot = plot1 + plot2
combined_plot

Conclusion

Adding colorbars to multiple DataFrames in Hvplot not only enhances the interpretability of your visualizations but also helps in distinguishing the datasets effectively. By following the steps outlined above, you can create engaging and informative visual representations of your data.

Feel free to customize further according to your specific needs and preferences!