Creating a Stacked Bar Chart with Plotly Using Two DataFrames

When working with multiple data sets and the need to overlay them in a single chart, Plotly provides an effective solution using its bar chart functionality. In this article, we will explore how to create a stacked bar chart by overlaying two different bar plots on top of each other, sharing the same x-axis.

Overview of Plotly Bar Chart

Before diving into creating a stacked bar chart with Plotly, let’s briefly discuss the basics of a bar chart in Plotly. A bar chart is a popular type of plot used to compare categorical data across different groups or categories. In Plotly, bar charts are created using the px.bar() function.

Here is an example of how to create a basic bar chart:

import plotly.express as px
import pandas as pd

# Create sample data
df = pd.DataFrame({
    'x': ['a', 'b', 'c'],
    'y': [10, 15, 7]
})

# Create the bar chart
fig = px.bar(df, x='x', y='y')

# Show the plot
fig.show()

Merging DataFrames for Stacked Bar Chart

To create a stacked bar chart with two data sets, we need to merge these data sets into a single DataFrame. This can be achieved by renaming columns in one of the DataFrames so that they share the same name.

Let’s continue with our example:

import plotly.express as px
import pandas as pd

# Create sample data for both plots
df1 = pd.DataFrame({
    'x1': [1, 2, 3],
    'y1': [10, 15, 7],
    'col': ['A', 'B', 'C']
})

df2 = pd.DataFrame({
    'x1': [1, 2, 3],
    'y1': [-5, -8, -3],
    'col': ['A', 'B', 'C']
})

# Rename columns in df2 so that they match those of df1
df2 = df2.rename(columns={'y1': 'y'})

# Concatenate the DataFrames
df = pd.concat([df1, df2])

# Create the bar chart with Plotly
fig = px.bar(df, x='x1', y='y', color='col')

# Show the plot
fig.show()

Creating Stacked Bar Charts in Plotly

When creating a stacked bar chart in Plotly using two DataFrames, the key is to merge these data sets into a single DataFrame before passing it to the px.bar() function.

Here’s an example with explanations:

import plotly.express as px
import pandas as pd

# Create sample data for both plots
df1 = pd.DataFrame({
    'x1': [1, 2, 3],
    'y1': [10, 15, 7],
    'col': ['A', 'B', 'C']
})

df2 = pd.DataFrame({
    'x1': [1, 2, 3],
    'y1': [-5, -8, -3],
    'col': ['A', 'B', 'C']
})

# Concatenate the DataFrames
df = pd.concat([df1, df2])

# Create the bar chart with Plotly
fig = px.bar(df, x='x1', y='y1', color='col')

# Show the plot
fig.show()

In this example, px.bar() is used to create a stacked bar chart by passing the merged DataFrame df as input.

Explanation of the Code

Here’s an explanation of how the code works:

• The first two DataFrames (df1 and df2) are created with their respective data sets.
• The columns in df2 are renamed to match those in df1, so that they can be concatenated together.
• The DataFrames are concatenated using pd.concat().
• The merged DataFrame is then passed to the px.bar() function, which creates a stacked bar chart.

Conclusion

Creating a stacked bar chart with Plotly involves merging two data sets into a single DataFrame and passing this merged DataFrame to the px.bar() function. By following these steps, you can effectively overlay two different bar plots on top of each other, sharing the same x-axis.

In conclusion, we have explored how to create a stacked bar chart by combining multiple DataFrames in Plotly using its bar chart functionality. This is particularly useful when comparing data across different categories or groups.

Last modified on 2023-09-08