How to Display Dataframe next to Plot in Jupyter Notebook

How to Display Dataframe next to Plot in Jupyter Notebook

To display a Pandas DataFrame next to a plot in a Jupyter Notebook, you can use the IPython.display module to control the layout of the elements. You can use the display() function to arrange the DataFrame and plot side by side using HTML/CSS styling. Here's how you can achieve this:

import pandas as pd import matplotlib.pyplot as plt from IPython.display import display, HTML # Create a sample DataFrame data = {'Name': ['Alice', 'Bob', 'Carol'], 'Age': [25, 30, 22]} df = pd.DataFrame(data) # Create a sample plot plt.figure(figsize=(6, 4)) plt.plot([1, 2, 3], [4, 6, 8], marker='o') plt.title('Sample Plot') # Display the DataFrame and plot side by side display(HTML('<h2>DataFrame:</h2>')) display(df) display(HTML('<h2>Plot:</h2>')) plt.show()

In this example, we first create a sample DataFrame (df) and a sample plot using Matplotlib. We then use the display() function from IPython.display to render the DataFrame and the plot side by side.

By using the HTML class, we can add HTML headers (<h2>) to provide titles for the DataFrame and plot sections.

Keep in mind that the exact layout may depend on the specific Jupyter Notebook environment and its CSS settings. You can adjust the styling and layout further using HTML and CSS if needed.

Examples

  1. "Display dataframe next to plot Jupyter Notebook"

    • Description: This query seeks methods to present a Pandas DataFrame alongside a plot in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot plt.plot(df['x'], df['y']) plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.title('Plot Title') # Display DataFrame df

  2. "Combine DataFrame and plot in Jupyter"

    • Description: This query aims to merge a Pandas DataFrame with a plot in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Create subplots fig, ax = plt.subplots() # Plot ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame display(df)

  3. "Show DataFrame next to plot in Jupyter"

    • Description: This query is about how to present a Pandas DataFrame alongside a plot in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame next to plot df

  4. "Display DataFrame and plot together in Jupyter Notebook"

    • Description: This query seeks ways to exhibit a Pandas DataFrame and a plot side by side within a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt from IPython.display import display # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame next to plot display(df)

  5. "Present plot and DataFrame side by side in Jupyter"

    • Description: This query looks for methods to showcase a plot and a Pandas DataFrame side by side in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5)) ax1.plot(df['x'], df['y']) ax1.set_xlabel('X-axis') ax1.set_ylabel('Y-axis') ax1.set_title('Plot Title') # Display DataFrame ax2.axis('off') ax2.table(cellText=df.values, colLabels=df.columns, loc='center')

  6. "Embed DataFrame next to plot in Jupyter Notebook"

    • Description: This query is about embedding a Pandas DataFrame alongside a plot within a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame next to plot df.style.set_caption('DataFrame').set_table_styles([{'selector': 'caption','props': [('color', 'blue')]}])

  7. "Show DataFrame alongside plot in Jupyter"

    • Description: This query seeks ways to exhibit a Pandas DataFrame alongside a plot in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame next to plot plt.show() df

  8. "Arrange plot and DataFrame in Jupyter Notebook"

    • Description: This query is about arranging a plot and a Pandas DataFrame in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt from IPython.display import display # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame next to plot display(df)

  9. "Combine plot and DataFrame output in Jupyter Notebook"

    • Description: This query aims to merge the output of a plot and a Pandas DataFrame in a Jupyter Notebook.
    import pandas as pd import matplotlib.pyplot as plt from IPython.display import display # Generate sample data data = {'x': range(10), 'y': range(10, 20)} df = pd.DataFrame(data) # Plot fig, ax = plt.subplots() ax.plot(df['x'], df['y']) ax.set_xlabel('X-axis') ax.set_ylabel('Y-axis') ax.set_title('Plot Title') # Display DataFrame below the plot display(df)

  10. "Present DataFrame next to plot in Jupyter Notebook"

    • Description: This query seeks methods to present a Pandas DataFrame alongside a plot in a Jupyter Notebook.

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