Add x and y labels to a pandas plot

Add x and y labels to a pandas plot

To add x and y labels to a Pandas plot, you can use the .set_xlabel() and .set_ylabel() methods on the Pandas DataFrame's plot object. Here's an example of how to do it:

import pandas as pd import matplotlib.pyplot as plt # Create a sample DataFrame data = {'X': [1, 2, 3, 4, 5], 'Y': [10, 15, 13, 18, 20]} df = pd.DataFrame(data) # Create a scatter plot ax = df.plot.scatter(x='X', y='Y') # Add x and y labels ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label") # Show the plot plt.show()

In this example:

  1. We create a sample DataFrame df with two columns 'X' and 'Y' containing data.

  2. We create a scatter plot using the plot.scatter() method, specifying the 'X' column as the x-axis and the 'Y' column as the y-axis.

  3. We access the plot object as ax.

  4. We use ax.set_xlabel() to set the x-axis label and ax.set_ylabel() to set the y-axis label.

  5. Finally, we display the plot using plt.show().

This will create a scatter plot with x and y labels.

You can customize the labels and formatting as needed for your specific plot.

Examples

  1. How to add x-label and y-label to a Pandas plot?

    • Description: This query is common for users seeking guidance on labeling their Pandas plots properly.
    • Code Implementation:
      import pandas as pd import matplotlib.pyplot as plt # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with labels ax = df.plot() ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label") plt.show()

  2. Pandas plot xlabel ylabel syntax

    • Description: This query targets users looking specifically for the syntax to add labels to their Pandas plots.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with labels using syntax df.plot().set(xlabel="X-axis Label", ylabel="Y-axis Label")

  3. How to label axes on Pandas plot?

    • Description: Users often search for general guidance on labeling axes in Pandas plots.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with labeled axes ax = df.plot() ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label")

  4. Adding titles and labels to Pandas plot

    • Description: Users may want to add both titles and labels to their Pandas plots for clarity.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with title and labels ax = df.plot() ax.set_title("Plot Title") ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label")

  5. How to name x and y axes in Pandas plot?

    • Description: This query is focused on naming the axes of Pandas plots accurately.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with named axes ax = df.plot() ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label")

  6. Pandas plot xlabel ylabel without matplotlib

    • Description: Users may prefer solutions that don't explicitly use Matplotlib for labeling axes.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with labels without directly importing matplotlib ax = df.plot() ax.set_xlabel("X-axis Label", fontsize=14) ax.set_ylabel("Y-axis Label", fontsize=14)

  7. How to add labels to a Pandas plot without using plt?

    • Description: Some users prefer to avoid using plt for labeling to stick to Pandas-only solutions.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with labels without using plt ax = df.plot() ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label")

  8. Pandas plot with custom x and y axis labels

    • Description: Users might want to customize their axis labels beyond the default ones.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with custom axis labels ax = df.plot() ax.set_xlabel("Custom X-label") ax.set_ylabel("Custom Y-label")

  9. How to add axis labels in Pandas plot with style?

    • Description: Users may want to add labels with specific styles to match their plot aesthetics.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with styled axis labels ax = df.plot() ax.set_xlabel("X-axis Label", fontsize=14, color='blue') ax.set_ylabel("Y-axis Label", fontsize=14, color='green')

  10. Pandas plot add labels best practices

    • Description: This query targets users seeking best practices for adding labels to Pandas plots.
    • Code Implementation:
      import pandas as pd # Sample data data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]} df = pd.DataFrame(data) # Plotting with best practices for labels ax = df.plot() ax.set_xlabel("X-axis Label") ax.set_ylabel("Y-axis Label")

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