Random Chart Generator with Seaborn

This function uses the seaborn library to randomly generate different types of charts, including bar plots, box plots, line plots, and scatter plots. It first generates a random dataset and then draws a chart based on the randomly selected chart type.

Technology Stack : The packages and technologies used in this code include seaborn, numpy, matplotlib, and pandas.

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

def generate_random_plot():
    # Generate a random dataset
    np.random.seed(10)
    data = pd.DataFrame({
        'Category': pd.Categorical([np.random.choice(['A', 'B', 'C']) for _ in range(100)]),
        'Value': np.random.rand(100) * 100
    })

    # Randomly select a seaborn plot type
    plot_type = np.random.choice(['barplot', 'stripplot', 'lineplot', 'scatterplot'])

    # Set the figure and axis
    plt.figure(figsize=(10, 6))
    ax = plt.gca()

    # Generate the plot based on the random selection
    if plot_type == 'barplot':
        sns.barplot(x='Category', y='Value', data=data, ax=ax)
    elif plot_type == 'stripplot':
        sns.stripplot(x='Category', y='Value', data=data, ax=ax)
    elif plot_type == 'lineplot':
        sns.lineplot(x='Category', y='Value', data=data, ax=ax)
    elif plot_type == 'scatterplot':
        sns.scatterplot(x='Category', y='Value', data=data, ax=ax)

    plt.title(f'Random {plot_type}')
    plt.show()