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

# Example DataFrame
data = {
    'Product_Categroy': ['Electronics', 'Furniture', 'Clothing', 'Electronics', 'Furniture', 'Clothing'],
    'Sales': [1000, 1500, 1200, 1100, 1400, 1300],
    'Region': ['North', 'North', 'North', 'South', 'South', 'South']
}

df = pd.DataFrame(data)

def plot_avg_sales_regionwise():
    sns.set_theme(style="whitegrid")  # Set a theme
    ax = sns.barplot(x='Product_Categroy', y='Sales', hue='Region', data=df, palette="pastel", ci=None)  # No error bars
    ax.set_title("Average Sales by Product Category and Region")
    ax.set_xlabel("Product Category")
    ax.set_ylabel("Average Sales")
    ax.legend(title="Region")
    plt.xticks(rotation=45)  # Rotate x-axis labels for better readability
    plt.tight_layout()  # Adjust layout to prevent overlapping
    plt.show()
    
plot_avg_sales_regionwise()

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

# Example DataFrame with relevant categories
data = {
    'Product_Category': ['Category B', 'Category A', 'Category C', 'Category B', 'Category A', 'Category C'],
    'Sales': [1000, 1500, 1200, 1100, 1400, 1300],
    'Region': ['North', 'North', 'North', 'South', 'South', 'South']
}

df = pd.DataFrame(data)

def plot_avg_sales_regionwise():
    sns.barplot(x='Product_Category', 
                y='Sales', 
                hue='Region', 
                data=df, 
                palette="pastel",  # Use a pastel color palette
                ci=None,           # Remove error bars
                order=['Category B', 'Category A', 'Category C']  # Custom order
               )
    plt.title("Average Sales by Product Category and Region")
    plt.xlabel("Product Category")
    plt.ylabel("Average Sales")
    plt.xticks(rotation=45)  # Rotate x-axis labels
    plt.show()

plot_avg_sales_regionwise()