data_visualization.ipynb

Kernel: Unknown Kernel

Data Visualization Notebook

This notebook demonstrates how to visualize and analyze sales data using reusable functions.

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

Data Loading

# Load sample sales data
data = pd.DataFrame({
    'month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'sales': [200, 220, 250, 270, 300],
    'region': ['North', 'North', 'East', 'East', 'West']
})
data.head()

Visualization

# Reusable function for plotting
def plot_sales(df, region=None):
    """
    Plot sales data.

    Args:
        df (pd.DataFrame): The input DataFrame containing sales data.
        region (str, optional): The region to filter data. Defaults to None.

    Returns:
        None
    """
    if region:
        df = df[df['region'] == region]

    plt.figure(figsize=(8, 5))
    sns.lineplot(data=df, x='month', y='sales', marker='o')
    plt.xlabel('Month')
    plt.ylabel('Sales')
    plt.show()

Plot sales for the North region

plot_sales(data, region='North')

Plot sales for all regions

plot_sales(data)