HUST_25_auto_qiming_python

# Python Data Analysis Example

## Data Cleaning
```python
import pandas as pd

# Load dataset
file_path = 'sales_data.csv'
data = pd.read_csv(file_path)

# Remove duplicates
data = data.drop_duplicates()

# Handle missing values
data = data.fillna(data.mean())
```

## Data Visualization
```python
import matplotlib.pyplot as plt

# Plot sales trends
data['Date'] = pd.to_datetime(data['Date'])
data.set_index('Date', inplace=True)
data['Sales'].plot(figsize=(10, 5), title='Monthly Sales Trends')
plt.show()
```

## Key Insights
- Sales peaked in Q4 2022
- Average monthly sales: $125,000
- Top 3 products by revenue: Product A, Product B, Product C