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Convert CSV to styled HTML reports

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Computer Science

To convert a CSV file to a styled HTML report, you can follow this process using Python and Pandas with basic HTML and CSS for styling. Below is a script that takes a CSV file and generates an HTML file with a clean, styled table layout.

Python Script to Convert CSV to Styled HTML

python
import pandas as pd

# Load CSV file
csv_file = "data.csv"  # Replace with your CSV file path
df = pd.read_csv(csv_file)

# Define custom HTML style
style = """
<style>
    body {
        font-family: Arial, sans-serif;
        padding: 20px;
    }
    h2 {
        text-align: center;
        color: #333;
    }
    table {
        width: 100%;
        border-collapse: collapse;
        margin-top: 20px;
        font-size: 14px;
    }
    th, td {
        border: 1px solid #ddd;
        padding: 8px;
        text-align: left;
    }
    th {
        background-color: #4CAF50;
        color: white;
    }
    tr:nth-child(even) {
        background-color: #f9f9f9;
    }
    tr:hover {
        background-color: #f1f1f1;
    }
</style>
"""

# Convert DataFrame to HTML with style
html_content = f"""
<html>
<head>{style}</head>
<body>
<h2>CSV Report</h2>
{df.to_html(index=False, escape=False, classes='table')}
</body>
</html>
"""

# Save HTML file
output_file = "report.html"
with open(output_file, "w", encoding="utf-8") as file:
    file.write(html_content)

print(f"HTML report generated: {output_file}")

Notes:

Replace "data.csv" with the path to your actual CSV file.
You can modify the CSS in the style variable to match your branding or design preferences.
The table includes alternating row colors and hover effects for better readability.

Let me know if you’d like to embed images, charts, or conditional formatting in the report as well.

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