CSV (Comma-Separated Values) files store structured data, making them useful for analysis. Converting CSV data into bar charts helps in better visualization and decision-making.
Ensure your CSV file is properly formatted with headers. Example:
Category,Sales Electronics,5000 Clothing,3000 Furniture,4000 Groceries,7000
Since JavaScript works better with JSON, convert CSV to JSON using Python:
import csv import json csv_file = "data.csv" json_file = "data.json" data = [] with open(csv_file, "r") as file: reader = csv.DictReader(file) for row in reader: data.append(row) with open(json_file, "w") as file: json.dump(data, file, indent=4) print("CSV converted to JSON successfully!")
Use Chart.js to visualize the data as a bar chart.
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script> <canvas id="barChart"></canvas> <script> fetch("data.json") .then(response => response.json()) .then(data => { let labels = data.map(item => item.Category); let values = data.map(item => item.Sales); new Chart(document.getElementById("barChart"), { type: "bar", data: { labels: labels, datasets: [{ label: "Sales Data", data: values, backgroundColor: "blue" }] } }); }); </script>
Modify the chart by changing colors, labels, and data options in the Chart.js configuration.
Users can download the chart as an image by adding a button:
<button onclick="downloadChart()">Download Chart</button> <script> function downloadChart() { let canvas = document.getElementById("barChart"); let link = document.createElement("a"); link.href = canvas.toDataURL("image/png"); link.download = "bar_chart.png"; link.click(); } </script>
By following these steps, you can easily convert CSV data into bar charts for better visualization. Using Chart.js, you can make interactive charts and export them for further use.