Hi, As mentioned in this link https://video2.skills-academy.com/en-us/azure/synapse-analytics/spark/apache-spark-data-visualization I want to use D3.js to visualize my data. How do I send data from my pyspark dataframe into displayHTML() to visualize it?

@Raghul Kannan - Thanks for the question and using MS Q&A platform. Did you get a chance to look at the following code to create the visualization as mentioned in the documentation: displayHTML() option , which helps to send data into displayHTML function in Azure Synapse Analytics. To send data from your PySpark DataFrame into the displayHTML() function to visualize it using D3.js in Azure Synapse Analytics, you can follow these steps: Convert the PySpark DataFrame to JSON: You can use the toJSON() function to convert the PySpark DataFrame to a JSON string. This will allow you to pass the data into the JavaScript function for visualization. Create the HTML Template with D3.js: Create an HTML template that includes your D3.js script for visualization. Within this template, you'll use a placeholder to inject the JSON data. Inject the Data into the HTML Template: Replace the placeholder in the HTML template with the actual JSON data. You can use string formatting to replace the placeholder with the JSON data. Use displayHTML() to Render the HTML: Use the displayHTML() function to render the HTML with your D3.js visualization. Here's an example code snippet that demonstrates these steps: import json # Convert PySpark DataFrame to JSON json_data = df.toJSON().collect() # Create HTML template with D3.js html_template = """ <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>D3.js Visualization</title> <script src="https://d3js.org/d3.v4.js"></script> </head> <body> <div id="chart"></div> <script> var data = {0}; // D3.js code for visualization using data </script> </body> </html> """ # Inject data into HTML template html = html_template.format(json.dumps(json_data)) # Render HTML with D3.js visualization displayHTML(html) In this example, df is your PySpark DataFrame. The toJSON() function is used to convert the DataFrame to a JSON string, which is then collected into a list using the collect() function. The JSON data is then injected into the HTML template using string formatting. Finally, the displayHTML() function is used to render the HTML with your D3.js visualization. Hope this helps. Do let us know if you any further queries. If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

Accepted answer

PRADEEPCHEEKATLA-MSFT 84,051 Microsoft Employee

@Raghul Kannan - Thanks for the question and using MS Q&A platform.

Did you get a chance to look at the following code to create the visualization as mentioned in the documentation: displayHTML() option, which helps to send data into displayHTML function in Azure Synapse Analytics.

To send data from your PySpark DataFrame into the displayHTML() function to visualize it using D3.js in Azure Synapse Analytics, you can follow these steps:

Convert the PySpark DataFrame to JSON: You can use the toJSON() function to convert the PySpark DataFrame to a JSON string. This will allow you to pass the data into the JavaScript function for visualization.
Create the HTML Template with D3.js: Create an HTML template that includes your D3.js script for visualization. Within this template, you'll use a placeholder to inject the JSON data.
Inject the Data into the HTML Template: Replace the placeholder in the HTML template with the actual JSON data. You can use string formatting to replace the placeholder with the JSON data.
Use displayHTML() to Render the HTML: Use the displayHTML() function to render the HTML with your D3.js visualization.

Here's an example code snippet that demonstrates these steps:

import json

# Convert PySpark DataFrame to JSON
json_data = df.toJSON().collect()

# Create HTML template with D3.js
html_template = """
<!DOCTYPE html>
<html>
<head>
  <meta charset="utf-8">
  <title>D3.js Visualization</title>
  <script src="https://d3js.org/d3.v4.js"></script>
</head>
<body>
  <div id="chart"></div>
  <script>
    var data = {0};
    // D3.js code for visualization using data
  </script>
</body>
</html>
"""

# Inject data into HTML template
html = html_template.format(json.dumps(json_data))

# Render HTML with D3.js visualization
displayHTML(html)

In this example, df is your PySpark DataFrame. The toJSON() function is used to convert the DataFrame to a JSON string, which is then collected into a list using the collect() function. The JSON data is then injected into the HTML template using string formatting. Finally, the displayHTML() function is used to render the HTML with your D3.js visualization.

Hope this helps. Do let us know if you any further queries.

If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

Raghul Kannan 146 Reputation points

2024-07-01T06:20:07.9666667+00:00

@PRADEEPCHEEKATLA-MSFT Hi, Can you add the visualization code in the same example as well, let's say a line chart?
Raghul Kannan 146 Reputation points

2024-07-01T11:52:34.28+00:00

@PRADEEPCHEEKATLA-MSFT It's also very difficult to debug what's going on inside displayHTML() function, how do I use console.log() or similar functionalities to print values for troubleshooting?

PRADEEPCHEEKATLA-MSFT 84,051 Microsoft Employee

@Raghul Kannan -

Here is an example of how you can visualize your data as a line chart using D3.js within Azure Synapse Analytics and how to include console.log() statements for debugging.

Step-by-Step Example with Line Chart and Debugging

Convert the PySpark DataFrame to JSON Convert your PySpark DataFrame to a JSON string.

# Assuming you have a PySpark DataFrame called df
json_data = df.toJSON().collect()

Create the HTML Template with D3.js for a Line Chart Include console.log() statements for debugging.

html_template = """
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>D3.js Line Chart Visualization</title>
    <script src="https://d3js.org/d3.v5.min.js"></script>
    <style>
        .line {
            fill: none;
            stroke: steelblue;
            stroke-width: 2px;
        }
    </style>
</head>
<body>
    <script>
        // Replace this line with the JSON data from the PySpark DataFrame
        const data = JSON.parse('<DATA_PLACEHOLDER>');
        console.log("Data received:", data); // Debugging

        // Example D3.js line chart visualization
        const svg = d3.select("body").append("svg")
            .attr("width", 600)
            .attr("height", 400);

        const margin = {top: 20, right: 20, bottom: 30, left: 50},
              width = +svg.attr("width") - margin.left - margin.right,
              height = +svg.attr("height") - margin.top - margin.bottom;

        const g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");

        const x = d3.scaleTime().rangeRound([0, width]);
        const y = d3.scaleLinear().rangeRound([height, 0]);

        const line = d3.line()
            .x(d => x(new Date(d.date)))  // Assuming 'date' is in your data
            .y(d => y(d.value));  // Assuming 'value' is in your data

        x.domain(d3.extent(data, d => new Date(d.date)));
        y.domain(d3.extent(data, d => d.value));

        g.append("g")
            .attr("transform", "translate(0," + height + ")")
            .call(d3.axisBottom(x));

        g.append("g")
            .call(d3.axisLeft(y));

        g.append("path")
            .datum(data)
            .attr("class", "line")
            .attr("d", line);
    </script>
</body>
</html>
"""

Certainly! Here is an example of how you can visualize your data as a line chart using D3.js within Azure Synapse Analytics and how to include console.log() statements for debugging.

Step-by-Step Example with Line Chart and Debugging

Convert the PySpark DataFrame to JSON Convert your PySpark DataFrame to a JSON string.

python Copy code

Assuming you have a PySpark DataFrame called df

json_data = df.toJSON().collect() 2. Create the HTML Template with D3.js for a Line Chart Include console.log() statements for debugging.

html Copy code html_template = """ <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>D3.js Line Chart Visualization</title> <script src="https://d3js.org/d3.v5.min.js"></script> <style> .line { fill: none; stroke: steelblue; stroke-width: 2px; } </style> </head> <body> <script> // Replace this line with the JSON data from the PySpark DataFrame const data = JSON.parse('<DATA_PLACEHOLDER>'); console.log("Data received:", data); // Debugging

    // Example D3.js line chart visualization
    const svg = d3.select("body").append("svg")
        .attr("width", 600)
        .attr("height", 400);

    const margin = {top: 20, right: 20, bottom: 30, left: 50},
          width = +svg.attr("width") - margin.left - margin.right,
          height = +svg.attr("height") - margin.top - margin.bottom;

    const g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");

    const x = d3.scaleTime().rangeRound([0, width]);
    const y = d3.scaleLinear().rangeRound([height, 0]);

    const line = d3.line()
        .x(d => x(new Date(d.date)))  // Assuming 'date' is in your data
        .y(d => y(d.value));  // Assuming 'value' is in your data

    x.domain(d3.extent(data, d => new Date(d.date)));
    y.domain(d3.extent(data, d => d.value));

    g.append("g")
        .attr("transform", "translate(0," + height + ")")
        .call(d3.axisBottom(x));

    g.append("g")
        .call(d3.axisLeft(y));

    g.append("path")
        .datum(data)
        .attr("class", "line")
        .attr("d", line);
</script>

</body> </html> """ 3. Inject the Data into the HTML Template Replace the placeholder with the actual JSON data.

import json

# Convert the JSON list to a JSON string
json_str = json.dumps(json_data)

# Inject the JSON string into the HTML template
html_content = html_template.replace('<DATA_PLACEHOLDER>', json_str)

Use displayHTML() to Render the HTML Render the HTML with your D3.js visualization and debugging statements.

displayHTML(html_content)

Complete Example with Line Chart and Debugging

# Assuming you have a PySpark DataFrame called df
json_data = df.toJSON().collect()
import json

# Create the HTML template with D3.js
html_template = """
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>D3.js Line Chart Visualization</title>
    <script src="https://d3js.org/d3.v5.min.js"></script>
    <style>
        .line {
            fill: none;
            stroke: steelblue;
            stroke-width: 2px;
        }
    </style>
</head>
<body>
    <script>
        // Replace this line with the JSON data from the PySpark DataFrame
        const data = JSON.parse('<DATA_PLACEHOLDER>');
        console.log("Data received:", data); // Debugging

        // Example D3.js line chart visualization
        const svg = d3.select("body").append("svg")
            .attr("width", 600)
            .attr("height", 400);

        const margin = {top: 20, right: 20, bottom: 30, left: 50},
              width = +svg.attr("width") - margin.left - margin.right,
              height = +svg.attr("height") - margin.top - margin.bottom;

        const g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");

        const x = d3.scaleTime().rangeRound([0, width]);
        const y = d3.scaleLinear().rangeRound([height, 0]);

        const line = d3.line()
            .x(d => x(new Date(d.date)))  // Assuming 'date' is in your data
            .y(d => y(d.value));  // Assuming 'value' is in your data

        x.domain(d3.extent(data, d => new Date(d.date)));
        y.domain(d3.extent(data, d => d.value));

        g.append("g")
            .attr("transform", "translate(0," + height + ")")
            .call(d3.axisBottom(x));

        g.append("g")
            .call(d3.axisLeft(y));

        g.append("path")
            .datum(data)
            .attr("class", "line")
            .attr("d", line);
    </script>
</body>
</html>
"""

# Convert the JSON list to a JSON string
json_str = json.dumps(json_data)

# Inject the JSON string into the HTML template
html_content = html_template.replace('<DATA_PLACEHOLDER>', json_str)

# Render the HTML with displayHTML()
displayHTML(html_content)

**Debugging: **

To debug the visualization, open the browser's developer tools (usually accessed by pressing F12 or Ctrl+Shift+I). The console.log("Data received:", data); statement will print the data to the console, allowing you to inspect the data and debug your D3.js code.

Hope this helps. Do let us know if you any further queries.

Share via

How to send data into displayHTML function in Azure Synapse Analytics

Assuming you have a PySpark DataFrame called df

0 additional answers