Admin dashboard PHP overview

A PHP admin dashboard is a web-based interface that allows administrators to manage and monitor various aspects of a website, application or business. It provides a centralized location for performing tasks and viewing important information, such as website traffic, user accounts, and data analytics.

A PHP Admin dashboards are typically designed to be user-friendly and easy to navigate, making it easy for administrators to quickly find and access the information they need. Some of the technology used to create an admin dashboard include HTML, CSS, JavaScript and PHP and other web development frameworks.

Make your work easier with our Admin dashboard and generate complete PHP source code.

Our PHP admin dashboard includes a robust analytics system that provides real-time data and statistics on website traffic, user behavior, and other metrics. This information can be used to make informed decisions about the website or application, such as identifying areas that need improvement.

Making work easier with the PHP admin dashboard involves utilizing the various features and tools that are available within the dashboard, such as analytics, reporting, and settings, to perform tasks quickly and efficiently, and make informed decisions about the website or application. Here are a few ways to do this:

• Utilize analytics: Use the analytics features of the dashboard to view real-time data and statistics on website traffic, user behavior, and other metrics. This information can be used to identify areas that need improvement, and make informed decisions about the website or application.


• Use reporting features: Use the reporting features of the dashboard to generate reports on various aspects of the website or application, such as sales, website traffic, and user activity. This will help track progress and measure the success of various initiatives.


• Streamline user management: Use the user management features of the dashboard to easily add, edit, and delete user accounts, and manage user permissions and roles. This will save time and reduce the need for manual processes.


• Customize settings: Use the settings features of the dashboard to configure various settings for the dashboard, charts and reports, such as color settings, font size and color settings, and background color settings. This will ensure that the dashboard or chart is running optimally and nicely.

Benefit of PHP Admin dashboard

One of the key benefits of using a PHP admin dashboard is that it allows administrators to perform tasks quickly and efficiently. For example, if an administrator needs to view a new user to the system, they can simply log into the dashboard and complete the task in a matter of minutes. This eliminates the need for manual processes, such as sending emails or making phone calls, which can save a significant amount of time and resources.

Another benefit of a PHP admin dashboard is that it can provide real-time information and analytics. This can help administrators make informed decisions about the website or application they are managing. For example, a dashboard might display the number of visitors to a website, the number of pages viewed, and the number of conversions.

How to create a PHP admin dashboard?

To create a PHP admin dashboard, developers typically use a variety of tools and technologies, such as PHP, HTML, CSS, and JavaScript. These technologies allow developers to create a user-friendly interface that is easy to navigate and understand.

the PHP Dashboard provide built-in support for creating admin dashboards, which can make the development process faster and more efficient. The PHP dashboard is a powerful tool that can help building, administrators manage and monitor a dashboard quickly and efficiently. It provides real-time information and analytics, and can be created using a variety of charts and reports. With the help of PHP Dashboard the Admin Dashboard will be much more efficient and easy.

How to code admin dashboard in PHP?

In our PHP Admin Dashboard example, we will develop Admin Dashboard PHP and link it to a MySQL database, fetch data, and create a dynamic dashboard using a drag and drop interface, before generating Dashboard PHP source code for our web application. We will demonstrate this using our freely released, open-source drag-and-drop Dashboard Builder. The following are the prerequisites for installing and running the PHP Dashboard..

Prerequisites

PHP Admin Dashboard framework can be installed on any platform, including Windows, Linux, and Ubuntu, as well as any platform that supports Apache, Nginx, and other web servers.

• PHP Version 7.2 or later
• Apache 2 or later
• Windows 7 or later /Linux 3 or later
• Firefox 52, Chrome 57, IE 8

Installation

There is a free trial version of PHP Dashboard.. available.

• You can download PHP Dashboard.. code from Download Dashboard Builder
• Place the files in a directory on the web server. e.g. …/www/yoursite/dashbboardbuilder-v3-FREE/
• Unzip the file dashboard.php using Extract Here option to the root folder of "dashboardbuilder"

Admin PHP MySQL Dashboard Template FREE with examples

Our Admin dashboard PHP template makes use of the Bootstrap 5 framework, D3.js, and HTML5, providing you with a completely responsive and dynamic dashboard. With this awesome PHP dashboard tool, you can quickly produce source code for your PHP application and develop interactive database-driven HTML, Bootstrap 5 and D3.js-based dynamic dashboards. The Admin dashboards PHP built with this fantastic tool are totally responsive and adaptable to any device. You may view your dashboards at any time and from any device, such as a PC, tablet, or mobile phone, using any standard browser.

Admin Dashboard PHP tutorial

How to build an attractive Admin Dashboard in PHP in minutes?

Before we begin learning how to develop a dynamic dashboard in Admin dashboard PHP and connect it to a database to retrieve data, we must first ensure that our PHP server (such as Apache, Nginx, or others) is configured to display files in the dashboard folder. chmod -R 777 dashbboardbuilder-v3-FREE gives read-write access to dashboardbuilder's folders and subfolders. Check your browser inspector/console to ensure that no errors are being detected and that all Dashboard Builder files are correctly loaded. We shall examine how to develop a dashboard in PHP step by step in the following phases.

1. Connect to the MySQL database
2. Enter SQL Query statement
3. Select X and Y axis
4. Changes to your chart
5. Create the source code for the PHP dashboard.

STEP-1: Connect to the MySQL database

• In your browser, open the web folder. http://localhost/dashboardbuilder





• The main panel of the PHP Dashboard is depicted in the above image. This tool is an HTML5-based fully responsive interface built with the most widely used PHP, HTML, JavaScript, Bootstrap 5 framework, and a powerful D3.js chart engine. The interface is simple in design, with a drag-and-drop feature that allows users to add as many chart panels as they want to customize the dashboard.
• Now click the Database icon
• The screen below will appear. In our Admin dashboard PHP example, we will connect to PHP MySQL Admin Dashboard and retrieve data from a sample MySQL database. Select database from the data source page.Select MySQL from the database list, enter database credentials and Save changes as instructed on the screen.

• When you click the save changes button, a green tick mark with a database appears, indicating that your database has been successfully connected..

This fantastic Admin dashboard tool allows you to connect to a variety of database sources using PDO, an acronym for Data Objects and the most consistent way to access databases in PHP applications. As stated in the introduction, this fantastic Dashboard PHP MySQL Open Source supports all major databases, including MySQL, MS SQL, SQLite, PostgreSQL, Sybase, and Cuboid. However, if you have data in Google Sheets, Excel, or CSV files, this great PHP dashboard can also fetch data from these sources using the upload sub-tab, as shown in the image above.

STEP-2: Enter SQL Query statement

• After successfully connecting to the database, our next step will be to retrieve data from the database..
• Select the chart settings option.

• As shown in the image below, a pop-up screen and a list of the tables will appear on the table list:

Our Admin dashboards include a powerful Query Builder and a smart SQL statement builder tool for quick and easy writing of complex SQL queries without the need for manual code writing, which is intended to simplify data retrieval from the database.

• When you click on a table, a default SQL statement appears in the SQL statement box, which you can alter as needed.
• You can use up to ten SQL statements at the same time to get data from various tables.

• In this example, we'll make a simple PHP application for sales management.This PHP dashboard will include a chart where customers may see sales statistics and keep product info.
• Now, type the following SQL query in the text field in the format shown below.

SELECT strftime('%Y-%m',o.shippeddate) as xaxis, sum(d.quantity) as yaxis from `order details` d, orders o where o.orderid = d.orderid group by strftime('%Y-%m',o.orderdate) limit 50

• Now we'll run our query and retrieve the data from the tables. Hit the Run Query button to execute the SQL query.

STEP-3: Select the X and Y axes

• The query result will be displayed. Now we must assign data from the x-axis to the x-axis column and data from the y-axis to the y-axis column. Choose your x-axis data from the X drop down list, and your y-axis data from the Y drop down list.
• Click the Save Changes   button

• As illustrated below, charts will appear on the screen.

STEP-4: Changes to your chart

• By sliding the Chart Panel's corner, you can change its size and position. According to the Bootstrap framework, the size and position are entirely responsive.

STEP-5: Create the source code for the PHP dashboard

• So far, our dashboard has been built successfully. In this step, we will generate the admin dashboard source code that we just created. To create an admin dashboard source code for our PHP application, click the Create PHP code   button.

• The admin dashboard source code for the chart will be generated automatically; you can copy and paste this dashboard PHP script into your PHP application.

Admin dashboard source code

This dashboard generator's auto-generated admin dashboard source code is shown below. You can use this dashboard PHP script in your PHP application. .

PHP dashboard code example::

/**
 * DashboardBuilder
 *
 * @author Diginix Technologies www.diginixtech.com
 * Support  - http://www.dashboardbuilder.net
 * @copyright (C) 2016-22 Dashboardbuilder.net
 * @version 5.7
 * @license: This code is under MIT license, you can find the complete information about the license here: https://dashboardbuilder.net/code-license */
 */

include("inc/dashboard_dist.php");  // copy this file to inc folder 


// for chart #1
$data = new dashboardbuilder(); 
$data->type =  "line";

$data->source =  "Database"; 
$data->rdbms =  "sqlite"; 
$data->servername =  "";
$data->username =  "";
$data->password =  "";
$data->dbname =  "data\Northwind.db";
$data->xaxisSQL[0]=  "SELECT strftime(^%Y-%m^,o.shippeddate) as xaxis, sum(d.quantity) as yaxis from `order details` d, orders o  where o.orderid = d.orderid group by strftime(^%Y-%m^,o.orderdate) limit 50";
$data->xaxisCol[0]=  "xaxis";
$data->yaxisSQL[0]=  "SELECT strftime(^%Y-%m^,o.shippeddate) as xaxis, sum(d.quantity) as yaxis from `order details` d, orders o  where o.orderid = d.orderid group by strftime(^%Y-%m^,o.orderdate) limit 50";
$data->yaxisCol[0]=  "yaxis";
$data->name = "linechart";
$data->title = "Line Chart";
$data->orientation = "";
$data->xaxistitle = "x-axis title";
$data->yaxistitle = "y-axis title";
$data->showgrid = "";
$data->showline = "";
$data->height = "167";
$data->width = "";
$data->col = "0";
$result[0] = $data->result();

?>

<!DOCTYPE html>
<html> 
<head> 
	<script src="assets/js/dashboard.min.js"></script> <!-- copy this file to assets/js folder --> 
	<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css"> <!-- Bootstrap CSS file, change the path accordingly --> 

<style>
@media screen and (min-width: 960px) {
.id0 {position:absolute;margin-top:67px;}

}
.panel-heading {line-height:0.7em;}
</style>


</head>
<body> 

<div class="container-fluid main-container">
<div class="col col-12">
<div class="row">
<div class="col-lg-4 offset-lg-4 col-xs-12 id0">
<div class="card-default">
<div class="card-heading">Line Chart</div>
    <div class="card-body">
        <?php echo $result[0];?>
    </div>
</div>
</div>
</div>
</div>
</div>
</body>

Dashboard performance indicators - a comprehensive guide to performance indicators Dashboard

How to create your Performance Indicators Dashboard?

Regardless of size, every business has certain processes or metrics that it needs to track. Without measuring this data, business rely on guesswork. The Dashboard Performance Indicator is a great tool to translate this data into charts and graphs that reflect the performance of your business. But how to start? What is an efficiency rate? How to create a performance indicator dashboard?

This article provides an overview of performance indicator dashboards. It contains valuable information and examples for both beginners and seasoned professionals.

What is a Performance Indicator dashboards and why you need one?

The performance indicators dashboard is a commonly used indicator of performance against strategic goals. Dashboard performance indicators help reduce the complexity associated with performance monitoring by reducing the multidimensionality of the actual number of performance indicators.

Performance indicator dashboards are often used in organizations to track the operational performance of departments, programs or individuals against goals or objectives. They provide managers with tools to obtain information and make decisions.

The most important benefits we summarized for you, are listed below:

1. SPI Dashboard

SPI Dashboards (Strategic Performance Indicator Dashboards) typically reflect the health of the business and track performance against future business goals, such as expansion, development, growth etc .

2. OPI Dashboard

OPI Dashboards (Operational Performance Indicator Dashboards) are usually associated with strategic performance indicators. However, they focus on core activities or areas such as product development, marketing or internal projects. This information is used to make daily management decisions.

3. IPI Dashboard

IPI Dashboard (Individual performance Indicator Dashboards) are used to measure how well an employee's skills are being used on the job. They are also used to provide managers with a tool to evaluate, in particular, how to manage salaries in departments such as sales.

Related:

• An overview of KPI Dashboard
• Why KPI Dashboard is Important?

How to build your Dashboard Performance Indicators

Creating performance indicator dashboards is a relatively simple process. Setting goals is the first step. Then find the best scale (also called frequency) to control. This basic structure then defines the goals or objectives and the source of the data.

A Performance Indicator Dashboard should present your Performance Indicators and metrics in a concise and useful way for a specific purpose. It is a tool to provide information "at a glance" to the right audience to achieve goals and objectives.

But it can easily be overlooked when designing a dashboard. With so much data available from an ever-growing array of sources, how do you avoid unproductive dashboards and audience overload?

Here are some important points to consider:

• Keep it simple: Target a limited number of Performance Indicator dashboards on a single screen for a goal, project or department. Users can miss important information, trends and opportunities when data is hidden or "charts" are overloaded.
• Show trends over time: For charts or data to be truly useful, the information must provide context and history. This allows viewers to make decisions based on seasonal trends they may have missed.
• Telling a story: Like a graphic explanation, it is best understood when explained in the context of a story. Statistics showing the steps in completing the registration process can provide a clear path to follow.
• Avoid rainbow overload: Excessive color schemes can quickly make a dashboard unreadable. Stick to a simple color palette.

Revision, Fix and Repeat

As the business environment changes over time, organizations must adapt and adjust accordingly – and performance indicator dashboards are no different. It is a continuous cycle of revision, Fix and repetition.

Communication is key; Regular feedback from all areas of the business, including performance indicator dashboard owners and dashboard users, is critical. Frequent review tips are a great way to keep your dashboard from falling behind. A flexible dashboard, streamlined and working at its optimum, provides advantages such as:

• More competent processes.
• Management and strategic decisions can be made even faster.
• Bring attention to underlying problems before they become major problems.
• Removes dashboard bloat - (The common condition of performance indicator dashboards is becoming a control mechanism for almost everything.)

Some useful advice about the dashboard

Here are some tips and best practices for getting the most out of your dashboards.

The Performance Indicator Dashboard needs owners

If you have a dashboard of performance indicators, you will do well. Without owners, it is unclear who interprets the data, communicates the results and initiates the necessary actions.

Segment your Performance Indicator Dashboard by action

Group dashboards of performance Indicator and create individual dashboards targeted to specific audiences. Strategy dashboards visualize company growth and goals. Operational dashboards for daily activities such as sales departments. Analytics dashboards to analyze trends and research. Avoid trying to create a single dashboard for all these functions. Breaking them up gives the audience a single target to focus on.

Don't make it complicated

When it comes to designing performance indicator dashboards, less is more. Aim for no more than nine (09) views on one screen. Reduce the number of colors and use graphs of consistent size. For each chart, ask yourself if all historical data should be displayed if your audience only wants real-time data.

Use Vanity Metrics carefully

A useful performance indicator dashboard, such as the number of users who complete a particular stage of a registration process, provides information for making decisions that can improve performance. Vanity metrics, on the other hand, such as the number of website visitors are useful, but they are subject to fluctuations, manipulations, and don't tell the real story. Is this audience really interested in buying your product or service?

Avoid fancy widgets

There are many dashboard providers competing for a unique selling proposition, so new and unique widgets appear almost daily. For example, "last time in Spain", image rotation tools or "last tweets" provide little or no useful and concrete information and only add to the confusion.

Regular Reviews and Correction

Like any business tool, they require regular inspection and maintenance in order to function at their best. The participation of Performance Indicator Dashboard owners in regular "optimization" reviews reduces the information load and increases productivity even more.

Set up your dashboard.

There is nothing when creating a fancy dashboard if it's limited to one person or hidden behind dozens of logins. The information received should be communicated to all interested parties involved in the process. Feel free to share your dashboard internally and externally and consider providing a feedback mechanism.

Combine metrics to create effective Performance Indicator Dashboard

Combining the metrics into a actionable Performance Indicator Dashboard provides guidance for actionable action. For example, dividing the number of subscriptions to a service by the number that completes a particular stage yields information that can help you change parts of the process that are not performing inferiority.

Accuracy of Data

Garbage in, Garbage out. It doesn't matter how good your dashboard design looks if your data is inaccurate. The Performance Indicator Dashboard doesn't have the right fuel to perform. If fairly practicable, check the reliability and accuracy of your data.

Implementing without measurements

Implementing the Performance Indicator Dashboard at an enterprise-wide can be difficult. Start small; even a single graph can provide some welcome insights, but it will actually remain unknown without measurements.

Are you ready to try your hand at Performance Indicator Dashboard ? Try Performance Indicator Dashboard !

Mastering Heatmap Charts: From Insights to Impactful Visuals

What is a Heatmap Chart? Exploring Definition, Examples, Procedure, Techniques, and Elements

A heatmap chart is a visual depiction of data that employs a color-coded two-dimensional grid, where the intensity of each cell's color corresponds to a particular data value. A heatmap chart serves as a valuable instrument for the visualization and examination of extensive datasets, enabling the recognition of patterns, trends, and discrepancies within the data. It finds applications in diverse domains, including social network analysis, financial market assessment, scientific investigations, and customer segmentation, ultimately enhancing the generation of data-driven insights and informed decision-making.

What is a heatmap used for?

A heatmap chart is used for visualizing and analyzing data patterns, trends, and variations within large datasets. In essence, heatmap charts are a versatile data visualization tool that serves a wide range of purposes by simplifying complex data, enhancing data-driven insights, and improving decision-making across different industries and fields of study. It helps in the following ways:

1. Identifying Trends: Heatmap charts make it easy to spot trends and patterns in data by using color intensity to represent data values, allowing users to quickly identify high or low points.
2. Data Comparison: They enable users to compare data across different categories, variables, or time periods, making it useful for performance analysis and benchmarking.
3. Anomaly Detection: Heatmap charts can highlight outliers or anomalies within a dataset by displaying them as distinct color variations, aiding in anomaly detection and troubleshooting.
4. Data Exploration: Heatmap charts are an excellent tool for exploring data, as they provide an at-a-glance overview of the entire dataset, helping users focus on areas of interest.
5. User Behavior Analysis: In website analytics and user experience studies, heatmaps are used to track and analyze user interactions, such as clicks, mouse movements, and scrolling behavior.
6. Risk Assessment: In fields like finance and security, heatmap charts are used to assess risks and vulnerabilities by visualizing data related to security breaches, financial market fluctuations, and more.
7. Scientific Research: Scientists use heatmap charts to visualize complex scientific data, including gene expression patterns, climate data, and spatial distributions.
8. Customer Insights: In marketing and customer segmentation, heatmap charts help businesses identify customer preferences and segments based on purchase history, demographic data, or geographic location.
9. Resource Allocation: Heatmap charts assist in optimizing resource allocation by showing where resources are most and least utilized, helping organizations make informed decisions about resource allocation.
10. Decision-Making: Heatmap charts provide a clear visual representation of data, aiding decision-makers in making informed choices in various domains, from business strategy to healthcare planning.

What type of chart is a heatmap?

A heatmap falls under the category of charts or graphical representations utilized to visualize and analyze data. It is a particular type of two-dimensional graphical display where data values are depicted through a color-coding scheme. In this grid-like structure, each cell typically represents a specific combination of variables or categories. Heatmap charts are widely employed for presenting data, emphasizing patterns, trends, and variations, thus making them an invaluable tool in the realm of data analysis and visualization.

What is heatmap in data visualization?

In data visualization, a heatmap is a graphical representation used to display data more accessible and understandable. They are particularly effective for visualizing large datasets and are used across various domains, including website analytics, scientific research, financial analysis, and more, to provide insights into data relationships and distributions. Heatmap charts offer a powerful visual tool for data analysts and decision-makers to make data-driven assessments and identify key insights within their data.

Heatmap chart example

Here's an example of a heatmap chart: Suppose you are analyzing website user engagement data for an e-commerce site. You have a dataset that tracks the number of products sold in region users within different region groups (columns) and product categories (rows). You want to visualize this data to identify patterns and trends in user behavior.

Your pivot table might look something like this:

In this example, each cell in the heatmap represents the number of products sold by users in a specific region and product category. The color intensity of each cell corresponds to the data value, with warmer colors (e.g., darker shades of orage) indicating higher values and cooler colors (e.g., shades of yellow) indicating lower values.

Your heatmap chart might look something like this:

By analyzing this heatmap chart, you can quickly discern patterns such as which age groups are most interested in specific product categories. For instance, region Sub Saharan Africa 145k show a high interest in fruits, while users in Middle East and North Africa 79k have a preference for clothing.

Heatmap charts like this help you gain insights into data relationships and make data-driven decisions in various fields, including marketing, user experience design, and product development.

Heat map analysis

Heat map analysis refers to the process of using heat map charts to explore and interpret data. These charts visually represent data by employing color-coded grids, where each cell's color intensity corresponds to specific data values.

Heat map analysis is an invaluable technique for extracting insights from data, revealing connections between variables, and supporting data-driven decision-making in a multitude of domains. It simplifies the visualization of intricate data, rendering it accessible and actionable for analysts and decision-makers.

Here's a succinct overview of heat map analysis:

• Data Visualization: Heat map analysis is employed to visually represent complex datasets, making it easier to identify patterns, trends, and variations within the data. The color gradient used in the heatmap allows for the quick identification of high and low values.
• Two-Dimensional Grid: In heat map analysis, data is organized into a two-dimensional grid, often with categories or variables represented along both the horizontal and vertical axes. Each cell in the grid represents a unique combination of these categories or variables.
• Color Coding: The intensity of color within each cell reflects the magnitude of the data value it represents. Typically, warmer colors like red or orange indicate higher values, while cooler colors like blue or green indicate lower values.
• Data Aggregation: Heat maps often involve data aggregation within each cell, which can include calculations like averaging, summing, or percentages. This helps provide a summary of data in each category combination.
• Pattern Recognition: Heat map analysis is particularly useful for recognizing patterns and trends in data. Analysts can quickly spot clusters of high or low values, which can inform decision-making or further exploration.
• Applications: Heat map analysis finds applications in various fields, including business analytics, biology (e.g., gene expression analysis), finance (e.g., stock market analysis), and user experience research (e.g., website click patterns).
• Interactivity: In digital environments, interactive heat maps allow users to explore data further by hovering over cells for specific values or by clicking on cells to access more detailed information.

A Comprehensive Guide to Heatmap chart: Step-by-Step Creation

Creating a heatmap chart can be a powerful way to visualize data, especially when dealing with large datasets or when you want to highlight patterns and trends within your data. In this comprehensive guide, we'll walk you through the steps to create a heatmap chart using the dashboard builder and the popular data visualization tool along with some explanations and tips along the way.

Before we start, make sure you have the following prerequisites installed:

APPLIES TO:    On-premises    Online   Desktop

Prerequisites

The Dashboard Builder can be installed any platforms like Windows, Linux, Mac and Ubuntu or any other platforms support Apache.

• PHP Version 7.2 or later
• Apache 2 or later
• Windows 7 or later /Linux 3 or later
• Firefox 52, Chrome 57, IE 8

Installation

• Download from https://dashboardbuilder.net/download-free-dashboard
• Place the files in a directory on the web server. e.g. …/www/dashboar/dbuilder/
• Unzip the file using Extract Here option to the root folder of "dashboardbuilder"

How to create heatmap chart - Step-by-Step Guide

Let's walk through the process of creating a heatmap chart using a simple example dataset. For this guide, we'll use a fictional sales dataset with columns for "Item Type," "Region," and "Units Sold."

Creating a heatmap chart involves the following steps:

Step 1: Open Your Data

Launch dashboard settings after establishing a database connection. And select the heatmap chart.

In this article we have used the following query to retrieve the data

Step 2: Select Your Data

To retrieve data from your database, create your SQL query. You can also just click the desired table in the table list to retrieve the table's default data.

Step 3: Insert Pivot Table Query

On the right side, go to the "Fields" tab. A new tab will appear. You'll see a panel to configure your pivot table fields

• Row: Select the fields from the dropdown list you want to categorize your data by. In our example, select the "Region" fields here.
• Column: Select the fields you want to use as column headers. In this case, we'll add the "Item Type" field.
• Value: This section is for the numerical data you want to analyze. Select the "Units Sold" field here.
• Calculations: By default, it will display the sum of 'Unit Sold' you can select your desired formula that you want to apply. In this case, we'll select the "Sum"
• Now click the Apply button

An auto generated SQL query will be generated with a pivot table

Step 4: Explore and Analyze

Now you have your heatmap chart! Explore the data by collapsing or expanding rows and columns, changing the values, and experimenting with filters. This dynamic analysis helps you gain insights from your data quickly.

Heatmap chart PHP source code

With a single, straightforward action, you have the capability to generate PHP source code for your heatmap chart. Simply navigate to the "Publish" button and select the "PHP code" option to effortlessly create the necessary PHP code for your Heatmap chart.

<?php
ob_start();
/**
 * DashboardBuilder
 *
 * @author Diginix Technologies www.diginixtech.com
 * Support  - https://www.dashboardbuilder.net
 * @copyright (C) 2016-2023 Dashboardbuilder.net
 * @version 6.5
 * @license: This code is under MIT license, you can find the complete information about the license here: https://dashboardbuilder.net/code-license
 */

$_SESSION["DF"]="";
$_SESSION["NF0"]="";
$_SESSION["NF"]="";

include("../inc/dashboard_dist.php");  // copy this file to inc folder 
?>
<!DOCTYPE html>
<html lang="en-us" dir="ltr">
<head>
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1">
	<script src="https://cdn.jsdelivr.net/gh/DashboardBuilder/cdn@master/v55/dashboard.min.js"></script> <!-- copy this file to assets/js folder -->
	<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/DashboardBuilder/cdn@master/v55/bootstrap.min.css"> <!-- Bootstrap 5 CSS file, change the path accordingly -->
	<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/DashboardBuilder/cdn@master/v55/font-awesome.min.css">  <!-- Font Awesome CSS file, change the path accordingly -->
	
<style>
@media screen and (min-width: 960px) {
.id0 {position:absolute; top:4px;}

}
.card-header {line-height:0.7em;}
#number {font-size:32px; font-weight:bold;text-align:center;margin-top:-10px;}
#number_legand {font-size:11px; text-align:center;}
.panel-body {  box-shadow: 5px 5px 35px  #e0e0e0;color:#787b80;}
.page-header {margin-top:-30px;}.dropdown-toggle{font-size:12px;line-height:12px;}
	.selectoption {font-size:12px !important;}
	.bs-searchbox > input {
	  font-size: 12px;
	  height:26px;
	}
</style>

</head>
<body> 

<?php
// for chart #1
$data = new dashboardbuilder(); 
$data->type[0]=  "heatmap";

$data->legacy = "";
$data->source =  "Database"; 
$data->rdbms =  "mysql"; 
$data->servername =  "localhost";
$data->username =  "root";
$data->password =  "0IhmBpPwnaCxKQXSsHI6qw==";
$data->dbname =  "salesreport";
$data->toImage = "Download graph";
$data->zoomin = "Zoom in";
$data->zoomout = "Zoom out";
$data->autoscale = "Reset";
$data->filterlabel = "Filter";
$data->forecastlabel = "Forecast";
$data->filter = "false";
$data->xaxisSQL[0]=  "SELECT * FROM salesrecords LIMIT 10;";
$data->xaxisCol[0]=  "Region";
$data->xsort[0]=  "";
$data->xmodel[0]=  "";
$data->forecast[0]=  "";
$data->yaxisSQL[0]=  "SELECT * FROM salesrecords LIMIT 10;";
$data->yaxisCol[0]=  "Region";
$data->ysort[0]=  "";
$data->ymodel[0]=  "";
$data->sql[0] = "SELECT `Region`, SUM(CASE WHEN (`Item Type`='Baby Food') THEN `Units Sold` ELSE 0 END) AS `Baby Food`,SUM(CASE WHEN (`Item Type`='Beverages') THEN `Units Sold` ELSE 0 END) AS `Beverages`,SUM(CASE WHEN (`Item Type`='Cereal') THEN `Units Sold` ELSE 0 END) AS `Cereal`,SUM(CASE WHEN (`Item Type`='Clothes') THEN `Units Sold` ELSE 0 END) AS `Clothes`,SUM(CASE WHEN (`Item Type`='Cosmetics') THEN `Units Sold` ELSE 0 END) AS `Cosmetics`,SUM(CASE WHEN (`Item Type`='Fruits') THEN `Units Sold` ELSE 0 END) AS `Fruits`,SUM(CASE WHEN (`Item Type`='Household') THEN `Units Sold` ELSE 0 END) AS `Household`,SUM(CASE WHEN (`Item Type`='Meat') THEN `Units Sold` ELSE 0 END) AS `Meat`,SUM(CASE WHEN (`Item Type`='Office Supplies') THEN `Units Sold` ELSE 0 END) AS `Office Supplies`,SUM(CASE WHEN (`Item Type`='Personal Care') THEN `Units Sold` ELSE 0 END) AS `Personal Care`,SUM(CASE WHEN (`Item Type`='Snacks') THEN `Units Sold` ELSE 0 END) AS `Snacks`,SUM(CASE WHEN (`Item Type`='Vegetables') THEN `Units Sold` ELSE 0 END) AS `Vegetables` FROM salesrecords GROUP BY `Region`; ";

$data->name = "0";
$data->title = "Charttable Chart";
$data->orientation = "v";
$data->dropdown = "false";
$data->side = "left";
$data->toImage = "Download graph";
$data->zoomin = "Zoom in";
$data->zoomout = "Zoom out";
$data->autoscale = "Reset";
$data->filter = "false";
$data->forecastlabel = "Forecast";
$data->legposition = "";
$data->xaxistitle = "";
$data->yaxistitle = "";
$data->datalabel = "true";
$data->showgrid = "true";
$data->showline = "true";
$data->tablefontsize = "12";
$data->height = "420";
$data->width = "0";
$data->col = "0";

$data->plot = "dynamic";
$data->font_color = "";
$data->bg_color = "";
$data->color[0]=  "#ff8040";
$result[0] = $data->result();?>
<div class="container-fluid main-container position-relative">
<div class="col col-md-12 col-lg-12 col-xs-12">
	<div class="row my-4">
	<div class="col-md-8 col-xs-12 offset-md-2 id0">
	<div class="card-default shadow">
		<div class="card-body bgcolor">
		<span class="d-flex justify-content-start mx-2 font-color">Charttable Chart</span>
			
		</div>
	</div>
	</div>
        </div>
</div>
</div>


</body>

Conclusion

In summary, Heatmap charts are versatile data visualization tools that employ color-coded grids to represent and analyze data, making complex information accessible and insightful. They serve diverse purposes, from identifying trends and anomalies in datasets to understanding user behavior, finding applications in fields like social network analysis, financial market assessment, and scientific research. Heatmaps simplify complex data visualization by using color intensity to represent values within a two-dimensional grid. The process of creating a heatmap chart involves data preparation, tool selection, customization, and careful review, with options for interactivity and annotations to enhance understanding. Once created, heatmap charts can be saved, exported, and shared, making them invaluable for conveying insights and facilitating data-driven decision-making across various domains.

Are you ready to try your hand at heatmap chart ? Try Data Visualization tool for Heatmap Chart