vlty

Chartlet is a lightweight, performance-focused plugin for creating beautiful, interactive charts and graphs via shortcodes.
Stop bloating your database! Unlike other chart plugins that store every graph as a custom post type, Chartlet stores all configurations directly within the shortcode. This makes your site faster and your data easier to manage.
Using the power of Chart.js (loaded locally for maximum privacy and GDPR compliance), Chartlet allows you to visualize data in seconds. Perfect for data journalism, financial reports, or simply adding a professional touch to your blog posts.
<h3>Key Benefits:</h3>
<ul>
<li>Zero Database Bloat: No per-chart database entries. Everything lives in your content.</li>
<li>Ultra Lightweight: Optimized for Core Web Vitals and speed.</li>
<li>GDPR Compliant: No external CDNs. Chart.js is served directly from your server.</li>
<li>Intuitive Builder: Create charts visually in your admin settings and get a shortcode instantly.</li>
<li>Native Gutenberg Block: Insert charts directly from the block inserter with a live server-side preview.</li>
</ul>
<h3>Features</h3>
<ul>
<li>8 Chart Types: Bar, Line, Pie, Doughnut, Radar, Polar area, Scatter, and Bubble charts.</li>
<li>Gutenberg Block: Native <code>chartlet/chart</code> block with real-time server-side preview in the editor.</li>
<li>Live Shortcode Builder: Configure labels, data points, colors, and dimensions with a real-time generator.</li>
<li>Fully Responsive: Charts automatically scale to fit any screen size (mobile, tablet, desktop).</li>
<li>Smart Defaults: Set global brand colors and heights in the settings to keep your charts consistent.</li>
<li>Custom Units: Add prefixes (e.g., $) or suffixes (e.g., %) to your data tooltips.</li>
<li>Translation Ready: Fully compatible with multilingual sites.</li>
</ul>
<h3>Usage</h3>
Gutenberg block: Open the block inserter and search for “Chartlet”. Insert the block, enter data, and the chart preview updates live in the editor.
Shortcode builder: Go to Chartlet → Generate. Use the visual builder to: 
1. Select your chart type. 
2. Input labels and data (separated by <code>,</code>). 
3. Customize colors, title, and height. 
4. Add a value suffix (e.g., %) or prefix (e.g., $). 
5. Click Generate Shortcode, copy it, and paste it anywhere!
Shortcode examples:
<pre><code>[chartlet type="bar" labels="Jan,Feb,Mar" data="10,20,15" colors="#3366cc,#dc3912" title="Revenue" height="300" prefix="$"]

[chartlet type="scatter" data="1:5, 2:10, 3:8"]

[chartlet type="bubble" data="1:5:3, 2:10:5, 3:8:10"]
</code></pre>

Chartlet

The lightest way to create beautiful, responsive charts in WordPress. No database clutter, no heavy libraries — just pure performance.

dsamourkasidis

Map Visualizer allows users to import csv files, and to create a map out of them using the plugin’s interface. 
After you have successfully imported (or created) a data source, you can visualise it on a map and add it to your posts/pages with a shortcode. 
All shortcodes can be constructed easily through the plugin’s interface.
<h4>CSV File Format</h4>
In order for the CSV file to be imported successfully, its format must comply with the following rules:
<ul>
<li>
The first row must contain all the Header names:
<ul>
<li>If you use geographical coordinates, the headers of the first two column must be named “Latitude” and “Longitude” respectively. </li>
<li>If you use addresses, the first column must be named “Address” and the plugin will geocode the data accordingly.</li>
<li>If you wish to use polygons, the first column must be named “Polygon”. Format of polygon data should be of Well-Known Text.</li>
</ul>
</li>
<li>
The second row must contain the data type of each column:
<ul>
<li>Available data types include “INT”, “FLOAT” and “TEXT”.</li>
<li>For “Latitude” and “Longitude” headers, the data type to be used is “FLOAT”.</li>
<li>For “Polygon” or “Address” headers, the data type to be used is “TEXT”.</li>
</ul>
</li>
</ul>
<h4>shortcode format</h4>
The general format of this plugin’s shortcodes is [visualise]. Available attributes include:
<ul>
<li>“file_name” : The name of the file imported you wish to visualise.</li>
<li>“map” : The map type to be used for the visualization. You can choose between “Satellite” or “Streets” maps and the default one is “Streets”.</li>
<li>“type” : Type of visualization. Either visualise your data as “polygon” or as “marker”. Default type is “marker”.</li>
<li>“marker_type” : Choose between “simple marker” or “circle_marker” to be pinned on the chosen map. The default markers are “simple marker”.</li>
<li>“category” : Header Name of your file, which will be used to differentiate the data based on the marker_type chosen.</li>
<li>“colorant” : Color of circle_markers and polygons, used to differentiate the data.</li>
<li>“circle_radius” : Radius of circle_markers. The default value is 5, and it is advised to stay between a 1-10 scale.</li>
<li>“fill_opacity” : Level of opacity for circle_markers and polygons. The default value is 0.3, and it is advised to stay between a 0.1-1 scale.</li>
<li>“center_point” : An Address for setting the initial center point of the map.</li>
<li>“zoom” : Initial zoom of the map. Value 1 shows the entire world map and the default zoom used is 3.</li>
</ul>

Map Visualizer

Import your data from csv files and visualise them on Google streets/satellite maps

Chartlet vs Map Visualizer