Display data comparisons easily with a Column Chart, highlighting differences between categories with clear, vertical bars.

Compare data across categories with a Bar Chart, using horizontal bars for clear visual distinctions and comparisons.

Display hierarchical data with a Treemap Chart, using nested rectangles to compare proportions and visualize data distribution.

Summarize data distribution with a Boxplot Chart, highlighting medians, quartiles, and outliers for effective statistical analysis.

Display data progress and performance with a Radial Bar Chart, using circular bars to illustrate completion percentages visually.

Using different data sources—whether custom, CSV, databases, APIs, or Google Sheets—provides flexibility in chart creation.

Custom Data Types are especially useful when you want to preprocess or manipulate data before charting, or if you’re working with complex datasets.

Using CSV data to create charts is a common approach, especially when handling data from external sources.

Using Database Data Type to create a chart involves directly retrieving data from a database (such as MySQL, PostgreSQL, etc.)

Using Google Sheets as a data source for charts involves accessing data directly from a Google Sheets document via the Google Sheets API.

Setting up theme and background options is powerful for making charts visually distinct and enhancing data clarity.

Marker Options in Chart define the visual representation of data points on a chart. Key settings include: Size, Colors, Shape, Hover Effects etc.

Data Label Settings control the appearance and behaviour of labels that display data values directly on the chart. Key options include: Enabled, Formatter, Style, Position etc.

The X-Axis in chart is crucial for defining the horizontal orientation of your chart, typically representing categories or values.

The Toolbar Option provides interactive controls that enhance user experience when viewing charts. It allows you to add features like Download, Zooming, Reset etc.