Clustered Column Chart

1) Clustered Column Chart is an analytical tool that displays data in clusters of columns, grouped by category. This chart is instrumental for comparing multiple series of data simultaneously, allowing viewers to observe differences and trends across categories within the same context.

2) The clustered format is particularly useful for presenting distinct but related data sets side by side, enhancing both the analysis and the presentation of comparative metrics. Such charts are ideal for revealing relationships between parts of a whole and for benchmarking competitive scenarios.

3) Version

4) Application Scenario：Multi-series column charts can be used to display the comparative effect of different series indicators.

5) Basic Requirement

The following table shows basic requirements for the multi-series column chart.

6) Chart Feature

Advantage: The multi-series column chart can clearly display the value of different indicators in each dimension, helping you compare the data volumes of different dimensions through different bars.

Disadvantage: The multi-series column chart is unsuitable for data with too many dimensions.

Example 1: Common Multi-Series Column Chart

Data Preparation

You can download the sample data Access Information Table.xlsx.

1. Click My Analysis, click a folder, and click New Subject.

2. Click Local Excel and click Upload Data, as shown in the following figure.

Component Creation

1. Click Add Component in the lower left corner. Click the Multi-Series Column Chart icon and drag Statistical Date to Horizontal Axis and Number of Exit, Number of View, and Number of Access to Vertical Axis, as shown in the following figure.

Note:

 The Multi-Series Column Chart icon can be clicked only when at least one dimension field and at least two indicator fields exist on the horizontal and vertical axes respectively, otherwise the icon in Chart Type is grayed out and cannot be clicked.

2. Perform filtering to display data before 2015-07-13, as shown in the following figure.

The following figure shows the effect after the adjustment.

Component Beautification

Color

Drag the field Indicator Name to Color, click Color, and set Scheme to Light Purple, as shown in the following figure.

For details, see Graphic Properties.

Size

Click Size to set the column width, rounded corner, and column spacing, as shown in the following figure.

Note:

You can also drag a field to Size. For details, see Graphic Properties.

You can set the column spacing to Small, Middle, or Large in FineBI 6.0 and later versions, as shown in the following figure.

Effect Display

The multi-series column chart is supported on both mobile terminals and PC.

For details, see section "Application Scenario."

Example 2: Multi-Series Column Chart (Stacking Enabled)

Data Preparation

1. Click My Analysis, click a folder, and click New Subject.

2. Click Local Excel and click Upload Data, as shown in the following figure.

You can download the sample data Sales Information Table.xlsx.

Component Creation

1. Click Add Component in the lower left corner.

2. Add a calculation field named Other Cost with the formula SUM_AGG(Total Cost) - SUM_AGG(Labor Cost), as shown in the following figure.

Note:

For details about the SUM_AGG formula, see SUM_AGG.

3. Click the Multi-Series Column Chart icon and drag Product Name to Horizontal Axis and Total Cost, Other Cost, and Labor Cost to Vertical Axis, as shown in the following figure.

4. Set Enable Stacking for the fields Other Cost and Labor Cost on the vertical axis, as shown in the following figure.

Component Beautification

Drag the field Indicator Name to Color, click Color, and set Scheme to Ocean, as shown in the following figure.

Effect Display

On PC

On Mobile Terminals

The following figure shows the preview effect on the DataAnalyst app and in HTML5.

In conclusion, the Clustered Column Chart is a highly effective visualization tool for comparing data across multiple categories. It facilitates the side-by-side comparison of different series within the same context, making it easier to identify trends and anomalies. This chart type is particularly valuable in settings where detailed comparative analysis is crucial for strategic decision-making.