๐Ÿ“ˆ Communicate your results effectively with the best data visualizations
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๐Ÿ“ˆ Communicate your results effectively with the best data visualizations

Oct 25, 2023ยท
Dr. Shuai Zhang
Dr. Shuai Zhang
ยท 4 min read
Image credit: Unsplash
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Hugo Blox is designed to give technical content creators a seamless experience. You can focus on the content and Hugo Blox handles the rest.

Use popular tools such as Plotly, Mermaid, and data frames.

Embed Rich Content

HuggingFace Model

{{/* < embed platform=“huggingface” resource=“google/embeddinggemma-300m” type=“model” > */}}

HuggingFace Dataset

{{/* < embed platform=“huggingface” resource=“fka/awesome-chatgpt-prompts” type=“dataset” > */}}

GitHub Repository

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Custom embed with manual data

A great resource for learning

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Custom Images

Embed beautiful images from any source with Hugo image processing (Unsplash, custom URLs, etc.):

Beautiful data visualization workspace

Beautiful data visualization workspace

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You can also add images to any platform embed:

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Charts

Hugo Blox supports the popular Plotly format for interactive data visualizations. With Plotly, you can design almost any kind of visualization you can imagine!

Save your Plotly JSON in your page folder, for example line-chart.json, and then add the {{< chart data="line-chart" >}} shortcode where you would like the chart to appear.

Demo:

You might also find the Plotly JSON Editor useful.

Diagrams

Hugo Blox supports the Mermaid Markdown extension for diagrams.

An example flowchart:

```mermaid
graph TD
A[Hard] -->|Text| B(Round)
B --> C{Decision}
C -->|One| D[Result 1]
C -->|Two| E[Result 2]
```

renders as

graph TD A[Hard] -->|Text| B(Round) B --> C{Decision} C -->|One| D[Result 1] C -->|Two| E[Result 2]

An example sequence diagram:

```mermaid
sequenceDiagram
Alice->>John: Hello John, how are you?
loop Healthcheck
    John->>John: Fight against hypochondria
end
Note right of John: Rational thoughts!
John-->>Alice: Great!
John->>Bob: How about you?
Bob-->>John: Jolly good!
```

renders as

sequenceDiagram Alice->>John: Hello John, how are you? loop Healthcheck John->>John: Fight against hypochondria end Note right of John: Rational thoughts! John-->>Alice: Great! John->>Bob: How about you? Bob-->>John: Jolly good!

An example class diagram:

```mermaid
classDiagram
Class01 <|-- AveryLongClass : Cool
Class03 *-- Class04
Class05 o-- Class06
Class07 .. Class08
Class09 --> C2 : Where am i?
Class09 --* C3
Class09 --|> Class07
Class07 : equals()
Class07 : Object[] elementData
Class01 : size()
Class01 : int chimp
Class01 : int gorilla
Class08 <--> C2: Cool label
```

renders as

classDiagram Class01 <|-- AveryLongClass : Cool Class03 *-- Class04 Class05 o-- Class06 Class07 .. Class08 Class09 --> C2 : Where am i? Class09 --* C3 Class09 --|> Class07 Class07 : equals() Class07 : Object[] elementData Class01 : size() Class01 : int chimp Class01 : int gorilla Class08 <--> C2: Cool label

An example state diagram:

```mermaid
stateDiagram
[*] --> Still
Still --> [*]
Still --> Moving
Moving --> Still
Moving --> Crash
Crash --> [*]
```

renders as

stateDiagram [*] --> Still Still --> [*] Still --> Moving Moving --> Still Moving --> Crash Crash --> [*]

Data Frames

Save your spreadsheet as a CSV file in your page’s folder and then render it by adding the Table shortcode to your page:

{{< table path="results.csv" header="true" caption="Table 1: My results" >}}

renders as

customer_idscore
10
20.5
31
Table 1: My results

Interactive Buttons

Add engaging call-to-action buttons to your data visualization posts:

Basic Buttons

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{{< button url="/" >}}Contact Us{{< /button >}}

{{< button url="https://plotly.com/python/" new_tab="true" style="secondary" >}}Learn Plotly{{< /button >}}

Styled Buttons for Data Actions

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{{< button url="#" style="primary" size="lg" align="center" icon="chart-bar" >}}View Dashboard{{< /button >}}

{{< button url="/data/results.csv" style="outline" icon="document-arrow-down" >}}Download Data{{< /button >}}

{{< button url="https://github.com/HugoBlox" new_tab="true" style="ghost" icon="arrow-top-right-on-square" icon_position="right" >}}View Source Code{{< /button >}}

Multiple Aligned Buttons

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{{< button url="https://jupyter.org/" new_tab="true" style="secondary" rounded="full" align="center" >}}Try Jupyter{{< /button >}}

{{< button url="https://colab.research.google.com/" new_tab="true" style="primary" rounded="full" align="center" icon="rocket-launch" >}}Open in Colab{{< /button >}}

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Dr. Shuai Zhang
Authors
PhD Student

I am currently a Ph.D. candidate at the Ai4City-Lab, Urban Governance and Design Thrust, Society Hub, The Hong Kong University of Science and Technology (Guangzhou), under the supervision of Prof. Wufan Zhao and Prof. Yuan Liu. Prior to this, I obtained my Master’s degree from the School of Geospatial Engineering and Science, Sun Yat-sen University, where I was advised by Prof. Wuming Zhang and Prof. Yiping Chen.

My research focuses on 3D visual perception, intelligent interpretation and processing of point cloud data, and multi-modal urban foundation models. I am particularly interested in bridging geometric understanding with semantic reasoning in large-scale urban environments, with an emphasis on open-vocabulary learning, training-free paradigms, and cross-modal fusion between 2D and 3D data.

My goal is to develop scalable, interpretable, and generalizable AI systems for urban analysis, enabling applications such as digital twin construction, urban scene understanding, and intelligent infrastructure management.