📈 Communicate your results effectively with the best data visualizations

📈 Communicate your results effectively with the best data visualizations

Oct 25, 1900·
Dr. Mauricio Zambrano-Bigiarini
Dr. Mauricio Zambrano-Bigiarini
· 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

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HuggingFace Dataset

a.k.a. Awesome ChatGPT Prompts This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts. 📢 Notice This Hugging Face dataset is a mirror. For the …

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GitHub Repository

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⚡ The Open Research Copilot. Build high-perf Portfolios, Lab Sites & Docs in Markdown + Jupyter. 100% Data Control. 🦫 数据科学家的开源 Copilot。一键部署 👇

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Custom embed with manual data

My Custom Resource

example.com

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:

plotly.py

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plotly.py

The interactive graphing library for Python ✨

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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_id score
1 0
2 0.5
3 1
Table 1: My results

Interactive Buttons

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

Basic Buttons

 

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

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

Styled Buttons for Data Actions

 

 

{{< 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

 

{{< 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. Mauricio Zambrano-Bigiarini
Authors
Associate Professor

I am an Associate Professor in the Department of Civil Engineering at the University of La Frontera. I hold a PhD in Environmental Engineering from the University of Trento (Italy) and completed postdoctoral training at the European Commission’s Joint Research Centre. I have more than 20 years of experience in water resources research and have previously served as an Associate Researcher at the Center for Climate and Resilience Research (CR)2 and as a member of the Earth Sciences Assessment Group of the Chilean National Research and Development Agency (ANID).

My research lies at the interface of hydrology, data science, and environmental sciences, with a particular focus on the use of gridded datasets and open-source tools to investigate droughts, extreme events, and water-related impacts of global change.

I work across spatial and temporal scales to improve the understanding of catchment-scale hydrological processes and to translate this knowledge into operational modelling, forecasting, and early-warning systems that support robust environmental decision-making.

Please reach out to collaborate 😃