Plotly.NET: A fully featured charting library for .NET programming languages

Kevin Schneider; Benedikt Venn; Timo Mühlhaus

doi:10.12688/f1000research.123971.1

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Software Tool Article

Plotly.NET: A fully featured charting library for .NET programming languages

[version 1; peer review: 1 approved, 1 approved with reservations]

Kevin Schneider¹, Benedikt Venn¹, Timo Mühlhaus ¹

PUBLISHED 23 Sep 2022

Author details Author details

¹ Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

Kevin Schneider
Roles: Conceptualization, Methodology, Software, Validation, Visualization, Writing – Original Draft Preparation

Benedikt Venn
Roles: Resources, Software, Visualization, Writing – Original Draft Preparation

Timo Mühlhaus
Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Software, Supervision, Writing – Original Draft Preparation

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Software and Hardware Engineering gateway.

Abstract

Data visualization is integral for exploratory data analysis and data presentation. Consequently, every programming environment suitable for data analysis needs a feature-rich visualization library. In this paper, we present Plotly.NET - a fully featured charting library for the .NET ecosystem. Plotly.NET requires little ceremony to use, provides multiple API (application programming interface) layers for both low-code and maximum customizability, and can be used in many different visualization workflows - from interactive scripting and notebooks to user interface applications. Plotly.NET brings the charting capabilities of plotly.js to the .NET ecosystem, successfully combining the flexibility of the plotly grammar with the type-safety and expressiveness of .NET.

Keywords

.NET, F#, C#, data visualization

Corresponding author: Timo Mühlhaus

Competing interests: No competing interests were disclosed.

Grant information: This work was supported by the Deutsche Forschungsgemeinschaft (SFB/TRR175, project INF) and the National Research Data Infrastructure Germany (NFDI) DataPLANT, awarded to Timo Mühlhaus.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Schneider K et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Schneider K, Venn B and Mühlhaus T. Plotly.NET: A fully featured charting library for .NET programming languages [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2022, 11:1094 (https://doi.org/10.12688/f1000research.123971.1) First published: 23 Sep 2022, 11:1094 (https://doi.org/10.12688/f1000research.123971.1) Latest published: 19 Feb 2024, 11:1094 (https://doi.org/10.12688/f1000research.123971.2)

Introduction

Proper visualization of scientific results or data in general is an essential element for teaching, the discussion of analysis results, or the distribution of new insights within the research community. Well structured figures help to improve visibility, explorability, and interpretability of the underlying data, consequently saving tedious searching in order to be able to interpret the presented data. Algorithmic diversity is paramount in exploratory data analysis, but ultimately the goal will always be to produce meaningful figures that represent the obtained information in an optimal way. Even during exploration, figures help to guide the researcher to hidden properties that become apparent when inspected in the form of a figure, especially when the figure is interactive. Therefore, the ability for convenient and streamlined plotting strategies/possibilities is not only important for distributing results, but also helps to get new insights during data analysis, and is an invaluable tool in the data science stacks of any programming language.

plotly.js¹ is a popular open source graphing JavaScript library. It provides a well defined grammar for creating visualizations via the figure data structure - a tree with named nodes called attributes. The figure data structure can be represented via JavaScript Object Notation (JSON) - a widespread standard for representation of structured data which can be parsed and created by any modern programming language (see Figure 1 for an example). Due to this interoperability, libraries for creating plotly.js figures are available in many programming languages, most notably in Python² and R³ which see widespread adoption in the scientific programming landscape.

Figure 1. A simple plotly.js line graph.

Left: The JSON (JavaScript Object Notation) formatted figure object. Lines 2-9 are the data array, which contains trace objects representing individual data visualizations of the figure. Lines 10-13 are the layout object, which contains data-independent styling options such as the axis objects. Right: The respective rendered graph.

In this paper we present Plotly.NET - a library for creating plotly.js-conform JSON formatted figures for the set of statically typed .NET languages (F#,⁴^,⁵ C#,⁶ VB.NET⁷). Plotly.NET is written in F# and leverages the static type system by providing type-safe domain specific languages (DSLs) for plotly.js attributes and objects, as well as several abstraction layers for ease-of-use. Plotly.NET is feature complete regarding plotly.js API (application programming interface) coverage and is compatible with the .NET kernel for Jupyter, therefore offering a complete suite of data visualization tools for exploratory data analysis unprecedented in the .NET environment.

Methods

Implementation

Plotly.NET is implemented in the open source F# programming language. It creates objects which are serialized into JSON (using the Newtonsoft.Json package⁸) which can be used by a rendering engine to create the visual equivalent. This is either realized by embedding the generated JSON in a HTML scaffold where plotly.js is used for rendering the plot in a browser (or equivalent environment where JavaScript can be executed), or via an interface for custom rendering engines.

The API is designed to enable different styles of creating charts and contains several abstraction layers. All (as of v2.6.3) plotly.js trace types have type safe equivalents with additional convenience layers to create derivative charts from these base traces.

Core API layers

Plotly.NET provides multiple API layers with increasing abstraction levels: (1) DynamicObject, (2) plotly.js object mappings, and (3) the high-level Chart API.

(1) DynamicObject: The low-level API builds on top of the DynamicObj package⁹ which provides a way of setting dynamic members in the statically typed .NET environment. Instances of this class, as well as instances of classes inheriting from it, provide the ?-operator which enables member assignment on runtime. This is usually prevented by the static type system of .NET languages, but necessary to support the highly dynamically typed nature of the JSON objects expected by plotly.js. Static classes are not flexible enough for this, especially because almost all attributes are optional and can be of multiple types.

This API layer is closest to plotly.js and can be used to directly translate javascript examples, as attribute names must be mirrored exactly. This also means that extensive knowledge of plotly.js, or at least it’s JSON schema is necessary to effectively use it, but makes it easy to implement new features should the underlying plotly.js version be updated. Figure 2 shows an example on how to use this API layer to generate the same plot shown in Figure 1.

Figure 2. A simple plotly.js line graph created with Plotly.NET’s low-level DynamicObject API (application programming interface) layer.

Left: F# code creating the figure data structure. Lines 1-3 are referencing the library, lines 5-8 create the trace object (see equivalent lines 2-9 in Figure 1). Lines 10-23 create the layout object containing the axis objects (see equivalent lines 10-13 in Figure 1). Lines 25-27 create the figure object and render it in a browser. Right: The respective rendered graph.

(2) plotly.js object mappings: plotly.js attributes that are themselves objects are abstracted as classes built on top of (1) and provide static init and style methods, as well as object-specific methods. These methods have a plethora of optional typed arguments which are equivalent to all attributes supported in the respective plotly.js JSON. Additionally, type-safe DSLs for attributes/values used on multiple occasions such as style parameters, color, or enums are provided in the StyleParam namespace. This layer comes with the additional advantage of providing options for auto-completing argument names as well as documentation for them, leading to less plotly.js knowledge being required for its usage. Figure 3 shows an example on how to use this API layer to generate the same plot shown in Figure 1.

Figure 3. A simple plotly.js line graph created with Plotly.NET’s object abstraction API (application programming interface) layer.

Left: F# code creating the figure data structure. Lines 1-3 are referencing the library. Lines 5-9 create the trace object (see equivalent lines 2-9 in Figure 1). Lines 11-18 create the layout object containing the axis objects (see equivalent lines 10-13 in Figure 1). Lines 20-23 create the figure object with default styling (Line 21) and render it in a browser. Right: The respective rendered graph.

Note that this API layer provides type-safe abstractions, but still needs insights about how plotly.js structures figures: While allowed attribute names and types are abstracted, the user still needs to know that for example axis styles are to be set on a Layout object (see Figure 3 left, lines 11-18). It is also possible to use style presets (see Figure 3 left, line 21) with this API layer.

(3) The high-level Chart API provides type safe abstractions for chart creation and styling without knowledge of the structure of plotly.js JSON. Type-safe methods for creating figure structures for all trace types and derived charts as well as various styling methods are provided.

The plotly.js figure schema is completely abstracted away. The API surface is only concerned with’creating and styling a chart’. Consider the following example: In plotly.js JSON, the axis style has to be set on the layout object. It also must be specified which type of axis (x, y, z, etc.) it is. Styling the x axis usually requires knowledge of this. The Chart API however provides a Chart.withXAxisStyle function, which also provides arguments for the relevant attributes, and can be applied to any Chart object.

Using this API layer also significantly decreases the lines of code necessary to create figures, as proper creation of nested objects and argument naming is implicitly done by the Chart methods. See Figure 4 for an example on how to use this API layer to generate the same plot shown in Figure 1. Note that there is a single flow of the initial Chart object, without the need of creating additional objects for axis styling.

Figure 4. A simple plotly.js line graph created with Plotly.NET’s top-level Chart API (application programming interface) layer.

Left: F# code creating the figure data structure. Lines 1 and 2 are referencing the library. In this API layer, there are no clear equivalents to Figure 1: in Lines 4-7, the Chart. Line method creates a figure structure with default styling and the input data. Subsequently, the x and y axes are styled using respective styling methods without the need of creating title objects in contrast to the other API layers. Right: The respective rendered graph.

Plotly.NET however does not enforce the usage of any API layer. The low-level, abstraction-less layer (1) is exposed on purpose as this gradual abstraction via API layers enables users with any kind of knowledge about plotly.js to use it. Additionally, this allows for both imperative and declarative creation of figures. The dynamic assignment of members however might seem not intuitive to .NET users unexposed to dynamically typed languages. The high-level Chart API (3) on the other hand provides type-safe abstractions with the trade-off of reduced customizability. Extending this layer needs a lot of domain knowledge in both plotly.js and the Plotly.NET equivalent DSL. We believe that users are offered the best of both worlds by providing low-code abstractions for common use-cases, while retaining the ability to take full control where needed.

Extensions

In addition to the core API, three extension packages - Plotly.NET.ImageExport, Plotly.NET.Interactive, and Plotly.NET.CSharp - are provided. Plotly.NET.ImageExport and Plotly.NET.Interactive cover two specific use cases - static image export and usage with the .NET Jupyter Kernel .NET Interactive - while the aim of Plotly.NET.CSharp is providing a native, idiomatic API surface for consuming the core API for the object-oriented C# language (note that the core API can be consumed in any.NET programming language, this package just provides a more idiomatic API).

Plotly.NET.ImageExport provides an interface for rendering engines that can produce PNG, JPG, or SVG files from plotly.js JSON figures. A reference implementation is provided that uses PuppeteerSharp¹⁰ to create a headless Chromium browser to render the figure and save it to the disk in the desired format.

Plotly.NET.Interactive is a formatting extension for .NET interactive, the Jupyter kernel for .NET languages. It enables automatic rendering of figures created with Plotly.NET in the notebook output cells without the need to leave the analysis environment by switching to the browser. Having the charts tied to the code producing them is especially helpful in the context of sharing and comprehension of visualizations. Examples of such notebooks are included in the Plotly.NET repository (see the Data availability section).

Operation

Plotly.NET targets the netstandard2.0 framework and is therefore supported on a plethora of compatible target frameworks across the .NET ecosystem. At the time of writing this article, this means that Plotly.NET can be used on any modern desktop operating system, as well as multiple mobile operating systems. It can be either referenced as nuget package or be built from source.

Using Plotly.NET nuget packages

Plotly.NET is available as pre-compiled binary package on nuget.org (see here), which is the central package registry in the .NET ecosystem. It can be incorporated into any .NET project, script or notebook via the respective package reference. A target framework compatibility matrix is available on the nuget package page.

Building Plotly.NET from source

The source code as well as detailed instructions on how to build it are available on GitHub (see Software availability¹³). An installation of the .NET SDK of version ≥ 6.0.1 (freely available to readers and reviewers here) is mandatory.

Use cases

Plotly.NET aims to be a general-purpose visualization library for the .NET ecosystem. It targets interactive workflows such as visualization in scripting or in notebook environments, as well as visualizations in any kind of application, be it for desktop, mobile, or the web. Therefore, we demonstrate some of the visualization capabilities in the following section instead of specifying use cases.

Figure 5 shows a few more complex charts that can be generated with Plotly.NET:

• Figure 5A shows various variations of box and violin plots for the purpose of visualizing shapes and properties of distributions.
• Figure 5B is a combination of a temperature time course as line chart and a superimposed heatmap indicating correlation coefficients derived by continuous wavelet transform using FSharp.Stats (see Ref. 11 and Underlying data). High values (reddish) indicate high correlation to the frequency given as row indicators on the right. High negative values (bluish) indicate high anti-correlation.
• Figure 5C shows a scatter plot matrix of the classic iris data set (see Ref. 12 and Underlying data) providing an overview of how the respective features in it correlate with each other.
• Figure 5D shows a surface chart of the three dimensional wave function $f (x, y) = sin (\sqrt{x^{2} + y^{2}})$ .

Figure 5. Example charts.

(A) Box and violin plots to describe properties and shapes of distributions. (B) Combined chart of temperature measurements and their frequency representation as heatmap. (C) Splom chart of the iris data set. (D) Surface chart of a three dimensional wave function.

The respective code is provided as interactive notebooks in the repository on GitHub (see Software availability¹³).

Data availability

Underlying data

The data underlying Figure 5 are contained in the’publication’ folder in the Plotly.NET GitHub and Zenodo repositories (see Software availability below) as follows:

• iris-data.csv (contains species label, sepal length/width, and petal length/width of observed iris flowers. This data was originally obtained from Ref. 12).
• waveletData.txt (contains water temperature measurements conducted by the authors. Additional correlation coefficients were derived by continuous wavelet transform using Marr wavelets with frequencies specified in the row annotations. This data was made available previously in Ref. 11).

Software availability

• Software available from: https://nuget.org/packages/Plotly.NET
• Source code and notebooks generating the example figures are available from: https://github.com/plotly/Plotly.NET
• Archived source code at time of publication: https://doi.org/10.5281/zenodo.6822582¹³
• License: MIT

Acknowledgements

The authors would like to thank all independent open source contributors on the GitHub repository, no matter how small the contributions. Special thanks to @WhiteBlackGoose for the extensive conceptual discussions about all things .NET.

References

1. Plotly Technologies Inc: Collaborative data science.2015.Reference Source
2. Plotly Technologies Inc: plotly.py - the interactive graphing library for python (includes plotly express).2022.Reference Source
3. Sievert C: Interactive Web-Based Data Visualization with R, plotly, and shiny.Chapman and Hall/CRC;2020. ISBN 9781138331457.Reference Source
4. Syme D:Leveraging .net meta-programming components from f#: Integrated queries and interoperable heterogeneous execution. Proceedings of the 2006 Workshop on ML, ML’06. New York, NY, USA:Association for Computing Machinery;2006; page 43–54. ISBN 1595934839.Leveraging.net Publisher Full Text
5. Syme D, Battocchi K, Takeda K, et al.:Themes in information-rich functional programming for internet-scale data sources. Proceedings of the 2013 Workshop on Data Driven Functional Programming, DDFP’13. New York, NY, USA: Association for Computing Machinery;2013; page 1–4. ISBN 9781450318716. Publisher Full Text
6. Hejlsberg A, Torgersen M, Wiltamuth S, et al.: The C# programming language.Pearson Education;2008.
7. Grundgeiger D: Programming Visual Basic. NET.O’Reilly;2018.
8. Newton-King J: Jamesnk/newtonsoft.json.2022.Reference Source
9. Schneider K: @WhiteBlackGoose, and Timo Mühlhaus. Csbiology/dynamicobj.2022.Reference Source
10. Kondratiuk D: hardkoded/puppeteer-sharp.2022.Reference Source
11. Venn B, Weil L, Schneider K, et al.: fslaborg/fsharp.stats.May 2022. PubMed Abstract
12. Fisher RA: The use of multiple measurements in taxonomic problems. Ann. Eugenics. 1936; 7(2): 179–188. Publisher Full Text
13. Schneider K, Mühlhaus T, Goose WB, et al.: plotly/Plotly.NET: 3.0.0-manuscript (3.0.0-manuscript). Zenodo. [Software].2022. Publisher Full Text

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Version 2

VERSION 2 PUBLISHED 23 Sep 2022

Author details Author details

¹ Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

Kevin Schneider
Roles: Conceptualization, Methodology, Software, Validation, Visualization, Writing – Original Draft Preparation

Benedikt Venn
Roles: Resources, Software, Visualization, Writing – Original Draft Preparation

Timo Mühlhaus
Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Software, Supervision, Writing – Original Draft Preparation

Competing interests

No competing interests were disclosed.

Grant information

This work was supported by the Deutsche Forschungsgemeinschaft (SFB/TRR175, project INF) and the National Research Data Infrastructure Germany (NFDI) DataPLANT, awarded to Timo Mühlhaus.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (2)

version 2

Revised

Published: 19 Feb 2024, 11:1094

https://doi.org/10.12688/f1000research.123971.2

version 1

Published: 23 Sep 2022, 11:1094

https://doi.org/10.12688/f1000research.123971.1

© 2022 Schneider K et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Schneider K, Venn B and Mühlhaus T. Plotly.NET: A fully featured charting library for .NET programming languages [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2022, 11:1094 (https://doi.org/10.12688/f1000research.123971.1)

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PUBLISHED 23 Sep 2022

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Reviewer Report 16 Nov 2023

Andrea Vázquez-Ingelmo, University of Salamanca, Salamanca, Spain

Approved with Reservations

https://doi.org/10.5256/f1000research.136133.r183698

This paper presents a fully featured charting library for the .NET ecosystem, namely Plotly.NET, which brings the charting capabilities of plotly.js to the .NET ecosystem.

The paper is well-written and well-structured. However, I think that the paper would ... Continue reading

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Partly
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

No
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Data visualization

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

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Author Response 19 Feb 2024

Timo Mühlhaus, Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

19 Feb 2024

Author Response

Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications ... Continue reading Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications (desktop, mobile, or web). The manuscript aims to highlight a subset of its visualization capabilities, prompting readers to refer to the documentation for comprehensive tutorials and samples.
In response to your suggestion, we have included the link to our extensive documentation and code samples at https://plotly.net. We appreciate your input. Thank you very much.
Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications (desktop, mobile, or web). The manuscript aims to highlight a subset of its visualization capabilities, prompting readers to refer to the documentation for comprehensive tutorials and samples.
In response to your suggestion, we have included the link to our extensive documentation and code samples at https://plotly.net. We appreciate your input. Thank you very much.
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 19 Feb 2024

Timo Mühlhaus, Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

19 Feb 2024

Author Response

Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications ... Continue reading Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications (desktop, mobile, or web). The manuscript aims to highlight a subset of its visualization capabilities, prompting readers to refer to the documentation for comprehensive tutorials and samples.
In response to your suggestion, we have included the link to our extensive documentation and code samples at https://plotly.net. We appreciate your input. Thank you very much.
Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications (desktop, mobile, or web). The manuscript aims to highlight a subset of its visualization capabilities, prompting readers to refer to the documentation for comprehensive tutorials and samples.
In response to your suggestion, we have included the link to our extensive documentation and code samples at https://plotly.net. We appreciate your input. Thank you very much.
Competing Interests: No competing interests were disclosed. Close
Report a concern

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Reviewer Report 02 Jun 2023

Mathieu Jacomy, Department of Culture and Learning, Aalborg Universitet, Aalborg, North Denmark Region, Denmark

Approved

https://doi.org/10.5256/f1000research.136133.r171764

The article is a high-level description of Plotly.NET, a tool that brings the charting library "plotly.js" into the .NET ecosystem. The article provides elements of justification for the design of the tool, in particular its central choice to offer three distinct API layers, each with their own writing style, and addressed to different publics.

The article offers an overview of the tool to researchers who use it or consider to. It documents where the tool comes from, what is its intended purpose, and how it has been architectured. The article is compact and not too detailed, as it should be; it does not try to replace the documentation. The user interested in a more in-depth description of the capabilities of Plotly.NET can browse the online reference instead.

I see this article as a proxy paper for Plotly.NET, and I see no issue with that. It provides sufficient context to the tool to motivate a short Software Tool paper. This will help the developers of the tool get recognition in the academic sphere, which I wholeheartedly support, as their work is worth it.

PS: I noted a small typo in the v1: "or at least it’s JSON schema" should be "or at least its JSON schema".

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Yes
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Yes
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Network visualization, network analysis, science and technology studies, controversy mapping, information design

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Author Response 19 Feb 2024

Timo Mühlhaus, Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

19 Feb 2024

Author Response

Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
... Continue reading Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
Once again, thank you very much.
Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
Once again, thank you very much.
Competing Interests: No competing interests were disclosed. Close
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Author Response 19 Feb 2024

Timo Mühlhaus, Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

19 Feb 2024

Author Response

Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
... Continue reading Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
Once again, thank you very much.
Thank you very much for taking the time to review our manuscript. We sincerely appreciate your valuable comments. Following the correction of a typo, we have uploaded a new version.
Once again, thank you very much.
Competing Interests: No competing interests were disclosed. Close
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Version 2

VERSION 2 PUBLISHED 23 Sep 2022

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Version 1 23 Sep 22	read	read

Mathieu Jacomy, Aalborg Universitet, Aalborg, Denmark
Andrea Vázquez-Ingelmo, University of Salamanca, Salamanca, Spain

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16 Nov 2023 | for Version 1

Andrea Vázquez-Ingelmo, University of Salamanca, Salamanca, Spain

19 Views Cite this report Responses(1)

Approved With Reservations

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Partly
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

No
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Data visualization

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Author Response

19 Feb 2024

Timo Mühlhaus, Computational Systems Biology, TU Kaiserslautern, 67663 Kaiserslautern, Germany

Thank you for reviewing our manuscript and providing valuable feedback. Plotly.NET is a versatile visualization library for the .NET ecosystem, catering to interactive workflows in scripting, notebooks, and various applications (desktop, mobile, or web). The manuscript aims to highlight a subset of its visualization capabilities, prompting readers to refer to the documentation for comprehensive tutorials and samples.
In response to your suggestion, we have included the link to our extensive documentation and code samples at https://plotly.net. We appreciate your input. Thank you very much.

View more View less

Competing Interests

No competing interests were disclosed.

Back to all reports

Reviewer Report

12 Views

02 Jun 2023 | for Version 1

Mathieu Jacomy, Department of Culture and Learning, Aalborg Universitet, Aalborg, North Denmark Region, Denmark

12 Views Cite this report Responses(1)

Approved

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Yes
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Yes
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Network visualization, network analysis, science and technology studies, controversy mapping, information design

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. Plotly Technologies Inc: Collaborative data science.2015.Reference Source

[2] 2. Plotly Technologies Inc: plotly.py - the interactive graphing library for python (includes plotly express).2022.Reference Source

[3] 3. Sievert C: Interactive Web-Based Data Visualization with R, plotly, and shiny.Chapman and Hall/CRC;2020. ISBN 9781138331457.Reference Source

[4] 4. Syme D:Leveraging .net meta-programming components from f#: Integrated queries and interoperable heterogeneous execution. Proceedings of the 2006 Workshop on ML, ML’06. New York, NY, USA:Association for Computing Machinery;2006; page 43–54. ISBN 1595934839.Leveraging.net Publisher Full Text

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Plotly.NET: A fully featured charting library for .NET programming languages

Abstract

Keywords

Introduction

Figure 1. A simple plotly.js line graph.

Methods

Implementation

Core API layers

Figure 2. A simple plotly.js line graph created with Plotly.NET’s low-level DynamicObject API (application programming interface) layer.

Figure 3. A simple plotly.js line graph created with Plotly.NET’s object abstraction API (application programming interface) layer.

Figure 4. A simple plotly.js line graph created with Plotly.NET’s top-level Chart API (application programming interface) layer.

Extensions

Operation

Using Plotly.NET nuget packages

Building Plotly.NET from source

Use cases

Figure 5. Example charts.

Data availability

Underlying data

Software availability

Acknowledgements

References

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