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CODE_OF_CONDUCT.md

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# Contributor Covenant Code of Conduct
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## Our Pledge
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In the interest of fostering an open and welcoming environment, we as
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contributors and maintainers pledge to making participation in our project and
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our community a harassment-free experience for everyone, regardless of age, body
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size, disability, ethnicity, sex characteristics, gender identity and expression,
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level of experience, education, socio-economic status, nationality, personal
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appearance, race, religion, or sexual identity and orientation.
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## Our Standards
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Examples of behavior that contributes to creating a positive environment
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include:
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* Using welcoming and inclusive language
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* Being respectful of differing viewpoints and experiences
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* Gracefully accepting constructive criticism
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* Focusing on what is best for the community
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* Showing empathy towards other community members
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Examples of unacceptable behavior by participants include:
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* The use of sexualized language or imagery and unwelcome sexual attention or
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advances
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* Trolling, insulting/derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or electronic
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address, without explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Our Responsibilities
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Project maintainers are responsible for clarifying the standards of acceptable
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behavior and are expected to take appropriate and fair corrective action in
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response to any instances of unacceptable behavior.
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Project maintainers have the right and responsibility to remove, edit, or
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reject comments, commits, code, wiki edits, issues, and other contributions
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that are not aligned to this Code of Conduct, or to ban temporarily or
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permanently any contributor for other behaviors that they deem inappropriate,
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threatening, offensive, or harmful.
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## Scope
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This Code of Conduct applies both within project spaces and in public spaces
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when an individual is representing the project or its community. Examples of
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representing a project or community include using an official project e-mail
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address, posting via an official social media account, or acting as an appointed
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representative at an online or offline event. Representation of a project may be
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further defined and clarified by project maintainers.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported by contacting the project team at joseshowh@gmail.com. All
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complaints will be reviewed and investigated and will result in a response that
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is deemed necessary and appropriate to the circumstances. The project team is
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obligated to maintain confidentiality with regard to the reporter of an incident.
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Further details of specific enforcement policies may be posted separately.
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Project maintainers who do not follow or enforce the Code of Conduct in good
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faith may face temporary or permanent repercussions as determined by other
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members of the project's leadership.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
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available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
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[homepage]: https://www.contributor-covenant.org
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For answers to common questions about this code of conduct, see
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https://www.contributor-covenant.org/faq

CONTRIBUTING.md

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# Contributing to DABEST-Python
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## Did you find a bug?
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- Ensure the bug was not already reported by searching in [Issues](https://github.com/ACCLAB/DABEST-python/issues). Check that the bug hasn't been addressed in a closed issue.
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- If the bug isn't being addressed, open a new one. Be sure to include a title and clear description, and a [minimally reproducible code sample](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) demonstrating the expected behavior that is not occurring.
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## Did you write a patch that fixes a bug?
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- Open a new GitHub [pull request](https://help.github.com/en/articles/about-pull-requests) (PR for short) with the patch.
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- Create the PR into the development branch, which is indicated by `v{latest version number}-dev`.
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- Clearly state the problem and solution in the PR description. Include the relevant [issue number](https://guides.github.com/features/issues/) if applicable.
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## Do you intend to add a new feature or change an existing one?
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- Suggest your change by opening an issue, and adding an Enhancement tag.
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- If the maintainers and the community are in favour, create a fork and start writing code.
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DABEST is a community tool for estimation statistics and analysis. We look forward to more robust and more elegant data visualizations from you all!

README.md

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@@ -53,21 +53,21 @@ DABEST is a package for **D**ata **A**nalysis using
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**B**ootstrap-Coupled **EST**imation.
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[Estimation
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statistics](https://en.wikipedia.org/wiki/Estimation_statistics) is a
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statistics](https://en.wikipedia.org/wiki/Estimation_statistics) are a
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[simple framework](https://thenewstatistics.com/itns/) that avoids the
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[pitfalls](https://www.nature.com/articles/nmeth.3288) of significance
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testing. It uses familiar statistical concepts: means, mean differences,
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and error bars. More importantly, it focuses on the effect size of one’s
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experiment/intervention, as opposed to a false dichotomy engendered by
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*P* values.
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testing. It employs familiar statistical concepts such as means, mean
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differences, and error bars. More importantly, it focuses on the effect
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size of one’s experiment or intervention, rather than succumbing to a
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false dichotomy engendered by *P* values.
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An estimation plot has two key features.
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An estimation plot comprises two key features.
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1. It presents all datapoints as a swarmplot, which orders each point
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to display the underlying distribution.
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1. It presents all data points as a swarm plot, ordering each point to
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display the underlying distribution.
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2. It presents the effect size as a **bootstrap 95% confidence
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interval** on a **separate but aligned axes**.
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2. It illustrates the effect size as a **bootstrap 95% confidence
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interval** on a **separate but aligned axis**.
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![The five kinds of estimation
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plots](showpiece.png "The five kinds of estimation plots.")
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## Installation
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This package is tested on Python 3.6, 3.7, and 3.8. It is highly
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This package is tested on Python 3.6, 3.7, 3.8 and 3.10. It is highly
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recommended to download the [Anaconda
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distribution](https://www.continuum.io/downloads) of Python in order to
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obtain the dependencies easily.
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You can install this package via `pip`.
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To install, at the command line run <!-- ```shell
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To install, at the command line run
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``` shell
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conda config --add channels conda-forge
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conda install dabest
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```
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or -->
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or –\>
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``` shell
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pip install --upgrade dabest
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pip install dabest
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```
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You can also
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import pandas as pd
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import dabest
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# Load the iris dataset. Requires internet access.
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# Load the iris dataset. This step requires internet access.
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iris = pd.read_csv("https://github.com/mwaskom/seaborn-data/raw/master/iris.csv")
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# Load the above data into `dabest`.
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## Contributing
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All contributions are welcome; please read the [Guidelines for
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contributing](https://github.com/ACCLAB/DABEST-python/blob/master/CONTRIBUTING.md)
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first.
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contributing](CONTRIBUTING.md) first.
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We also have a [Code of
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Conduct](https://github.com/ACCLAB/DABEST-python/blob/master/CODE_OF_CONDUCT.md)
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to foster an inclusive and productive space.
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We also have a [Code of Conduct](CODE_OF_CONDUCT.md) to foster an
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inclusive and productive space.
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### A wish list for new features
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Currently, DABEST offers functions to handle data traditionally analyzed
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with Student’s paired and unpaired t-tests. It also offers plots for
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multiplexed versions of these, and the estimation counterpart to a 1-way
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analysis of variance (ANOVA), the shared-control design. While these
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five functions execute a large fraction of common biomedical data
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analyses, there remain three others: 2-way data, time-series group data,
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and proportional data. We aim to add these new functions to both the R
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and Python libraries.
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- In many experiments, four groups are investigate to isolate an
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interaction, for example: a genotype × drug effect. Here, wild-type
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and mutant animals are each subjected to drug or sham treatments; the
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data are traditionally analysed with a 2×2 ANOVA. We have received
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requests by email, Twitter, and GitHub to implement an estimation
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counterpart to the 2-way ANOVA. To do this, we will implement
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$\Delta\Delta$ plots, in which the difference of means ($\Delta$) of
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two groups is subtracted from a second two-group $\Delta$.
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**Implemented in v2023.02.14.**
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- Currently, DABEST can analyse multiple paired data in a single plot,
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and multiple groups with a common, shared control. However, a common
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design in biomedical science is to follow the same group of subjects
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over multiple, successive time points. An estimation plot for this
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would combine elements of the two other designs, and could be used in
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place of a repeated-measures ANOVA. **Implemented in v2023.02.14**
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- We have observed that proportional data are often analyzed in
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neuroscience and other areas of biomedical research. However, compared
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to other data types, the charts are frequently impoverished: often,
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they omit error bars, sample sizes, and even P values—let alone effect
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sizes. We would like DABEST to feature proportion charts, with error
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bars and a curve for the distribution of the proportional differences.
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**Implemented in v2023.02.14**
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We encourage contributions for the above features.
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If you have any specific comments and ideas for new features that you
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would like to share with us, please fill this
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[form](https://docs.google.com/forms/d/1XnF-dkPFUYDPxH9WNXK0L2uU0uv2ZDy4paiCJuk_Kn0).
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## Acknowledgements
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## Testing
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To test DABEST, you will need to install
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[pytest](https://docs.pytest.org/en/latest).
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To test DABEST, you need to install
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[pytest](https://docs.pytest.org/en/latest) and
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[nbdev](https://nbdev.fast.ai/).
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- Run `pytest` in the root directory of the source distribution. This
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runs the test suite in the folder `dabest/tests/mpl_image_tests`.
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- Run `nbdev_test` in the root directory of the source distribution.
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This runs the value assertion tests in parent folder `dabest/tests`
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The test suite ensures that the bootstrapping functions and the plotting
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functions perform as expected.
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Run `pytest` in the root directory of the source distribution. This runs
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the test suite in the folder `dabest/tests`. The test suite will ensure
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that the bootstrapping functions and the plotting functions perform as
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For detailed information, please refer to the [test
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## DABEST in other languages
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nbs/01-getting_started.ipynb

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"Clone the [DABEST-python repo](https://github.com/ACCLAB/DABEST-python) locally (see instructions [here](https://help.github.com/articles/cloning-a-repository/)).\n",
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"``` shell\n",
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"id": "a9f8cb3e",
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"metadata": {},
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"source": [
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"To test DABEST, you will need to install [pytest](https://docs.pytest.org/en/latest/). \n",
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"To test DABEST, you will need to install [pytest](https://docs.pytest.org/en/latest/) and [nbdev](https://nbdev.fast.ai/). \n",
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"\n",
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"Run ``nbdev_export && nbdev_test`` in the root directory of the source distribution. This runs the value assertion tests in ``dabest/tests`` folder\n",
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"\n",
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"Run ``pytest`` in the root directory of the source distribution. This runs the image-based tests in ``dabest/tests/mpl_image_tests`` sub folder.\n",
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"Run ``pytest`` in the root directory of the source distribution. This runs the test suite in ``dabest/tests`` folder including also the image-based tests of the ``mpl_image_tests`` sub folder. The test suite will ensure that the bootstrapping functions and the plotting functions perform as expected.\n",
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"The test suite will ensure that the bootstrapping functions and the plotting functions perform as expected.\n",
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"\n"
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]
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},
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A,B,C,D
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8.109188439895592,9.33184689521894,9.354787823122058,12.672612419124242
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10.131749781263766,9.33184689521894,9.455474658800501,7.66146433397944
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7.178065881431648,14.342995181076896,9.577728760474645,7.66146410459298
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7.070698283373329,6.826272752289961,9.580692407448097,7.66146410459298
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14.530513949101707,11.837421038147918,8.976055745893488,7.66146410459298
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12.837160139759924,9.33184689521894,13.280120639175362,12.672612419124242
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8.98967523846707,9.33184689521894,5.284223374586355,7.66146410459298
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9.548347716611921,14.342995181076896,9.580597428100837,12.672612419124242
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10.98994063849879,9.33184689521894,9.547969576803277,7.66146410459298
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12.402350479094743,6.826272752289961,9.435510391485826,7.66146410459298
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11.694550072150143,6.826272752289961,9.277034488877351,12.672612419124242
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4.8799780463809785,9.33184689521894,9.389691597155812,12.672612419124242
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9.528364669906528,9.33184689521894,9.586309213728654,12.672612419124242
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9.392042031837274,9.33184689521894,17.540147276068026,7.66146410459298
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12.717374632226587,14.342995181076896,10.13365661827971,12.672612419124242

nbs/blog/posts/robust-beautiful/robust-beautiful.ipynb

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"In the above figure, four different samples with wildly different\n",
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"the same when visualized with a barplot on the right panel. (You can\n",
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"download the [dataset](_static/four_samples.csv) to see for yourself.)\n",
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"download the [dataset](four_samples.csv) to see for yourself.)\n",
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"[article 1](https://www.nature.com/articles/nmeth.2837),\n",

nbs/read_me.ipynb

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"\n",
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"```shell\n",
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"conda config --add channels conda-forge\n",
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"```\n",
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"pip install dabest\n",
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"You can also [clone](https://help.github.com/articles/cloning-a-repository) this repo locally.\n",
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"\n",
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"source": [
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"## Contributing\n",
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"\n",
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"All contributions are welcome; please read the [Guidelines for contributing](https://github.com/ACCLAB/DABEST-python/blob/master/CONTRIBUTING.md) first.\n",
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"All contributions are welcome; please read the [Guidelines for contributing](CONTRIBUTING.md) first.\n",
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"\n",
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"We also have a [Code of Conduct](https://github.com/ACCLAB/DABEST-python/blob/master/CODE_OF_CONDUCT.md) to foster an inclusive and productive space.\n"
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"We also have a [Code of Conduct](CODE_OF_CONDUCT.md) to foster an inclusive and productive space.\n"
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]
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},
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{
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"metadata": {},
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"source": [
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"### A wish list for new features\n",
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"If you have any specific comments and ideas for new features that you would like to share with us, please fill this form. **Add the link to a google doc form**"
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"If you have any specific comments and ideas for new features that you would like to share with us, please fill this [form](https://docs.google.com/forms/d/1XnF-dkPFUYDPxH9WNXK0L2uU0uv2ZDy4paiCJuk_Kn0)."
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"\n",
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"## Testing\n",
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"\n",
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"To test DABEST, you need to install [pytest](https://docs.pytest.org/en/latest).\n",
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"To test DABEST, you need to install [pytest](https://docs.pytest.org/en/latest) and [nbdev](https://nbdev.fast.ai/).\n",
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"\n",
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"Run `pytest` in the root directory of the source distribution. This runs the test suite in the folder `dabest/tests`. The test suite ensures that the bootstrapping functions and the plotting functions perform as expected.\n",
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"- Run `pytest` in the root directory of the source distribution. This runs the test suite in the folder `dabest/tests/mpl_image_tests`. \n",
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"- Run `nbdev_test` in the root directory of the source distribution. This runs the value assertion tests in parent folder `dabest/tests`\n",
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"\n",
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"The test suite ensures that the bootstrapping functions and the plotting functions perform as expected.\n",
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"\n",
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"For detailed information, please refer to the [test folder](nbs/tests/README.md)\n",
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"\n",
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"## DABEST in other languages\n",
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"\n",
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"DABEST is also available in R ([dabestr](https://github.com/ACCLAB/dabestr)) and Matlab ([DABEST-Matlab](https://github.com/ACCLAB/DABEST-Matlab)).\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7106313a",
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"metadata": {},
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"source": []
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"metadata": {

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