From 2858640614545d2600b820c49cb994a0ca73cd21 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Thu, 4 Sep 2025 23:39:40 +0200 Subject: [PATCH 1/8] Update README with workshop link and title case added youtube link --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index c418f0e..30c2926 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,8 @@ -Welcome to the sktime workshop at pydata global 2024 +Welcome to the sktime workshop at PyData Global 2024 ==================================================== +:movie_camera: Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) + This tutorial is about [skchange] and sktime [sktime]. `skchange` is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation. From 6e8427fb42a764dac0caa3d81b884004f4cd92c8 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Thu, 4 Sep 2025 23:47:52 +0200 Subject: [PATCH 2/8] Update YouTube link with badge in README add badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 30c2926..c8a9034 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ Welcome to the sktime workshop at PyData Global 2024 ==================================================== -:movie_camera: Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) +![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=flat&logo=YouTube&logoColor=white) Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) This tutorial is about [skchange] and sktime [sktime]. From 7d3d1e3946e6896111ab2c5105b66d3f0940f5da Mon Sep 17 00:00:00 2001 From: Franky1 Date: Thu, 4 Sep 2025 23:49:35 +0200 Subject: [PATCH 3/8] Update YouTube badge style in README.md update badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c8a9034..eff019c 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ Welcome to the sktime workshop at PyData Global 2024 ==================================================== -![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=flat&logo=YouTube&logoColor=white) Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) +![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white) Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) This tutorial is about [skchange] and sktime [sktime]. From f0a63cb4ecfbef5fe207fabdb05bb62a24ae6339 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Thu, 4 Sep 2025 23:52:03 +0200 Subject: [PATCH 4/8] Update README with YouTube workshop recording details Added a description of the workshop recording on YouTube. --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index eff019c..252e58e 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,9 @@ Welcome to the sktime workshop at PyData Global 2024 ==================================================== -![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white) Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) +![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white) + +Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) This tutorial is about [skchange] and sktime [sktime]. From f60b1617b191893ece73807a2e482c255621d0c1 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Thu, 4 Sep 2025 23:52:47 +0200 Subject: [PATCH 5/8] Modify README with new YouTube badge and details Updated YouTube badge style and added tutorial description. --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 252e58e..b73d4b6 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,12 @@ Welcome to the sktime workshop at PyData Global 2024 ==================================================== -![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white) +![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=flat&logo=YouTube&logoColor=white) Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) +--- + This tutorial is about [skchange] and sktime [sktime]. `skchange` is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation. From 485aef67046caa94426f08e2b69062511fa8f981 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Fri, 5 Sep 2025 21:40:56 +0200 Subject: [PATCH 6/8] markdown linting --- README.md | 33 +++++++++++++-------------------- 1 file changed, 13 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index b73d4b6..0b28ece 100644 --- a/README.md +++ b/README.md @@ -1,19 +1,14 @@ -Welcome to the sktime workshop at PyData Global 2024 -==================================================== +# Welcome to the sktime workshop at PyData Global 2024 -![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=flat&logo=YouTube&logoColor=white) +[![!youtube](https://img.shields.io/static/v1?logo=youtube&label=YouTube&message=Workshop&color=red)](https://www.youtube.com/watch?v=VwhevNkxjYw) -Recording of the workshop on [YouTube](https://www.youtube.com/watch?v=VwhevNkxjYw) +This tutorial is about [skchange] and [sktime]. ---- - -This tutorial is about [skchange] and sktime [sktime]. - -`skchange` is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation. - -`skchange` is based on, and extends, `sktime`, the most widely used scikit-learn compatible framework library for learning with time series. +- `skchange` is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation. +- `skchange` is based on, and extends, `sktime`, the most widely used scikit-learn compatible framework library for learning with time series. Both packages are maintained under permissive license, easily extensible by anyone, and interoperable with the python data science stack. + This workshop gives a hands-on introduction to the new joint detection interface developed in skchange and sktime, for detecting point anomalies, changepoints, and segment anomalies. [skchange]: https://skchange.readthedocs.io/en/latest/ @@ -27,9 +22,9 @@ In the tutorial, we will move through notebooks section by section. You have different options how to run the tutorial notebooks: -* Run the notebooks in the cloud on [Binder] - for this you don't have to install anything! -* Run the notebooks on your machine. [Clone] this repository, get [conda], install the required packages (`sktime`, `seaborn`, `jupyter`) in an environment, and open the notebooks with that environment. For detail instructions, see below. For troubleshooting, see sktime's more detailed [installation instructions]. -* or, use python venv, and/or an editable install of this repo as a package. Instructions below. +- Run the notebooks in the cloud on [Binder] - for this you don't have to install anything! +- Run the notebooks on your machine. [Clone] this repository, get [conda], install the required packages (`sktime`, `seaborn`, `jupyter`) in an environment, and open the notebooks with that environment. For detail instructions, see below. For troubleshooting, see sktime's more detailed [installation instructions]. +- or, use python venv, and/or an editable install of this repo as a package. Instructions below. [Binder]: https://mybinder.org/v2/gh/sktime/sktime-tutorial-pydata-global-2024/main?filepath=notebooks [clone]: https://help.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository @@ -53,7 +48,6 @@ Both `skchange` and `sktime` are developed by open communities, with aims of eco We invite anyone to get involved as a developer, user, supporter (or any combination of these). - ## :movie_camera: Other Tutorials - [EuroSciPy 2024 - Hierarchical, global forecasting, foundation models, extensions and marketplace](https://github.com/sktime/sktime-workshop-euroscipy2024) @@ -76,7 +70,6 @@ We invite anyone to get involved as a developer, user, supporter (or any combina - [Pydata Global 2022 - Feature extraction, Pipelines, Tuning](https://github.com/sktime/sktime-tutorial-pydata-global-2022) - ## :wave: How to contribute If you're interested in contributing to `skchange` or `sktime`, @@ -88,8 +81,8 @@ Any contributions are welcome, not just code! To run the notebooks locally, you will need: -* a local repository clone -* a python environment with required packages installed +- a local repository clone +- a python environment with required packages installed ### Cloning the repository @@ -113,8 +106,8 @@ To clone the repository locally: 1. Create a python virtual environment: `python -m venv skchange_pydata` 2. Activate your environment: - - `source skchange_pydata/bin/activate` for Linux - - skchange_pydata/Scripts/activate` for Windows +`source skchange_pydata/bin/activate` for Linux +`skchange_pydata/Scripts/activate` for Windows 3. Install the requirements: `pip install -r requirements` 4. If using jupyter: make the environment available in jupyter: From 822430b3accaf711f8eb1f0c0fd6a036aac3aba1 Mon Sep 17 00:00:00 2001 From: Franky1 Date: Fri, 5 Sep 2025 23:40:04 +0200 Subject: [PATCH 7/8] update --- README.md | 22 ++++++++++++---------- 1 file changed, 12 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 0b28ece..d6f24f5 100644 --- a/README.md +++ b/README.md @@ -88,27 +88,29 @@ To run the notebooks locally, you will need: To clone the repository locally: -`git clone https://github.com/sktime/sktime-tutorial-pydata-global-2024` +```shell +git clone https://github.com/sktime/sktime-tutorial-pydata-global-2024 +``` ### Using conda env 1. Create a python virtual environment: -`conda create -y -n skchange_pydata python=3.11` + `conda create -y -n skchange_pydata python=3.11` 2. Install required packages: -`conda install -y -n skchange_pydata pip skchange sktime seaborn jupyter pmdarima statsmodels` + `conda install -y -n skchange_pydata pip skchange sktime seaborn jupyter pmdarima statsmodels` 3. Activate your environment: -`conda activate skchange_pydata` + `conda activate skchange_pydata` 4. If using jupyter: make the environment available in jupyter: -`python -m ipykernel install --user --name=skchange_pydata` + `python -m ipykernel install --user --name=skchange_pydata` ### Using python venv 1. Create a python virtual environment: -`python -m venv skchange_pydata` + `python -m venv skchange_pydata` 2. Activate your environment: -`source skchange_pydata/bin/activate` for Linux -`skchange_pydata/Scripts/activate` for Windows + `source skchange_pydata/bin/activate` for Linux + `skchange_pydata/Scripts/activate` for Windows 3. Install the requirements: -`pip install -r requirements` + `pip install -r requirements` 4. If using jupyter: make the environment available in jupyter: -`python -m ipykernel install --user --name=skchange_pydata` + `python -m ipykernel install --user --name=skchange_pydata` From 2a171eb790e833489b695e76071ea3b024d55a0e Mon Sep 17 00:00:00 2001 From: Franky1 Date: Fri, 5 Sep 2025 23:45:56 +0200 Subject: [PATCH 8/8] update --- README.md | 48 +++++++++++++++++++++++++++++++++++++++--------- 1 file changed, 39 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index d6f24f5..abe46f3 100644 --- a/README.md +++ b/README.md @@ -95,22 +95,52 @@ git clone https://github.com/sktime/sktime-tutorial-pydata-global-2024 ### Using conda env 1. Create a python virtual environment: - `conda create -y -n skchange_pydata python=3.11` + + ```shell + conda create -y -n skchange_pydata python=3.11 + ``` + 2. Install required packages: - `conda install -y -n skchange_pydata pip skchange sktime seaborn jupyter pmdarima statsmodels` + + ```shell + conda install -y -n skchange_pydata pip skchange sktime seaborn jupyter pmdarima statsmodels + ``` + 3. Activate your environment: - `conda activate skchange_pydata` + + ```shell + conda activate skchange_pydata + ``` + 4. If using jupyter: make the environment available in jupyter: - `python -m ipykernel install --user --name=skchange_pydata` + + ```shell + python -m ipykernel install --user --name=skchange_pydata + ``` ### Using python venv 1. Create a python virtual environment: - `python -m venv skchange_pydata` + + ```shell + python -m venv skchange_pydata + ``` + 2. Activate your environment: - `source skchange_pydata/bin/activate` for Linux - `skchange_pydata/Scripts/activate` for Windows + + ```shell + source skchange_pydata/bin/activate # for Linux + skchange_pydata/Scripts/activate # for Windows + ``` + 3. Install the requirements: - `pip install -r requirements` + + ```shell + pip install -r requirements.txt + ``` + 4. If using jupyter: make the environment available in jupyter: - `python -m ipykernel install --user --name=skchange_pydata` + + ```shell + python -m ipykernel install --user --name=skchange_pydata + ```