Comments (7)
MaxHalford
commented on June 12, 2024
1
Ok great, it works for me too (locally). I've just published a new version (0.10.8) with your change. The docs are being built now.
Thanks!
from prince.
MaxHalford
commented on June 12, 2024
Hey there. Sure, I think that's possible. I guess it's poetry which added altair <5.0.0 by itself. Would you like to take of this in a pull request?
from prince.
skupr-anaconda
commented on June 12, 2024
First, I would test if it will work correctly. That's why I'm asking about the compatibility
from prince.
MaxHalford
commented on June 12, 2024
Of course. The way to test it would be to bump to dependency, and then run jupyter nbconvert --execute --to notebook --inplace docs/content/*.ipynb to check all the notebooks run without raising an exception. Then one would have to visually inspect the notebooks to checks nothing looks wrong.
from prince.
skupr-anaconda
commented on June 12, 2024
Looks like only ca.ipynb failed if I run:
Visualization
ca.plot(
dataset,
x_component=0,
y_component=1
)
with an error:
Javascript Error: Failed to execute 'setAttribute' on 'Element': '0' is not a valid attribute name.
This usually means there's a typo in your chart specification. See the javascript console for the full traceback.
The same issue was on the altair project altair-viz/altair#3041 but after reopening the notebook at the same browser, restarting the kernel with clearing cells, and running all cells again the issue has been resolved.
from prince.
skupr-anaconda
commented on June 12, 2024
I've opened a PR #159
from prince.
skupr-anaconda
commented on June 12, 2024
My logs:
╰─❯ poetry install
Installing dependencies from lock file
Package operations: 0 installs, 33 updates, 0 removals
• Updating attrs (22.1.0 -> 23.1.0)
• Updating platformdirs (2.5.2 -> 3.8.0)
• Updating pyrsistent (0.18.0 -> 0.19.3)
• Updating traitlets (5.7.1 -> 5.9.0)
• Updating asttokens (2.0.5 -> 2.2.1)
• Updating executing (0.8.3 -> 1.2.0)
• Updating fastjsonschema (2.16.2 -> 2.17.1)
• Updating pyzmq (25.0.2 -> 25.1.0)
• Updating tornado (6.2 -> 6.3.2)
• Updating wcwidth (0.2.5 -> 0.2.6)
• Updating appnope (0.1.2 -> 0.1.3)
• Updating jedi (0.18.1 -> 0.18.2)
• Updating jupyter-client (8.1.0 -> 8.3.0)
• Updating markupsafe (2.1.1 -> 2.1.3)
• Updating nbformat (5.7.0 -> 5.9.0)
• Updating numpy (1.24.2 -> 1.24.4)
• Updating prompt-toolkit (3.0.36 -> 3.0.38)
• Updating pygments (2.15.0 -> 2.15.1)
• Updating pytz (2022.7 -> 2023.3)
• Updating stack-data (0.2.0 -> 0.6.2)
• Updating bleach (4.1.0 -> 6.0.0)
• Updating comm (0.1.2 -> 0.1.3)
• Updating debugpy (1.5.1 -> 1.6.7)
• Updating jupyterlab-pygments (0.1.2 -> 0.2.2)
• Updating mistune (0.8.4 -> 3.0.1)
• Updating nbclient (0.5.13 -> 0.8.0)
• Updating packaging (23.0 -> 23.1)
• Updating pandas (1.5.3 -> 2.0.2)
• Updating psutil (5.9.0 -> 5.9.5)
• Updating virtualenv (20.17.1 -> 20.23.1)
• Updating altair (4.2.2 -> 5.0.1)
• Updating ipykernel (6.19.2 -> 6.23.3)
• Updating nbconvert (6.5.4 -> 7.6.0)
Installing the current project: prince (0.10.7)
╰─❯ poetry run jupyter nbconvert --execute --to notebook --inplace docs/content/*.ipynb
[NbConvertApp] Converting notebook docs/content/ca.ipynb to notebook
[NbConvertApp] Writing 37696 bytes to docs/content/ca.ipynb
[NbConvertApp] Converting notebook docs/content/famd.ipynb to notebook
[NbConvertApp] Writing 138314 bytes to docs/content/famd.ipynb
[NbConvertApp] Converting notebook docs/content/gpa.ipynb to notebook
[NbConvertApp] Writing 18683 bytes to docs/content/gpa.ipynb
[NbConvertApp] Converting notebook docs/content/mca.ipynb to notebook
[NbConvertApp] Writing 35478 bytes to docs/content/mca.ipynb
[NbConvertApp] Converting notebook docs/content/mfa.ipynb to notebook
[NbConvertApp] Writing 29718 bytes to docs/content/mfa.ipynb
[NbConvertApp] Converting notebook docs/content/pca.ipynb to notebook
[NbConvertApp] Writing 104641 bytes to docs/content/pca.ipynb
from prince.
Related Issues (20)
- Unable to allocate memory HOT 4
- FAMD transform ValueError on qualitative data HOT 1
- 'MCA' object has no attribute '_check_is_fitted' with .transform HOT 2
- Not compatible with pandas 2.0.0 HOT 4
- Sklearn GridSearchCV: 'MCA' object has no attribute 'set_params' HOT 3
- Difficulty applying FMA with a group of categorical variables. HOT 1
- Handle_unknown in OneHotEncoder (FAMD) method HOT 5
- Information regarding Inverse MCA HOT 2
- MCA: plotting assumes raw dataset has already run get_dummies HOT 7
- prince.PCA vs. sklearn.decomposition.PCA? HOT 3
- UserWarning "pandas.DataFrame with sparse columns found" when running famd() HOT 1
- Feature idea: biplot HOT 2
- Feature Idea: Weights HOT 3
- How to transform on new unseen test data? HOT 3
- CA.row_coordinates only works with pd.DataFrame HOT 5
- FAMD fit method not compatible with scikit-learn pipeline HOT 2
- MCA doesn't work with column transformers of sklearn HOT 2
- Bug in FAMD transform() HOT 1
- Support for sklearn Pipelines HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from prince.