Python library for multidimensional analysis, classification - clustering analysis
Project description
scientisttools : Python library for multidimensional analysis
About scientisttools
scientisttools is a Python
package dedicated to multivariate Exploratory Data Analysis, clustering analysis and discriminant analysis.
Why use scientisttools?
-
It performs classical principal component methods :
- Principal Components Analysis (PCA)
- Principal Components Analysis with partial correlation matrix (PartialPCA)
- Exploratory Factor Analysis (EFA)
- Classical Multidimensional Scaling (CMDSCALE)
- Metric and Non - Metric Multidimensional Scaling (MDS)
- Correspondence Analysis (CA)
- Multiple Correspondence Analysis (MCA)
- Factor Analysis of Mixed Data (FAMD)
- Multiple Factor Analysis (MFA)
- Multiple Factor Analysis for qualitatives/categoricals variables (MFAQUAL)
- Multiple Factor Analysis of Mixed Data (MFAMIX)
- Multiple Factor Analysis of Contingence Tables (MFACT)
-
In some methods, it allowed to add supplementary informations such as supplementary individuals and/or variables.
-
It provides a geometrical point of view, a lot of graphical outputs.
-
It provides efficient implementations, using a scikit-learn API.
Those statistical methods can be used in two ways :
- as descriptive methods ("datamining approach")
- as reduction methods in scikit-learn pipelines ("machine learning approach")
scientisttools
also performs clustering analysis
- Clustering analysis:
- Hierarchical Clustering on Principal Components (HCPC)
- Variables Hierarchical Clustering Analysis (VARHCA)
- Variables Hierarchical Clustering Analysis on Principal Components (VARHCPC)
- Categorical Variables Hierarchical Clustering Analysis (CATVARHCA)
Notebooks are availabled.
Installation
Dependencies
scientisttools requires
numpy>=1.26.2
matplotlib>=3.5.3
scikit-learn>=1.2.2
pandas>=1.5.3
mapply>=0.1.21
plotnine>=0.10.1
plydata>=0.4.3
pingouin>=0.5.3
scientistmetrics>=0.0.3
ggcorrplot>=0.0.2
User installation
You can install scientisttools using pip
:
pip install scientisttools
Tutorial are available
Author
Duvérier DJIFACK ZEBAZE (duverierdjifack@gmail.com)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for scientisttools-0.1.4-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 25fa38531db1f9dd02a791db6ad84da9e3b8e84b6a77ad4df89af99b3fa1fd76 |
|
MD5 | 5ad1377584f542bbeed0fd7dd5f4a0de |
|
BLAKE2b-256 | 5a693d610aad9656f5a0c6cf94777fc3af2a2162528e66339513d7ae4c84f1ca |