Metadata-Version: 2.1
Name: factanal
Version: 0.2.0
Summary: A python wrapper for the R function factanal.
Home-page: https://github.com/kjul/factanalpy
Author: kjul
Author-email: juliankunschke@yahoo.de
License: MIT
Description: ### Factanal
        
        Python wrapper replicating the known factor analysis output from the factanal R function. 
        The only supported input is a pandas data frame. Formulas as input are currently 
        not supported. A covariance matrix is always computed from the input data frame. 
        Setting control variables for maximum likelihood estimation is currently not 
        supported.
        
        
        Further information on R's factanal function for factor analysis: https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/factanal
        
        More information on the factanal output and examples: 
        https://data.library.virginia.edu/getting-started-with-factor-analysis/
        
        
        #### Example
        
        ```
        import pandas as pd
        import random
        from factanal.wrapper import factanal
        
        pdf = pd.DataFrame({"v1": [random.randint(0, 100) for _ in range (30)],
                            "v2": [random.randint(0, 100) for _ in range (30)],
                            "v3": [random.randint(0, 100) for _ in range (30)],
                            "v4": [random.randint(0, 100) for _ in range (30)],
                            "v5": [random.randint(0, 100) for _ in range (30)],
                            "v6": [random.randint(0, 100) for _ in range (30)],
                            "v7": [random.randint(0, 100) for _ in range (30)],
                            "v8": [random.randint(0, 100) for _ in range (30)]})
        
        fa_res = factanal(pdf, factors=4, scores='regression', rotation='promax', 
                          verbose=True, return_dict=True)
        
        
        Uniquenesses: 
           v1    v2    v3    v4    v5    v6    v7    v8 
        0.861 0.005 0.666 0.005 0.611 0.223 0.812 0.885 
        
        Loadings:
           Factor1 Factor2 Factor3 Factor4
        v1 -0.136                   0.326 
        v2  0.983           0.169   0.104 
        v3          0.128           0.575 
        v4          0.999                 
        v5 -0.114           0.199  -0.553 
        v6 -0.204          -0.825   0.197 
        v7 -0.264           0.317         
        v8                  0.313   0.106 
        
                       Factor1 Factor2 Factor3 Factor4
        SS loadings      1.127   1.048   0.953   0.807
        Proportion Var   0.141   0.131   0.119   0.101
        Cumulative Var   0.141   0.272   0.391   0.492
        
        Factor Correlations:
                Factor1 Factor2 Factor3 Factor4
        Factor1  1.0000  0.0380 -0.0526  0.1918
        Factor2  0.0380  1.0000  0.0675 -0.0599
        Factor3 -0.0526  0.0675  1.0000 -0.0671
        Factor4  0.1918 -0.0599 -0.0671  1.0000
        
        Test of the hypothesis that 4 factors are sufficient.
        The chi square statistic is 0.37 on 2 degrees of freedom.
        The p-value is 0.833 
        ```
        
        
        #### Installation
        
        ```pip install factanal```
        
        #### Dependencies
        The only dependency is the rpy2 library. 
        
        In addition to that, R must be installed on your system and accessible to rpy2.
        
        More information on rpy2: https://rpy2.github.io/doc/latest/html/index.html
        
        Download R here: https://www.r-project.org/
        
        #### Misc
        Factanal for python is MIT licensed.
        
        
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
