Metadata-Version: 2.1
Name: cosdem
Version: 0.0.1
Summary: Comparing Statistical Differences of Measurements
Home-page: http://github.com/yigitsener/cosdem_project
Author: Yiğit Şener
Author-email: dataevreni@gmail.com
License: MIT
Description: # COSDEM
        Cosdem is a python package for comparing statistical differences of measurements in two-dimension data especially equivalent medical devices
        
        ## Introduction 
        
        **Cosdem** aims to compare two-dimension data with many statistical tests and graphs in one method. 
        
        As an open-source tasking library, **cosdem**, provides one report on the following tests and graphs:
        ### Tests
        - Descriptive Statistics 
        - Homogeneity Tests of Variances
        - Normality Test: Shapiro Wilk
        - Statistical Difference Tests
        - Correlation Tests
        - Regression Result
        
        ###Graphs
        - Violin Plot
        - Regression Line in Scatter Plot
        - Blant Altman Plot
        
        ## Installation
        
        Prerequisites: `python3 >= 5` and `pip3`.
        
        ``` pip install cosdem ```
        
        or
        
        ``` git clone git@github.com:yigitsener/cosdem.git ```
        
        ## Usage
        
        ```python
        from cosdem import Cosdem
        import pandas as pd
        import random
        
        a = []
        b = []
        for i in range(50):
            a.append(random.uniform(10,15))
            b.append(random.uniform(10,15))
        
        df = pd.DataFrame({"Feature A":a, "Feature B":b})
        
        tests = Cosdem(df)
        
        ```
        ## Functions
        
        Text results
        ```python
        print(tests.report())
        ```
        
        Save all tables in Excel file
        ```python
        print(tests.save_all_tables())
        ```
        
        Save all graphs/figures in Excel file
        ```python
        print(tests.save_all_figures())
        ```
Keywords: Statistical Difference Tests,t test,regression,correlation,mann wihtney u test,Homogeneity Tests,Normality Test,Descriptive Statistics,bland altman plot,violin plot
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.6.*
Description-Content-Type: text/markdown
