Metadata-Version: 2.1
Name: big-data-normality
Version: 0.1.6
Summary: Normality Test for Big Data
Home-page: https://github.com/serhateerdem
Author: Serhat Erdem
Author-email: erdemserhat1994@gmail.com
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# Empirical Normality Test 

A normality test based on empirical rule for big data

### Installation
```
pip install big-data-normality
```

### Get started
How to get normality test for dataset with this lib:

```Python
# Library import
from big_data_normality.empirical_normality_test import EmpiricalNormalityTest
# Graph output
from big_data_normality.empirical_normality_test import EmpiricalNormalityTestGraph


# This line of code will allow shorter imports
from big_data_normality import EmpiricalNormalityTest
# Graph output
from big_data_normality import EmpiricalNormalityTestGraph

# Instantiate a EmpiricalNormalityTest object
"""Firstly, import the excel file, then run the library
P.S. Excel file must include name of each column. Like that;

name1	name2	name3	name4 ...
73,36	72,64	68,45	66,52 ...
78,97	67,04	60,85	70,96 ...
...     ...     ...     ...   ...

"""

import os
import pandas as pd

path = r'C:\data'
os.chdir(path)
df = pd.read_excel("my_dataset.xlsx")
# Test output
print(EmpiricalNormalityTest(df))
# Graph output
print(EmpiricalNormalityTestGraph(df))
```
