Metadata-Version: 2.1
Name: Outlier-removal-101883058
Version: 1.0.3
Summary: Removing outliers using IQR(Interquartile) range(25%-75%).
Home-page: UNKNOWN
Author: Pritpal Singh Pruthi
Author-email: psp.ps001@gmail.com
License: MIT
Description: # Outlier row removal using inter quartile range
        
        **Project 2 : UCS633**
        
        
        Submitted By: **Pritpal Singh Pruthi 101883058**
        
        ***
        pypi: <https://pypi.org/project/topsis-ppruthi-101883058/>
        ***
        
        ## IQR Interquartile range Description
        
        Any data can be described by its five-number summary. These five numbers,consist of (in ascending order):
        
        The minimum or lowest value of the dataset.
        <br>
        The first quartile Q1, which represents a quarter of the way through the list of all data.
        <br>
        The median of the data set, which represents the midpoint of the whole list of data.
        <br>
        The third quartile Q3, which represents three-quarters of the way through the list of all data.
        <br>
        The maximum or highest value of the data set.
        
        ## Calculation of acceptable data
        ```
        IQR = Q3-Q1
        lower=Q1-(1.5*IQR)
        upper=Q3+(1.5*IQR)
        ```
        The data values present in between the lower and upper are acceptable and the rest are outliers and hence being removed.
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install removal system.
        
        ```bash
        pip install Outlier-removal-101883058
        ```
        
        <br>
        
        ## How to use this package:
        
        Outlier-removal-101883058 can be run as done below:
        
        
        
        ### In Command Prompt
        ```
        >> outliers students.csv 
        ```
        <br>
        
        
        ## Sample dataset
        
        Marks| Students 
        :------------: | :-------------:
        3|S1
        57|S2
        65|S3
        98|S4
        43|S5
        44|S6
        54|S7
        99|S8
        1|S9
        
        
        <br>
        
        ## Output dataset after removal 
        
        Marks| Students 
        :------------: | :-------------:
        57|S2
        65|S3
        98|S4
        43|S5
        44|S6
        54|S7
        
        <br>
        
        It is clearly visible that the rows S1,S8 and S9 have been removed from the dataset.
        
        
        ## License
        [MIT](https://choosealicense.com/licenses/mit/)
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
