Metadata-Version: 2.1
Name: Outlier-removal-101883058
Version: 1.0.0
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
        The first quartile Q1, which represents a quarter of the way through the list of all data
        The median of the data set, which represents the midpoint of the whole list of data
        The third quartile Q3, which represents three-quarters of the way through the list of all data
        The maximum or highest value of the data set.
        
        ## Calculation of acceptable data
        ```
        IQR = Q3 â€“ 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
