outlier-removal-yash-saxena 1.0.2

Description:

outlierremovalyashsaxena 1.0.2

Outlier row removal using inter quartile range
Project 2 : UCS633 DATA ANALYSIS AND VISUALIZATION
Submitted By: Yash saxena 101703627

pypi: https://pypi.org/project/outlier-removal-yash-saxena

git: https://github.com/yashsaxena972/outlier-removal

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-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 to install removal system.
pip install outlier-removal-yash-saxena


How to use this package:
outlier-removal-yash-saxena can be run as done below:
In Command Prompt
>> outliers <dataset.csv>


Sample dataset



Marks
Students




3
S1


57
S2


65
S3


98
S4


43
S5


44
S6


54
S7


99
S8


1
S9




Output dataset after removal



Marks
Students




57
S2


65
S3


98
S4


43
S5


44
S6


54
S7




It is clearly visible that the rows S1,S8 and S9 have been removed from the dataset.
License
MIT