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
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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