Removing outliers using IQR(Interquartile) range(25%-75%).
Project 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-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-101883058
How to use this package:
Outlier-removal-101883058 can be run as done below:
In Command Prompt
>> outliers students.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.
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