Skip to main content

A Python pip package to remove outliers from the dataset

Project description

Outlier row removal using inter quartile range


Submitted By: Yash saxena 101703627


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

The data values present in between the lower and upper are acceptable and the rest are outliers and hence being removed.


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.



Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

outlier-removal-yash-saxena-1.0.2.tar.gz (3.6 kB view hashes)

Uploaded source

Built Distribution

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page