A Python pip package to remove outliers from the dataset
Outlier row removal using inter quartile range
Project 2 : UCS633 DATA ANALYSIS AND VISUALIZATION
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 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.
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>
Output dataset after removal
It is clearly visible that the rows S1,S8 and S9 have been removed from the dataset.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size outlier_removal_yash_saxena-1.0.2-py3-none-any.whl (4.2 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size outlier-removal-yash-saxena-1.0.2.tar.gz (3.6 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for outlier_removal_yash_saxena-1.0.2-py3-none-any.whl
Hashes for outlier-removal-yash-saxena-1.0.2.tar.gz