Outlier Removal Using Z-score
Project description
Library for removing outliers from pandas dataframe
PROJECT 2, UCS633 - Data Analysis and Visualization
Navkiran Singh
COE17
Roll number: 101703365
Takes two inputs - filename of input csv, intended filename of output csv. Third optional argument is threshold, by default it's 1.5. Output is the number of rows removed from the input dataset. Resulting csv is saved as output.csv.
Installation
pip install outliers_navkiran
Recommended - test in a virtual environment.
Use via command line
outliers_navkiran_cli in.csv out.csv
When providing custom threshold:
outliers_navkiran_cli in.csv out.csv 1.5
First argument after outcli is the input csv filename from which the dataset is extracted. The second argument is for storing the final dataset after processing.
Use in .py script
from outliers_navkiran import remove_outliers
remove_outliers('input.csv', 'output.csv',1.5)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for outliers_navkiran-1.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 25c9511c054bd3da40072effb6a54fecbd31e38c307069c772e32a76c0a074dc |
|
MD5 | 598014d6338048f392c051b38ee49322 |
|
BLAKE2b-256 | 290491e701b2529083091926ae010aa14ac56575b8305140c9d3e7ef3c89edd7 |