Handling missing values in python
Project description
HANDLING MISSING DATA
PROJECT 3, UCS633 - Data Analysis and Visualization
Nikhil Gupta
COE17
Roll number: 101703371
Output is the dataset which contains no missing values and this dataset is streamed to a new csv file whose name is provided by the user.
Installation
pip install hmvpack_NG
Note the name has an underscore not a hyphen. If installation gives error or package is not found after installing, install as sudo.
Recommended - test it out in a virtual environment.
To use via command line
The package contains two functions i.e there are two ways of handling missing data. First two arguments are same for accessing both functions.
- Deleting the row with missing values.
HMVcli infile.csv outfile.csv D
- Replacing the missing values by mean of the values of that particular feature
HMVcli infile.csv outfile.csv R
To use in .py script
For Deletion function ->
from hmvlib.models import delete_record
delete_record('infile.csv', 'oufile.csv')
For Replacement function ->
from hmvlib.models import replace_record
replace_record('infile.csv', 'oufile.csv')
Can email me for any issues or suggestions
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
Hashes for hmvpack_NG-0.0.3-py2-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5171a7e42d991d137576364aac4b8238eb237660f0eb1477433e94634398243d |
|
MD5 | d911727ff49017cbcb789e654ba5ce0e |
|
BLAKE2b-256 | f7cf9de868d3aca2b495acb778b1eb850ecf9a1c81925652dd4604db58e4212f |