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
