This Package will implement dummy columns for a column with multiple values.
The various supported format are :
1 :host_verifications is a column with values [‘email’, ‘phone’, ‘reviews’, ‘kba’] and we need to create dummy columns separately for each feature.
2 :amenites is a column with values {TV,”Cable TV”,Internet,”Wireless Internet”} and we need to create dummy columns separately for each feature.
The above two senarious are examples where this package can be used to get dummy columns embeded with original dataframe for further analysis.
Code to execute:
Step 1 :- create an object of Mdummies and provide dataframe name and column name as arguments.
from Multiple_dummies import Mdummies
dummies=Mdummies(airbnb_seatle_lis,’amenities’)
step 2: call the function create dummies.
dummies.create_dummies()
Step 3 : Result obtained.
The output will be the dataframe with all the dummy columns attached to the original dataframe and the original column with multiple values will be dropped. Home-page: UNKNOWN Author: Rajath Nagaraj Author-email: rnagara1@mtu.edu License: UNKNOWN Description-Content-Type: UNKNOWN Description: UNKNOWN Platform: UNKNOWN
Metadata
Release files for Multiple-dummies 2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| Multiple_dummies-2.0.tar.gz | 1.8 kB | Without provenance | Details for Multiple_dummies-2.0.tar.gz |
Release files / Multiple_dummies-2.0.tar.gz
| Download URL | Multiple_dummies-2.0.tar.gz |
|---|---|
| Size | 1.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
471a370bac82eb2c336b051de1ce709eb5f4b67bcb657fc7c6a7fc7af43abfef
|
|
BLAKE2b-256 checksum How to use checksums |
deff624cf35ae6ae0a429d2c405035953f351be28b69a9f35d92f3e589309a7f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/38.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.3
|
Security for Multiple-dummies 2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.