Hello, you are welcome to PB_Sent classifier
A sentiment lexicon algorithm to classify pidgin English and English text into positive, negative or neutral
To use this system, you can enter raw text directly or enter your document name which should be in a csv file format (for example, data.csv). You need to name the column as 'text'. The system creates new column for score and class. You should expect the output as shown below.
text score class
the bank is good 2 positive
How to use the packages
pip install PB_Sent
from sentileye.polarity import result
Follow the instructions, enter your csv filename (for example, data.csv) or your raw text directly to classify. NB: filename - the csv file must be in your current working directory
1 maintainer
Metadata
1 maintainer
Release files for PB-Sent 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| PB_Sent-0.0.1.tar.gz | 4.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| PB_Sent-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 51.5 kB
Release files / PB_Sent-0.0.1.tar.gz
| Download URL | PB_Sent-0.0.1.tar.gz |
|---|---|
| Size | 4.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
Release files / PB_Sent-0.0.1-py3-none-any.whl
| Download URL | PB_Sent-0.0.1-py3-none-any.whl |
|---|---|
| Size | 47.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
