CWordTM Package (cwordtm 0.7.7)

A Topic Modeling Toolkit from Low-code to Pro-code

Installation

$ pip install cwordtm

Usage

cwordtm can be used to perform some NLP pre-processing tasks, text exploration, including Chinese one, text visualization (word cloud), and topic modeling (BERTopic, LDA and NMF) as follows:

from cwordtm import meta, util, ta, tm, viz, pivot, quot

version Submodule

Provides some version information.

import cwordtm
print(cwordtm.__version__)

meta Submodule

Provides extracting source code of cwordtm module and adding timing and code-showing features to all functions of the module.

print(meta.get_module_info())

print(meta.get_submodule_info('viz', detailed=True))

quot Submodule

Provides functions to extract the quotation source Scripture in OT based on the presribed NT Scripture.

cdf = util.load_word('cuv.csv')
crom8 = util.extract2(cdf, 'Rom 8')

quot.show_quot(crom8, lang='chi')

pivot Submodule

Provides a pivot table of the prescribed text.

cdf = util.load_word('cuv.csv')

pivot.stat(cdf, chi=True)

ta Submodule

Provides text analytics functions, including extracting the summarization of the prescribed text.

cdf = util.load_word('cuv.csv')
crom8 = util.extract2(cdf, 'Rom 8')

ta.summary_chi(crom8)

tm Submodule

Provides text modeling functions, including LDA, NMF and BERTopics modeling.

lda = tm.lda_process("web.csv", eval=True, timing=True)

nmf = tm.nmf_process("web.csv", eval=True, code=1)

btm = tm.btm_process("cuv.csv", chi=True, cat='ot', eval=True)

btm = tm.btm_process("cuv.csv", chi=True, cat='nt', eval=True, code=2)

util Submodule

Provides loading text and text preprocessing functions.

df = util.load_word()
cdf = util.load_word('cuv.csv')

df.head()
cdf.head()

rom8 = util.extract2(df, 'Rom 8')
crom8 = util.extract2(cdf, 'Rom 8')

viz Submodule

Wordcloud plotting from the prescribed text.

cdf = util.load_word('cuv.csv')

viz.chi_wordcloud(cdf)

Demo

Usage demo file with output:

On BBC News: CWordTM_BBC.pdf
On Chinese Bible (CUV): CWordTM_CUV.pdf

Paper

For a more detailed overview, you can read the demo paper: https://link.springer.com/chapter/10.1007/978-3-031-70242-6_4

Documentation

cwordtm documentation can be reached from: https://cwordtm.readthedocs.io

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

cwordtm was created by Dr. Johnny Cheng. It is licensed under the terms of the MIT license.

Credits

cwordtm was created under the guidance of Jehovah, the Almighty God.