pip install 裝上了pyLDAvis
pip install pyLDAvis -i http://pypi.douban.com/simple --trusted-host 複制
(base) C:\Users\Administrator>pip install pyLDAvis -i http://pypi.douban.com/simple --trusted-host pypi.douban.com
Looking in indexes: http://pypi.douban.com/simple
Collecting pyLDAvis
Downloading http://pypi.doubanio.com/packages/03/a5/15a0da6b0150b8b68610cc78af80364a80a9a4c8b6dd5ee549b8989d4b60/pyLDAvis-3.3.1.tar.gz (1.7 MB)
|████████████████████████████████| 1.7 MB 6.8 MB/s
Installing build dependencies ... done
Getting requirements to build wheel ... done
Installing backend dependencies ... done
Preparing wheel metadata ... done
Requirement already satisfied: pandas>=1.2.0 in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (1.3.4)
Requirement already satisfied: future in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (0.18.2)
Requirement already satisfied: numpy>=1.20.0 in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (1.20.3)
Requirement already satisfied: scipy in c:\users\administrator\appdata\roaming\python\python38\site-packages (from pyLDAvis) (1.6.0)
Requirement already satisfied: joblib in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (1.0.1)
Requirement already satisfied: gensim in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (3.8.3)
Requirement already satisfied: scikit-learn in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (0.23.1)
Requirement already satisfied: jinja2 in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (2.7.2)
Requirement already satisfied: setuptools in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (49.2.0.post20200714)
Collecting sklearn
Downloading http://pypi.doubanio.com/packages/1e/7a/dbb3be0ce9bd5c8b7e3d87328e79063f8b263b2b1bfa4774cb1147bfcd3f/sklearn-0.0.tar.gz (1.1 kB)
Requirement already satisfied: numexpr in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (2.7.1)
Requirement already satisfied: funcy in d:\python\anaconda3\lib\site-packages (from pyLDAvis) (1.17)
Requirement already satisfied: pytz>=2017.3 in d:\python\anaconda3\lib\site-packages (from pandas>=1.2.0->pyLDAvis) (2020.1)
Requirement already satisfied: python-dateutil>=2.7.3 in d:\python\anaconda3\lib\site-packages (from pandas>=1.2.0->pyLDAvis) (2.8.1)
Requirement already satisfied: six>=1.5.0 in d:\python\anaconda3\lib\site-packages (from gensim->pyLDAvis) (1.15.0)
Requirement already satisfied: smart-open>=1.8.1 in d:\python\anaconda3\lib\site-packages (from gensim->pyLDAvis) (4.1.2)
Requirement already satisfied: Cython==0.29.14 in d:\python\anaconda3\lib\site-packages (from gensim->pyLDAvis) (0.29.14)
Requirement already satisfied: threadpoolctl>=2.0.0 in d:\python\anaconda3\lib\site-packages (from scikit-learn->pyLDAvis) (2.1.0)
Requirement already satisfied: markupsafe in d:\python\anaconda3\lib\site-packages (from jinja2->pyLDAvis) (2.0.1)
Building wheels for collected packages: pyLDAvis, sklearn
Building wheel for pyLDAvis (PEP 517) ... done
Created wheel for pyLDAvis: filename=pyLDAvis-3.3.1-py2.py3-none-any.whl size=136900 sha256=e23c194c0ef03967d487011208dede4141f5f6a163a77111283455f230c697fa
Stored in directory: c:\users\administrator\appdata\local\pip\cache\wheels\b5\ee\b2\29f82d7103ba90942d31cdeb29372b27fb74dbe7ff535cc081
Building wheel for sklearn (setup.py) ... done
Created wheel for sklearn: filename=sklearn-0.0-py2.py3-none-any.whl size=1320 sha256=9a20c412366931bdd7ca5bad4a82cdac502d9414a32a5320641b1898e633cd6e
Stored in directory: c:\users\administrator\appdata\local\pip\cache\wheels\c5\c2\a1\e36638731a4ac05326b1bf08abc0d79c19ba07700cf6b5d648
Successfully built pyLDAvis sklearn
Installing collected packages: sklearn, pyLDAvis
Successfully installed pyLDAvis-3.3.1 sklearn-0.0 複制
本以為開開心心地就能用了，然而一運作代碼報錯：
解除安裝剛裝的 pyLDAvis==3.3.1
安裝指定版本 pyLDAvis==2.1.2。
pip install pyLDAvis==2.1.2 -i http://pypi.douban.com/simple --trusted-host pypi.douban.com 複制
或者不用安裝舊版本，用新版本的方法：
import pyLDAvis.gensim_models as gensimvis
from pyLDAvis import gensim
pyLDAvis.enable_notebook()
'''
lda: 計算好的話題模型
corpus: 文檔詞頻矩陣
dictionary: 詞語空間
'''
d = gensim.prepare(lda,corpus,dictionary)
d = gensimvis.prepare(lda,corpus,dictionary)
pyLDAvis.display(d) # 展示在浏覽器
# pyLDAvis.save_html(p, 'lda.html') 複制
利用 pyLDAvis.save_html(p, ‘lda.html’) 方法可以将可視化結果儲存為單獨的 HTML 檔案。