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pip install 装上了pyLDAvis
pip install pyLDAvis -i http://pypi.douban.com/simple --trusted-host
(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
本以为开开心心地就能用了,然而一运行代码报错:
卸载刚装的 pyLDAvis==3.3.1
安装指定版本 pyLDAvis==2.1.2。
pip install pyLDAvis==2.1.2 -i http://pypi.douban.com/simple --trusted-host pypi.douban.com
或者不用安装旧版本,用新版本的方法:
import pyLDAvis.gensim_models as gensimvis from pyLDAvis import gensim pyLDAvis.enable_notebook() ''' lda: 计算好的话题模型 corpus: 文档词频矩阵 dictionary: 词语空间 ''' d = gensim.prepare(lda,corpus,dictionary) d = gensimvis.prepare(lda,corpus,dictionary) pyLDAvis.display(d) # 展示在浏览器 # pyLDAvis.save_html(p, 'lda.html')
利用 pyLDAvis.save_html(p, ‘lda.html’) 方法可以将可视化结果保存为单独的 HTML 文件。
参考了:
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