tidytext-py

使用pandas DataFrames的便捷文本处理。

此库是R包tidytext的Python端口。

安装

pip install tidytext

这将还会安装nltk包。但是，您需要下载额外的资源才能使用tidytext，请使用以下代码。

nltk.download("punkt")

实现的功能

• bind_tfidf
• unnest_tokens

示例

unnest_tokens

import pandas as pd

pd.set_option("display.max_rows", 6)

zen = """
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
"""

zen_split = zen.splitlines()


df = pd.DataFrame({
    "zen": zen_split,
    "line": list(range(len(zen_split)))
})

df

22行 × 2列

from tidytext import unnest_tokens

unnest_tokens(df, "word", "zen")

145行 × 2列

bind_tf_idf

from tidytext import unnest_tokens, bind_tf_idf 
from siuba import _, count, arrange

(df
  >> unnest_tokens(_.word, _.zen)
  >> count(_.line, _.word)
  >> bind_tf_idf(_.word, _.line, _.n)
  >> arrange(-_.tf_idf)
)

140行 × 6列