How to transform some occurrences of words in a text in different time series to apply PDC with Python and R?

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I want to transform some occurrences of words into a text in different time series to apply Permutation Distribution Clustering with Python or R.



For example, I know how to make the scatter diagram for the characters in Sense and Sensibility by Jane Austen:



>>> import nltk
>>> word_list = ['Elinor', 'Marianne', 'Edward', 'Willoughby']
>>> text2.dispersion_plot (word_list)


And I know that there is a method called PDC and it could be relevant in regards to the grouping of time series. However, I do not know how to transform the occurrences of text into time series.



I'm not sure if I should haved asked my question here or on Stackoverflow.
I felt here was better to be better understood with this specific Mathematics object which is time series.




time-series




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    up vote
    0
    down vote

    favorite












    I want to transform some occurrences of words into a text in different time series to apply Permutation Distribution Clustering with Python or R.



    For example, I know how to make the scatter diagram for the characters in Sense and Sensibility by Jane Austen:



    >>> import nltk
    >>> word_list = ['Elinor', 'Marianne', 'Edward', 'Willoughby']
    >>> text2.dispersion_plot (word_list)


    And I know that there is a method called PDC and it could be relevant in regards to the grouping of time series. However, I do not know how to transform the occurrences of text into time series.



    I'm not sure if I should haved asked my question here or on Stackoverflow.
    I felt here was better to be better understood with this specific Mathematics object which is time series.




    time-series




    share|cite|improve this question





















      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      I want to transform some occurrences of words into a text in different time series to apply Permutation Distribution Clustering with Python or R.



      For example, I know how to make the scatter diagram for the characters in Sense and Sensibility by Jane Austen:



      >>> import nltk
      >>> word_list = ['Elinor', 'Marianne', 'Edward', 'Willoughby']
      >>> text2.dispersion_plot (word_list)


      And I know that there is a method called PDC and it could be relevant in regards to the grouping of time series. However, I do not know how to transform the occurrences of text into time series.



      I'm not sure if I should haved asked my question here or on Stackoverflow.
      I felt here was better to be better understood with this specific Mathematics object which is time series.




      time-series




      share|cite|improve this question











      I want to transform some occurrences of words into a text in different time series to apply Permutation Distribution Clustering with Python or R.



      For example, I know how to make the scatter diagram for the characters in Sense and Sensibility by Jane Austen:



      >>> import nltk
      >>> word_list = ['Elinor', 'Marianne', 'Edward', 'Willoughby']
      >>> text2.dispersion_plot (word_list)


      And I know that there is a method called PDC and it could be relevant in regards to the grouping of time series. However, I do not know how to transform the occurrences of text into time series.



      I'm not sure if I should haved asked my question here or on Stackoverflow.
      I felt here was better to be better understood with this specific Mathematics object which is time series.





      time-series





      share|cite|improve this question










      share|cite|improve this question




      share|cite|improve this question









      asked Jul 24 at 17:18









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