python - 如何在 python 中编辑 .csv 以进行 NLP

Question

你好，我不是很熟悉编程，在研究我的任务时发现了 Stackoverflow。我想对这样的 .csv 文件进行自然语言处理，该文件大约有 15.000 行

    ID | Title        | Body
    ----------------------------------------
    1  | Who is Jack? | Jack is a teacher... 
    2  | Who is Sam?  | Sam is a dog.... 
    3  | Who is Sarah?| Sarah is a doctor...
    4  | Who is Amy?  | Amy is a wrestler... 

我想读取 .csv 文件并执行一些基本的 NLP 操作，然后将结果写回新文件或同一文件中。经过一些研究，python 和 nltk seams 成为我需要的技术。 (我希望那是对的)。标记化后，我希望我的 .csv 文件看起来像这样

    ID | Title                 | Body
    -----------------------------------------------------------
    1  | "Who" "is" "Jack" "?" | "Jack" "is" "a" "teacher"... 
    2  | "Who" "is" "Sam" "?"  | "Sam" "is" "a" "dog".... 
    3  | "Who" "is" "Sarah" "?"| "Sarah" "is" "a" "doctor"...
    4  | "Who" "is" "Amy" "?"  | "Amy" "is" "a" "wrestler"... 

经过一天的研究和拼凑，我所取得的成就如下所示

    ID | Title                 | Body
    ----------------------------------------------------------
    1  | "Who" "is" "Jack" "?" | "Jack" "is" "a" "teacher"... 
    2  | "Who" "is" "Sam" "?"  | "Jack" "is" "a" "teacher"...
    3  | "Who" "is" "Sarah" "?"| "Jack" "is" "a" "teacher"...
    4  | "Who" "is" "Amy" "?"  | "Jack" "is" "a" "teacher"... 

我的第一个想法是读取 .csv 中的特定单元格，进行操作并将其写回同一个单元格。而不是以某种方式在所有行上自动执行此操作。显然我设法读取了一个单元格并将其标记化。但我无法设法将它写回那个特定的单元格。而且我远离“自动对所有行执行此操作”。如果可能的话，我将不胜感激。

我的代码:

    import csv
    from nltk.tokenize import word_tokenize 

    ############Read CSV File######################
    ########## ID , Title, Body#################### 

    line_number = 1 #line to read (need some kind of loop here)
    column_number = 2 # column to read (need some kind of loop here)
    with open('test10in.csv', 'rb') as f:
        reader = csv.reader(f)
        reader = list(reader)
        text = reader[line_number][column_number] 


        stringtext = ''.join(text) #tokenizing just work on strings 
        tokenizedtext = (word_tokenize(stringtext))
        print(tokenizedtext)

    #############Write back in same cell in new CSV File######

    with open('test11out.csv', 'wb') as g:
        writer = csv.writer(g)
        for row in reader:
            row[2] = tokenizedtext
            writer.writerow(row)

我希望我问的问题是正确的，有人可以帮助我。

Answer 1

pandas 库将使所有这一切变得更加容易。

pd.read_csv() 将更容易地处理输入，您可以使用 pd.DataFrame.apply() 将相同的函数应用于列

下面是一个简单示例，说明您希望的关键部分如何工作。在 .applymap() 方法中，您可以将我的 lambda 函数替换为 word_tokenize() 以将其应用于所有元素。

In [58]: import pandas as pd

In [59]: pd.read_csv("test.csv")
Out[59]:
                     0                          1
0  wrestler Amy dog is         teacher dog dog is
1      is wrestler ? ?  Sarah doctor teacher Jack
2        a ? Sam Sarah           is dog Sam Sarah
3       Amy a a doctor             Amy a Amy Jack

In [60]: df = pd.read_csv("test.csv")

In [61]: df.applymap(lambda x: x.split())
Out[61]:
                          0                               1
0  [wrestler, Amy, dog, is]         [teacher, dog, dog, is]
1      [is, wrestler, ?, ?]  [Sarah, doctor, teacher, Jack]
2        [a, ?, Sam, Sarah]           [is, dog, Sam, Sarah]
3       [Amy, a, a, doctor]             [Amy, a, Amy, Jack]

另见:http://pandas.pydata.org/pandas-docs/stable/basics.html#row-or-column-wise-function-application