python - 拆分单元格中的文本并为标记创建额外的行

Question

假设我在 pandas 的 DataFrame 中有以下内容:

id  text
1   I am the first document and I am very happy.
2   Here is the second document and it likes playing tennis.
3   This is the third document and it looks very good today.

我想将每个 id 的文本拆分为 3 个单词的标记，所以我最终想要以下内容:

id  text
1   I am the
1   first document and
1   I am very
1   happy
2   Here is the
2   second document and
2   it likes playing
2   tennis
3   This is the
3   third document and
3   it looks very
3   good today

请记住，除了这两列之外，我的数据框可能还有其他列，它们应该以与上面的 id 相同的方式简单地复制到新的数据框。

最有效的方法是什么？

我认为我的问题的解决方案与此处给出的解决方案非常接近:Tokenise text and create more rows for each row in dataframe .

这也可能有帮助:Python: Split String every n word in smaller Strings .

Answer 1

你可以使用类似的东西:

def divide_chunks(l, n): 
    # looping till length l 
    for i in range(0, len(l), n):  
        yield l[i:i + n] 

---

然后使用 unnesting :

df['text_new']=df.text.apply(lambda x: list(divide_chunks(x.split(),3)))
df_new=unnesting(df,['text_new']).drop('text',1)
df_new.text_new=df_new.text_new.apply(' '.join)
print(df_new)

---

              text_new  id
0             I am the   1
0   first document and   1
0            I am very   1
0               happy.   1
1          Here is the   2
1  second document and   2
1     it likes playing   2
1              tennis.   2
2          This is the   3
2   third document and   3
2        it looks very   3
2          good today.   3

编辑:

m=(pd.DataFrame(df.text.apply(lambda x: list(divide_chunks(x.split(),3))).values.tolist())
.unstack().sort_index(level=1).apply(' '.join).reset_index(level=1))
m.columns=df.columns
print(m)

---

   id                 text
0   0             I am the
1   0   first document and
2   0            I am very
3   0               happy.
0   1          Here is the
1   1  second document and
2   1     it likes playing
3   1              tennis.
0   2          This is the
1   2   third document and
2   2        it looks very
3   2          good today.