การเข้ารหัสข้อความ

Feature Engineering สำหรับ Machine Learning ใน Python

Robert O'Callaghan

Director of Data Science, Ordergroove

การทำให้ข้อความเป็นมาตรฐาน

ตัวอย่างข้อความอิสระ:

Fellow-Citizens of the Senate and of the House of Representatives: AMONG the vicissitudes incident to life no event could have filled me with greater anxieties than that of which the notification was transmitted by your order, and received on the th day of the present month.

ชุดข้อมูล

print(speech_df.head())

                  Name           Inaugural Address    \ 
0    George Washington     First Inaugural Address
1    George Washington    Second Inaugural Address
2    John Adams                  Inaugural Address    
3    Thomas Jefferson      First Inaugural Address    
4    Thomas Jefferson     Second Inaugural Address

                        Date                               text
0    Thursday, April 30, 1789    Fellow-Citizens of the Sena...
1       Monday, March 4, 1793    Fellow Citizens: I AM again...
2     Saturday, March 4, 1797    WHEN it was first perceived...
3    Wednesday, March 4, 1801    Friends and Fellow-Citizens...
4       Monday, March 4, 1805    PROCEEDING, fellow-citizens...

การลบอักขระที่ไม่ต้องการ

[a-zA-Z]: ตัวอักษรทั้งหมด
[^a-zA-Z]: อักขระที่ไม่ใช่ตัวอักษร

speech_df['text'] = speech_df['text']\
                   .str.replace('[^a-zA-Z]', ' ')

การลบอักขระที่ไม่ต้องการ

ก่อน:

"Fellow-Citizens of the Senate and of the House of  
Representatives: AMONG the vicissitudes incident to   
life no event could have filled me with greater" ...

หลัง:

"Fellow Citizens of the Senate and of the House of  
Representatives AMONG the vicissitudes incident to   
life no event could have filled me with greater" ...

การทำให้ตัวพิมพ์เป็นมาตรฐาน

speech_df['text'] = speech_df['text'].str.lower()
print(speech_df['text'][0])

"fellow citizens of the senate and of the house of  
representatives among the vicissitudes incident to   
life no event could have filled me with greater"...

ความยาวของข้อความ

speech_df['char_cnt'] = speech_df['text'].str.len()
print(speech_df['char_cnt'].head())

0    1889  
1     806  
2    2408  
3    1495  
4    2465
Name: char_cnt, dtype: int64

จำนวนคำ

speech_df['word_cnt'] = 
    speech_df['text'].str.split()
speech_df['word_cnt'].head(1)

['fellow', 'citizens', 'of', 'the', 'senate', 'and',...

จำนวนคำ

speech_df['word_counts'] = 
    speech_df['text'].str.split().str.len()
print(speech_df['word_splits'].head())

0    1432
1     135
2    2323
3    1736
4    2169
Name: word_cnt, dtype: int64

ความยาวเฉลี่ยของคำ

speech_df['avg_word_len'] = 
         speech_df['char_cnt'] / speech_df['word_cnt']

มาฝึกกันเถอะ!

Feature Engineering สำหรับ Machine Learning ใน Python