High level text features
Once the text has been cleaned and standardized you can begin creating features from the data. The most fundamental information you can calculate about free form text is its size, such as its length and number of words. In this exercise (and the rest of this chapter), you will focus on the cleaned/transformed text column (text_clean
) you created in the last exercise.
Este exercício faz parte do curso
Feature Engineering for Machine Learning in Python
Instruções do exercício
- Record the character length of each speech in the
char_count
column. - Record the word count of each speech in the
word_count
column. - Record the average word length of each speech in the
avg_word_length
column.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Find the length of each text
speech_df['char_cnt'] = speech_df['text_clean'].____
# Count the number of words in each text
speech_df['word_cnt'] = speech_df['text_clean'].____
# Find the average length of word
speech_df['avg_word_length'] = ____ / ____
# Print the first 5 rows of these columns
print(speech_df[['text_clean', 'char_cnt', 'word_cnt', 'avg_word_length']])