Question: You are given a DataFrame named df with a single column named raw_text, which contains sentences with potential noise such as null characters (\x00) and specific punctuation marks. The task is to perform word count on the cleaned text. Explain the necessary steps involved in cleaning and processing the text data before calculating the word count.
Note : If you have alternate solution let's discuss on that approach.
Sample Data:
complex_data = [
(" Hello, World! This is the first sentence--a. Another--sentence follows. ",),
("PySpark is awesome. It allows for distributed data processing. Exciting \x00 stuff!",),
("Let's analyze text data. We can use various transformations-and \x00 and actions in PySpark.",),
("Data processing is crucial for extracting valuable insights \x00 from large datasets. "
"Spark provides powerful tools for--this purpose.",),
]
Sample Output:
+-----------+-----+
|word |count|
+-----------+-----+
|a |1 |
|actions |1 |
|allows |1 |
|analyze |1 |
|and |2 |
|another |1 |
|awesome |1 |
|can |1 |
|crucial |1 |
|data |3 |
|datasets |1 |
|distributed|1 |
|exciting |1 |
|extracting |1 |
|first |1 |
|follows |1 |
|for |3 |
|from |1 |
|hello |1 |
|in |1 |
+-----------+-----+
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16 янв 2024
