Python import txt file pre-processing

Answer 1

The following are the general steps for Python to import txts:
1. ** Open and read files **:
- Use the `open()` function to open the file, and then read the contents with the `read()` or `readlines()` methods. For example:
```python
with open('file.txt', 'r') as file:
data = file.readlines()
```
2. ** Data Cleansing **:
- Remove unnecessary white space characters (such as line breaks, spaces), remove special symbols, and replace specific strings as needed. The sample code is as follows:
```python
data = (line.strip() for line in data)
data = (line.replace('', '') for line in data)
```
3. ** Word Separation and Standardisation (If the text processing involves the requirements of natural language processing)**:
- Break down the text into words or phrases, and possibly stem or stop word filtering, as well as converting to lower case. You need to import a related library, such as `nltk`.
```python
import nltk
from nltk.corpus import stopwords
nltk.download('stopwords')
stop_words = set(stopwords.words('english'))
data = (' '.join((word.lower() for word in line.split() if word.lower() not in stop_words)) for line in data)
```
4. ** Encode conversion (if non-Qianqian character processing is involved)**:
- Encodes non-ascil characters, such as converting text to UTF - 8 or other standard codes.
```python
data = (line.encode('utf - 8') for line in data)
```
5. ** Save the processed data (if necessary)**:
- If necessary, the preprocessed data can be saved to a new TMT file or converted to a format suitable for further analysis (such as dsv, Json, or DataFrame).
```python
with open('preprocessed_data.txt', 'w', encoding='utf - 8') as output_file:
output_file.writelines(data)
```
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