A Package for text preprocessing
Project description
text-preprocessing
1. Text Cleaning
from nlp_preprocessing import clean
texts = ["Hi I am's nakdur"]
cleaned_texts = clean.clean_v1(texts)
2. Dataset Prepration
from nlp_preprocessing import dataset as ds
import pandas as pd
text = ['I am Test 1','I am Test 2']
label = ['A','B']
aspect = ['C','D']
data = pd.DataFrame({'text':text*5,'label':label*5,'aspect':aspect*5})
data
data_config = {
'data_class':'multi-label',
'x_columns':['text'],
'y_columns':['label','aspect'],
'one_hot_encoded_columns':[],
'label_encoded_columns':['label','aspect'],
'data':data,
'split_ratio':0.1
}
dataset = ds.Dataset(data_config)
train, test = dataset.get_train_test_data()
print(train['Y_train'],train['X_train'])
print(test['Y_test'],test['X_test'])
print(dataset.data_config)
3. Seq token generator
texts = ['I am Test 2', 'I am Test 1', 'I am Test 1', 'I am Test 1','I am Test 1', 'I am Test 2', 'I am Test 1', 'I am Test 2','I am Test 2']
tokens = seq_gen.get_word_sequences(texts)
print(tokens)
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