def preparing_data(data):
data = data[['Level', 'Type_of_Job', 'Description']]
data = data[data.Level != 'Not Applicable']
data = md.cleaning_text_regular_exp(data, 'Description')
data = md.removing_stop_words(data)
#data_stemming = steamming(data_no_stop_words)
data = md.lemmatizing(data, "token_no_stop_words")
data_cleaned = md.data_categorization(data)
return (data_cleaned)
def preparing_data(data):
data = data[['Level', 'Type_of_Job', 'Description']]
data = data[data.Level != 'Not Applicable']
data_no_regular_expression = md.cleaning_text_regular_exp(
data, 'Description')
data_no_stop_words = md.removing_stop_words(data_no_regular_expression)
# data_stemming = steamming(data_no_stop_words)
data_lemmatizing = md.lemmatizing(data_no_stop_words, "Description")
data_categorical = md.data_categorization(data_lemmatizing)
return data_categorical
