Python is a general-purpose, high-level language used here for data analysis and machine learning, with reproducible workflows built in Jupyter Notebook. section 1.1 section 1.0
Review sentiment analysis
A telecom operator can collect product reviews, ratings, titles, authors, dates, bodies, and helpfulness votes, then clean review text and estimate whether customer sentiment is positive, negative, or neutral. Comparing star ratings with polarity can expose disagreements between numerical ratings and written feedback. section 7.15
#### Loading all the required libraries here
from lxml import html
import requests
import pandas as pd
from nltk.corpus import stopwords
from textblob import TextBlob
import matplotlib.pyplot as plt
import sys
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import sklearn
import scikitplot as skplt
import nltk
#to ignore warnings
import warnings
warnings.filterwarnings("ignore")
nltk.download('stopwords')
nltk.download('punkt')
nltk.download('wordnet')
The library setup shows the Python ecosystem used for scraping, tabular analysis, natural-language processing, visualization, and machine learning. section 7.15
