techykajal

new1 = Trump_reviews.groupby('Expression Label').count()
x = list(new1['Sentiment_Polarity'])
y = list(new1.index)
tuple_list = list(zip(x,y))

df = pd.DataFrame(tuple_list, columns=['x','y'])

df['color'] = 'blue'
df['color'][1] = 'red'
df['color'][2] = 'green'

techykajal

Biden_reviews['Expression Label'] = np.where(Biden_reviews['Sentiment_Polarity']>0,'positive', 'negative')
Biden_reviews['Expression Label'][Biden_reviews.Sentiment_Polarity ==0] = "Neutral"
Biden_reviews.tail()

techykajal

Trump_reviews['Expression Label'] = np.where(Trump_reviews['Sentiment_Polarity']>0,'positive', 'negative')
Trump_reviews['Expression Label'][Trump_reviews.Sentiment_Polarity ==0] = "Neutral"
Trump_reviews.tail()

techykajal

def find_pol(review):
    return TextBlob(review).sentiment.polarity

Biden_reviews['Sentiment_Polarity'] = Biden_reviews['text'].apply(find_pol)
Biden_reviews.tail()

techykajal

def find_pol(review):
    return TextBlob(review).sentiment.polarity

Trump_reviews['Sentiment_Polarity'] = Trump_reviews['text'].apply(find_pol)
Trump_reviews.tail()

techykajal

import csv
import tweepy
import ssl

# Oauth keys
consumer_key = "QN3CzI2gScYvDsrhhaL2SRbOPrC"
consumer_secret = "AQU3NwlOqUb1aKxgy0Nk22H5k8jjj0tYJ4nlFRLFZQJCA07TLCJMm"
access_token = "969527167221563392-35WKxHqmuLkkqfe1zqQbmSN276vZTFAbz"
access_token_secret = "wplE6EPMtyqNRESaBV175jRzU5ffgq934nX3h2dNQ7rnzarg"

techykajal

text_blob_object1 = TextBlob(Trump_reviews['text'][10])
print(text_blob_object1.sentiment)
text_blob_object2 = TextBlob(Biden_reviews['text'][500])
print(text_blob_object2.sentiment)

techykajal

# Install Libraries
pip install -U textblob
pip install pandas
pip nstall numpy
pip install plotly
pip install seaborn
pip install matplotlib
pip install wordcloud

# Import Libraries

techykajal

import urllib.request,sys,time
from bs4 import BeautifulSoup
import requests
import pandas as pd

pagesToGet= 1

upperframe=[]  
for page in range(1,pagesToGet+1):
    print('processing page :', page)