The whole world faced an extremely grave situation during the Covid-19 pandemic. In these difficult times, social media platforms like Twitter were vigorously used by people to share their emotions and experiences. For being able to identify these emotions we use sentiment analysis. Sentiment analysis is the process of identifying the sentiment of a text based on words used in it. Sentiment analysis mainly categories text based on three broad categories- Positive, Neutral and Negative. It helps us getting to know the emotion displayed by a user through their choice of words in the text written by them. This paper aims to check for the tweets of such people who used twitter to post about their experiences during Covid-19. It also thrives to check for the sentiments of the people through their tweets in order to acquire a generic sentiment analytical view of the people during Covid using Textblob technique. For the above mentioned procedure, we first collect data consisting of tweets related to Covid-19 and then we process them. After that we perform sentiment analysis of all the tweets available. We then filter the dataset based on the location to be India, and further perform sentiment analysis upon the filtered tweets. This helps us by providing a comparative perspective of the sentiments of the Indian audience with respect to rest of the world as a whole, including India.