"Sentiment_Analysis_of_Covid19_Tweets_1-1.ipynb," contains a Jupyter Notebook with code cells that perform various tasks related to sentiment analysis of COVID-19 tweets. Here is a summary of the key components found in the notebook:
Exploratory Data Analysis (EDA): The notebook imports the necessary Python packages for data analysis, such as pandas for data manipulation. It includes code snippets for data visualization using matplotlib and seaborn libraries.
There are commands to suppress warnings during data analysis.
Data Loading: The notebook loads a dataset named "covid19_tweets.csv" using pandas to analyze COVID-19 related tweets.
Data Preview: The notebook displays a preview of the loaded dataset, showing the first few rows of data.
Data Columns and Types: It checks and displays the columns present in the dataset, providing an overview of the data structure. The notebook shows the data types of each column, including object (text), int64 (integer), and bool (boolean).
Twitter Sources: The notebook lists various sources from which the tweets were collected, including Twitter for iPhone, Twitter for Android, Twitter Web App, and many others. The notebook seems to focus on analyzing COVID-19 related tweets, exploring user information, tweet content, and sources of the tweets. It sets the groundwork for sentiment analysis by loading and examining the dataset, preparing it for further analysis and insights extraction
data sets link; https://www.kaggle.com/datasets/gpreda/covid19-tweets