Problem Statement: Create a bar chart or histogram to visualize the distribution of a categorical or continuous variable, such as the distribution of ages or genders in a population.
This project is designed to analyze social media data, focusing on sentiment patterns and message characteristics in a training dataset and a validation dataset. The analysis aims to understand public opinion and attitudes towards specific topics or entities. Below is a breakdown of the various steps and analyses carried out in this project:
- Installing and importing libraries (pandas, numpy, matplotlib, seaborn)
- Data Loading from CSV files: Training Data: Data used to build models and perform initial analyses. Validation Data: Data used to validate the outcomes and verify consistency.
- Initial Inspection to get overview of data using .head()
- Check for missing values and duplicates
- Data Cleaning (removing duplicate tweets)
- Data Visualization
Conclusion: These analyses and visualizations help to understand sentiment patterns, entity distribution, and message characteristics in social media data.