Python Twitter Analyzer
CodingNomads final project using tweepy and sqlalchemy
This is the final project of the online Python course by CodingNomads.
Aim
The aim of the project is providing a series of statistics (e.g. average user count or most popular hours) on a set of Twitter tweets fetched using tweepy and stored in a database using sqlalchemy.
The results of said statistics can be previewed in the three .txt files in the main folder of the project:
- results_text_analysis.txt: stats on the text of the tweets, e.g. most frequently used symbols and longest word in the set.
- results_time_analysis.txt: stats on the time when the tweets were written, e.g. most popular hours or oldest tweet.
- results_users_analysis.txt: stats on the users, e.g. users with most followers or average followers/followed accounts ratio.
Description
The project consists of a series of scripts aimed at:
- Use tweepy to fetch a list of users who recently wrote a tweet in English containing the word "cyberpunk". This was done to push the set of tweets towards the gaming world.
- Use tweepy to fetch the last 20 tweets published by said users. Only tweets in English and that are not retweets of other tweets were accepted.
- Use sqlalchemy to store and retrieve all the data in a database.
- Use python scripts to analyze the collected data (one file where the results are printed and written in a .txt file and another with all the actual functions used).
- All data was stored in the database provided in the homonymous separate folder.