https://github.com/justabhishek/us-election-2020

Python Visualization notebook using data from US Election 2020 Tweets ·
https://github.com/justabhishek/us-election-2020

data-science data-visualization kaggle-challenge matplotlib-pyplot nlp-machine-learning nltk-library plotly python3 us-elections

Last synced: about 11 hours ago
JSON representation

Python Visualization notebook using data from US Election 2020 Tweets ·

• Host: GitHub
• URL: https://github.com/justabhishek/us-election-2020
• Owner: JustAbhishek
• License: mit
• Created: 2020-11-18T18:17:51.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2020-11-18T18:18:45.000Z (almost 4 years ago)
• Last Synced: 2023-08-29T23:52:25.362Z (about 1 year ago)
• Topics: data-science, data-visualization, kaggle-challenge, matplotlib-pyplot, nlp-machine-learning, nltk-library, plotly, python3, us-elections
• Language: Jupyter Notebook
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# US-Election-2020

## Sentiment analysis on the tweets that is available for the two presidency candidates

### Columns of the dataset are as follows:

created_at: Date and time of tweet creation.

tweet_id: Unique ID of the tweet

tweet: Full tweet text

likes: Number of likes

retweet_count: Number of retweets

source: Utility used to post tweet

user_id: User ID of tweet creator

user_name: Username of tweet creator

user_screen_name: Screen name of tweet creator

user_description: Description of self by tweet creator

user_join_date: Join date of tweet creator

user_followers_count: Followers count on tweet creator

user_location: Location given on tweet creator's profile

lat: Latitude parsed from user_location

long: Longitude parsed from user_location

city: City parsed from user_location

country: Country parsed from user_location

state: State parsed from user_location

state_code: State code parsed from user_location

collected_at: Date and time tweet data was mined from twitter

More detail of the dataset can be found [here](https://www.kaggle.com/manchunhui/us-election-2020-tweets)

The Code does the pre-processing on the raw-data and performs Visualization using many python libraries.

## Check out the visualization and do upvote [here](https://www.kaggle.com/justabhishekprasad/us-election-2020)