Covid19-Geographical-tweets-analysics

COVID19 Tweets 🌎 Geographical Deep Analysis
Visit My Kaggle Notebook Now

In this Analysics I used opensource kaggle Dataset Gatered through Twitter API

• https://github.com/gabrielpreda/covid-19-tweets
• https://www.kaggle.com/gpreda/covid19-tweets

and Word world-cities-datasets to compare and map and concat unique cities precent in this Dataset as twitter gave complete location for the users

• https://www.kaggle.com/viswanathanc/world-cities-datasets

---

About Me

I'm Safdar Khan a software Engineer who is working on AI and Datascience. If you face any problem you can contact with me.

File Structure

📦Covid19-tweets-analysics
 ┣ 📂code
 ┃ ┣ 📜covid19-tweets-geographical-deep-analysis.ipynb
 ┃ ┗ 📜reame.md
 ┣ 📂Images
 ┃ ┣ 📜10 Countries With Lest Tweets.png
 ┃ ┣ 📜Clicable Geo Map.png
 ┃ ┣ 📜Clickable Geo Map 2.png
 ┃ ┣ 📜Top 10 Countries With Most Tweets.png
 ┃ ┗ 📜Tweets Per country Limit By 15 With Gediant View.png
 ┣ 📂input
 ┃ ┣ 📂covid19-tweets
 ┃ ┃ ┗ 📜covid19_tweets.csv
 ┃ ┗ 📂world-cities-datasets
 ┃ ┃ ┗ 📜worldcities.csv
 ┣ 📜LICENSE
 ┗ 📜README.md

Usage of This Project

This Open source Project is for best visualization of Large Data Over Geograpgical Data, Mapping of 2 Datasets, Remove and Handle NaN/ Null Values and Get Unique Data Results. This Project is a demonstration of Covid-19 Dataset Task

Geo Graphical Analysics and Visualization of Covid-19 Tweets "source Kaggle"

Geo Map Showing 193 Locations over 77910 Valid Tweets of 179108 Data rows

Contects Covred in this Project

1. Data and library loading
2. Visualizing and Understading of Data
3. Preprocessing/Data Cleaning
4. Data Viualization
   • Valid Tweets
   • Top 10 Countries with Most Tweets
   • 10 Countries with Least Tweets
   • Top 15 Countries with Most Tweets Diffrent
   • Representation
   • Geo-MAP
5. Conclusion