https://github.com/ronylpatil/whatsapp-group-chat-analysis

This project is totally based on data analysis where our college official Whatsapp group is used to extract useful information from the chat. Some of the useful extracted features are most active members of the group, most active day of the week, top-10 media contributors in the Group, and many more...
https://github.com/ronylpatil/whatsapp-group-chat-analysis

data-analysis data-preprocessing data-wrangling feature-engineering

Last synced: 9 days ago
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This project is totally based on data analysis where our college official Whatsapp group is used to extract useful information from the chat. Some of the useful extracted features are most active members of the group, most active day of the week, top-10 media contributors in the Group, and many more...

• Host: GitHub
• URL: https://github.com/ronylpatil/whatsapp-group-chat-analysis
• Owner: ronylpatil
• Created: 2021-02-08T03:59:25.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2022-12-21T03:04:00.000Z (about 2 years ago)
• Last Synced: 2023-02-27T04:22:01.645Z (almost 2 years ago)
• Topics: data-analysis, data-preprocessing, data-wrangling, feature-engineering
• Language: Jupyter Notebook
• Homepage:
• Size: 6.44 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Whatsapp Group Chat Analyzer

##### Profile Visits :

![Visitors](https://visitor-badge.glitch.me/badge?page_id=ronylpatil.Whatapp-Group-Chat-Analysis&left_color=lightgrey&right_color=brightgreen&left_text=visitors) 



  



These project is totally based on __Data Analysis__, where our college official __Whatsapp Group Chat__ is used to extract useful insights from the chat. A lot of __preprocessing__ and __feature engineering__ preformed on data & finally extracted __15 most useful insight's__ and pattern's from the chat.

The extracted features are : 

*  Visual Representation of most active member's of Group.

*  Mostly active day of week.

*  Top-10 visual media contributor of Group.

*  Top-10 Author who uses max no. of words in there messages.

*  Top-10 Authors who has shared max no. of links in Group.

*  Time whenever Group having high traffic.

*  Analysis of most suitable time slot of a day.

*  Word Cloud of top-5 highly active member's of Group.

*  Date on which Group was highly active.

*  Analysis of no. of messages using Time Series Plot.

*  Mostly active Month.

*  Analysis of mostly active month using Line Plot.

*  Analysis of Emojies used by users.

*  Mostly active year whenever max. no. of messages sent.

*  Analysis of most active Day and Time in the group.

Libraries Used : 

* Plotly Express.

* Seaborn.

* Matplotlib.

* Pandas 

Sample Output : 



  





  





  





  



© 2021 Ronil Patil


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