https://github.com/swapnil-jain/whatsapp-chat-statistics

Web Application showing common statistics, graphs and various charts about the uploaded Whatsapp chat.
https://github.com/swapnil-jain/whatsapp-chat-statistics

data-analytics data-science data-visualization heroku-deployment streamlit whatsapp

Last synced: 3 days ago
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Web Application showing common statistics, graphs and various charts about the uploaded Whatsapp chat.

• Host: GitHub
• URL: https://github.com/swapnil-jain/whatsapp-chat-statistics
• Owner: Swapnil-jain
• Created: 2022-09-03T07:07:56.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2023-04-14T07:06:28.000Z (over 1 year ago)
• Last Synced: 2023-09-05T15:13:50.402Z (about 1 year ago)
• Topics: data-analytics, data-science, data-visualization, heroku-deployment, streamlit, whatsapp
• Language: Python
• Homepage: https://whatsapp-chat-analysis.onrender.com/
• Size: 33.2 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# WhatsApp Chat Analysis

Upload your WhatsApp chats and the tool analyses them for you. Works for both group chats and individual chats. None of the chats are stored, and your data is 100% secured.

It is live at: https://whatsapp-chat-analysis.onrender.com/

## What it shows ?

1. Top statistics including total messages, total links shared, total words etc.

2. Monthly and Daily Timeline graphs.

3. Monthly and Daily Activity map including Heat map.

4. Wordcloud and top word count.

5. Emoji analysis and pie chart.









## How to use?

1. Change your phone time to 24 hours. Close Whatsapp and open it again.

2. On any WhatAapp chat, click "Export chat".

3. Select "Without Media".

4. Upload the text file generated in the website.

5. Choose either Overall Analysis or any particular user.

## Known issues:

1. Works only for 24 hours time format for now. Will soon make it work for any format.

2. Emojis are sometimes not visible in the pie-chart, due to incompatible support from matplotlib for those emojis.

### Tech stack used:

Python, Streamlit, Render, Lottie and data analysis libraries like numpy, pandas, matplotlib etc.