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benthecoder/linkedin-visualizer

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benthecoder/linkedin-visualizer has 54 GitHub stars and 11 forks. GitHot measured 0 in 7 days. Last checked 2026-11-10 19:59 UTC. Last push 2022-10-06.

How these counts are measured

The missing feature in LinkedIn

What you can do

  • Total connections on LinkedIn
  • Where most of your connections work at
  • Who most of your connections are (what job title they hold)
  • Who you last connected with

Measured star growth

in 24h
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in 7 days
0
in 15 days
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in 1 month
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Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.

README.md

Original

Linkedin Connections Insights 🪄

Streamlit App

Get helpful statistics on your LinkedIn connection now!

Learn more about the project (Link)

Check out a walkthrough of the app of my LinkedIn connections (Link)

all

Features

This app tells you the information below

  • Total connections on LinkedIn
  • Where most of your connections work at
  • Who most of your connections are (what job title they hold)
  • Who you last connected with
  • Who you first connected with (send them a message!)
  • Bar chart of top companies and positions
  • Time series plot of your connections over time (find out when you had the most connections)
  • A graph/network of your connections (see your connections in a graph)
  • A wordcloud of your chat messages with your connections (new!)
  • Last but not least, a "who you can cold email" section that provides a list of emails of your connections (perks of LinkedIn connections!)

Use it now!

Word Cloud (New Feature!)

wordcloud

Run Locally

Clone the project

  git clone https://github.com/benthecoder/linkedin-visualizer.git

Go to the project directory

  cd linkedin-visualizer

Using Docker

Build an Image

docker build -t linkedin-visualizer:1.0 .

Run the Image

docker run -p 8501:8501 linkedin-visualizer:1.0

The app is now live on http://localhost:8501/

Using Conda

Create Conda environment

  conda create --name env_name python=3.8

Activate the environment

  conda activate env_name

Install requirements

  pip install -r requirements.txt

Run streamlit

  streamlit run app.py

Using Poetry

first make sure you have python 3.8

  poetry install
  poetry run streamlit run app.py

Contributing

Contributions are always welcome!

All connections

Here's what happens when I display all of the companies where my connections work at

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