https://github.com/cronn/lin-in
Simple Data Science for LinkedIn
https://github.com/cronn/lin-in
data-science linkedin streamlit
Last synced: about 1 month ago
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Simple Data Science for LinkedIn
- Host: GitHub
- URL: https://github.com/cronn/lin-in
- Owner: cronn
- License: gpl-3.0
- Created: 2024-04-22T11:01:21.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-13T06:23:26.000Z (about 2 years ago)
- Last Synced: 2025-02-28T19:39:51.354Z (over 1 year ago)
- Topics: data-science, linkedin, streamlit
- Language: Python
- Homepage: https://lin-in.streamlit.app/
- Size: 189 KB
- Stars: 0
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# LIN-IN - LinkedIn Insights
Analyse your LinkedIn connections and messages with some simple data science.
[](https://lin-in.streamlit.app)
Caution: this is a quick and dirty simple toy project. No warranty!
## Features
Upload your LinkedIn data export to receive information about:
- Overview of all your connections
- Companies and positions of your connections
- How your profile developed over time
- A graph of your company network
- A graph of positions within your network
- Overview of all your messages
https://github.com/cronn/lin-in/assets/4086468/6f6c8f94-ddf2-4f21-91eb-913e010bce29
## Run Locally
Clone the project
```bash
git clone https://github.com/benthecoder/linkedin-visualizer.git
```
Go to the project directory
```bash
cd lin-in
```
### Using Docker
Build an Image
```bash
docker build -t lin-in:0.0.1 .
```
Run the Image
```bash
docker run -p 8501:8501 lin-in:0.0.1
```
The app is now live on http://localhost:8501/
### Using Conda
Create Conda environment
```bash
conda create --name env_name python=3.12.1
```
Activate the environment
```bash
conda activate env_name
```
Install requirements
```bash
pip install -r requirements.txt
```
Run streamlit
```bash
streamlit run app.py
```
### Using Poetry
first make sure you have python 3.12.1
```bash
poetry install
```
```bash
poetry run streamlit run app.py
```
## Credits
This is an extended fork of [Linkedin Visualizer](https://github.com/benthecoder/linkedin-visualizer), adding several new functions, extensions, dependency updates (python 12+) and further cleaning. Other sources used:
- [Linkedin Analysis](https://github.com/tavishcode/linkedin_analysis/tree/master)
- [Linkedin Network Visualization](https://github.com/Thanh-To/linkedin-network-visualization)
- [Plotly Docs](https://plotly.com/python/treemaps/)