How to Scrape LinkedIn Connections for Network Analysis

How to Scrape LinkedIn Connections for Network Analysis Understanding your professional network can reveal hidden patterns — clusters of industry contacts, potential introductions, and career trajectory insights. In this tutorial, we'll build a Python tool that analyzes LinkedIn connection data for network analysis. The Approach: Export + Enrich LinkedIn lets you export your own connections as CSV via Settings > Data Privacy > Get a copy of your data. We'll parse that export and enrich it with publicly available data. Setting Up pip install requests pandas networkx matplotlib Sign up for ScraperAPI to handle request routing when enriching profile data at scale. Parsing Your LinkedIn Export import pandas as pd import networkx as nx import matplotlib.pyplot as plt def load_connections ( csv_path ): df = pd . read_csv ( csv_path , skiprows = 3 ) df . columns = [ c . strip () for c in df . columns ] df [ " Connected On " ] = pd . to_datetime ( df [ " Connected On " ]) return df df = load_c