Created
October 14, 2021 07:17
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Visualize your LinkedIn connections
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#!/usr/bin/env python | |
# coding: utf-8 | |
# author: https://github.com/amansingh9097/ | |
import pandas as pd | |
import numpy as np | |
import plotly.express as px | |
# How to get your connection data? | |
# On LinkedIn, Go to "Me" --> "Settings & Privacy" --> "Get a Copy of your Data" | |
connections = pd.read_csv('Connections.csv') | |
connections = connections.loc[~connections['First Name'].isna()] | |
connections.loc[:, 'Company'] = connections.loc[:, 'Company'].fillna(value='Company: Unknown') | |
connections.loc[:, 'Position'] = connections.loc[:, 'Position'].fillna(value='Position: Unknown') | |
connections.loc[:, 'Email Address'] = connections.loc[:, 'Email Address'].fillna(value='eMail: Hidden') | |
connections.loc[:, 'Full Name'] = connections[['First Name','Last Name']].apply(lambda x: " ".join(x), axis=1) | |
# print(connections.head()) | |
# All connections | |
fig = px.treemap(connections, path=[px.Constant("My LinkedIn Network: {} connections".format(len(connections))), | |
'Company', 'Position', 'Full Name']) | |
fig.update_traces(root_color="lightskyblue") | |
fig.update_layout(margin = dict(t=50, l=25, r=25, b=25)) | |
fig.show() | |
# Top Positions from all connections | |
fig1 = px.treemap(connections, path=[px.Constant("My LinkedIn Network: {} Positions".format(len(connections['Position'].unique()))), | |
'Position']) | |
fig1.update_traces(root_color="skyblue") | |
fig1.update_layout(margin = dict(t=50, l=25, r=25, b=25)) | |
fig1.show() | |
# Current Role ---> #ToDO: change to your role specific position keywords | |
df = connections.loc[connections['Position'].str.contains('Data Scien')] | |
fig = px.treemap(df, path=[px.Constant("My Data-Scientist Network: {}".format(len(df))), 'Position', 'Company', 'Full Name']) | |
fig.update_traces(root_color="lightskyblue") | |
fig.update_layout(margin = dict(t=50, l=25, r=25, b=25)) | |
fig.show() | |
# Past Orgs ---> #ToDo: change to your orgs | |
df = connections.loc[connections['Company'].isin(['Clover Infotech','IBM','Tata Consultancy Services', | |
'3LOQ','Sunera Technologies','Amazon'])] | |
fig = px.treemap(df, path=[px.Constant("Connections from Orgs where I have worked in past: {}".format(len(df))), | |
'Company', 'Position', 'Full Name']) | |
fig.update_traces(root_color="lightskyblue") | |
fig.update_layout(margin = dict(t=50, l=25, r=25, b=25)) | |
fig.show() | |
# Leadership Roles | |
df = connections.loc[connections['Position'].str.contains('Founder|VP|CTO|CEO|COO|CFO|SVP|AVP|Director|Head of|Vice|President')] | |
fig = px.treemap(df, path=[px.Constant("Leaders/Founders/CEO/CTO/VP/AVP etc: {}".format(len(df))), | |
'Company','Position','Full Name']) | |
fig.update_traces(root_color="lightskyblue") | |
fig.update_layout(margin = dict(t=50, l=25, r=25, b=25)) | |
fig.show() |
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