Mindinventory/Bank-Marketing-Data-Visualisation
This repository contains Python code for visualizing the Bank Marketing dataset using various data visualization techniques. The dataset is loaded from a CSV file, and both numerical and categorical features are explored using popular libraries such as Pandas, Matplotlib, Seaborn, and Plotly.
This project helps bank marketing managers understand the effectiveness of their campaigns and identify customer segments. It takes raw bank marketing campaign data (like customer demographics, contact history, and campaign outcomes) as a CSV file and produces a suite of visual charts, graphs, and plots. These visuals highlight trends, distributions, and relationships between customer attributes and term deposit subscriptions, allowing marketing teams to gain insights into customer behavior.
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Use this if you are a bank marketing manager or data analyst looking to quickly visualize and explore your campaign data to understand customer demographics, campaign performance, and factors influencing term deposit subscriptions.
Not ideal if you need an interactive dashboard for real-time campaign monitoring or a predictive model for customer churn, as this focuses solely on static data visualization.
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Jan 11, 2024
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