This repository features a comprehensive end-to-end project showcasing data analysis and interactive dashboard creation using Python. The project leverages Pandas for data manipulation and Streamlit for developing an engaging and dynamic web application.
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Data Analysis: In-depth exploration of a customer dataset using Pandas. This includes data cleaning, statistical analysis, and visualization.
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Interactive Dashboard: A user-friendly Streamlit application that allows users to interactively explore data insights through various visualizations.
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Graphs and Plots: Includes diverse visualizations such as histograms, bar charts, pie charts, and more to effectively communicate data insights.
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Age Distribution: Visualizes the distribution of ages in the dataset.
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Average Total Spend by Subscription Type: Displays average spending categorized by subscription types.
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Gender Distribution: Shows the proportion of different genders in the dataset.
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Total Spend Distribution by Contract Length: Provides insights into spending patterns based on contract length.
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Churn Rate by Gender: Analyzes churn rates categorized by gender.
Python: Main programming language for data analysis and application development.
Pandas: Used for data manipulation and analysis.
Matplotlib: For creating static, animated, and interactive visualizations in Python.
Streamlit: Framework for building interactive web applications with Python.