This repository contains data and scripts for conducting Exploratory Data Analysis (EDA) on client data and price data. The analysis aims to uncover patterns, trends, and insights that can inform business decisions.
- client_data.csv: This file contains information about clients, such as demographics, location, and other relevant details.
- price_data.csv: This file contains pricing information related to products or services.
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Run Jupyter Notebook
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Explore Data: Used code cells to load and explore the datasets. Checked for missing values, outliers, and data types. Visualized distributions and relationships between variables.
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Descriptive Statistics: Calculated summary statistics. Identified central tendencies and variability.
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Visualizations: Created visualizations to better understand data patterns. Utilized histograms, scatter plots, box plots, etc.
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Insights and Conclusions: Summarized key findings. Provided insights into client characteristics and pricing trends.
This EDA aims to provide a comprehensive understanding of the client and pricing data. Please refer to the Jupyter notebook for detailed analysis steps and results. Feel free to reach out for any clarifications or additional information.