rekhadivay / Python_Amazon_Sales_Project

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Python_Amazon_Sales_Project

Overview:

This project involves the analysis of sales data from Amazon, aiming to derive meaningful insights that can contribute to better decision-making and business optimization. The data is explored and visualized using various techniques and tools, including Python libraries such as Pandas, Matplotlib, Seaborn, and others.

Project Structure:

1. Data Import and Cleaning:

The dataset is imported using Pandas, and potential issues like missing values and data types are addressed.

Unnecessary columns are dropped, and specific data types are adjusted for better analysis.

2. Exploratory Data Analysis (EDA):

The exploratory data analysis involves various visualizations and statistical summaries to understand the distribution and relationships within the dataset.

Grouping data is done using groupby to summarize and visualize information based on specific columns.

Other visualizations include pie charts, histograms, barplot and scatter plots to explore different aspects of the data.

3. Business Insights:

The project aims to provide actionable insights for business improvement. For instance, understanding the distribution of orders across different states, analyzing the fulfillment process, and identifying key product categories.

4. Conclusion:

The project concludes with a summary of key findings, providing insights into customer demographics, order fulfillment, product demand, and other relevant aspects.

5. Future Steps:

Future steps may involve more in-depth analyses, predictive modeling, or additional data sources to enhance the scope and accuracy of business insights.

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