Customer Shopping Behavior Analysis – Python - Pandas, SQL & Power BI Dashboard

@shivansh121

Hi, I have good working experience with Python Pandas PostgreSQL PowerBI Data Analysis and Scraping JavaScript Machine Learning Message me here & LET'S GET DISCUSS MORE. Regards, Shalu

@belarjsoufiane20

Hi, I hope you’re doing great With 7+ years of experience in data analytics, Python automation, SQL, and dashboard development, I can deliver a complete end-to-end retail analytics solution including data cleaning and feature engineering with Pandas, PostgreSQL analysis with optimized SQL queries, and a professional interactive Power BI dashboard with dynamic filters and clear business insights. I am available to start immediately and am Looking forward to collaborating with you.

@DevDataAnalyst

Hi there! I’ve spent the last 10+ years helping businesses make sense of their data — turning numbers and reports into clear, visual stories that drive smarter decisions. My expertise includes Power BI, Tableau (Desktop & Server), R, SQL Server, and KNIME for data prep and automation. Whether it’s building a simple KPI dashboard or a full-scale analytics solution, I focus on making your data work for you — easy to understand, easy to use, and built around your goals. If you’re looking for someone who blends technical skill with a business mindset, let’s connect and discuss how I can help bring your data to life.

@KarthikTechCon

Hi, I’m Karthik, a Data Analytics & BI specialist with 15+ years of experience in Python, SQL, Power BI, and business intelligence solutions for retail and customer analytics. I can deliver a complete end-to-end customer shopping behavior analysis project with clean, optimized, and well-documented outputs. ✔ Python/Pandas Data Cleaning * Handle missing values & preprocessing * Feature engineering & age-group creation * Clean reusable Python scripts * PostgreSQL database integration ✔ PostgreSQL Analysis * Revenue analysis by gender & age group * Customer segmentation (New/Returning/Loyal) * Product/category performance insights * Subscription vs non-subscription comparison * Discount impact & spending behavior analysis ✔ Interactive Power BI Dashboard * Dynamic KPI visuals & trend analysis * Filters for category, gender, season & subscription * Professional dashboard design for easy insights Deliverables: * Python scripts * SQL query files * Power BI .pbix dashboard * Summary insights report * Documentation for execution/setup Strong experience in retail analytics, ETL pipelines, dashboarding, and data-driven business reporting. Regards, Karthik

@mrresearcher99

Hello, I can help you complete the full retail data analysis project end-to-end, including Python data cleaning, PostgreSQL analysis, and an interactive Power BI dashboard. Recommended Tech Stack • Python (Pandas, NumPy, SQLAlchemy) • PostgreSQL • Power BI • Jupyter Notebook or standalone scripts I also focus on: • Clean documentation • Readable code structure • Accurate business insights • Professional dashboard presentation I would be happy to review the dataset structure and begin immediately. Best Regards

@atech20102018

Hi, I can help you complete the full customer shopping behavior analysis workflow — from data cleaning and SQL analysis to an interactive Power BI dashboard with actionable insights. Your requirements are well-structured, and I can assist with: • Data cleaning & preprocessing using Python/Pandas • Feature engineering and segmentation analysis • PostgreSQL integration & optimized SQL queries • Revenue, subscription, and discount analysis • Interactive Power BI dashboard creation • Summary insights/report generation I have experience working with analytics dashboards, backend data handling, and structured reporting workflows, with a focus on clean, maintainable deliverables. You will receive: • Clean Python scripts • SQL query files/results • Power BI dashboard (.pbix) • Summary findings documentation I can start immediately and ensure the analysis is presented clearly with meaningful business insights rather than just raw visualizations. Looking forward to discussing the dataset and expected dashboard structure further.

@sudhir0112

Hi! I'm Sudhir Jain, a data analyst with expertise in Python (Pandas), SQL (PostgreSQL), and Power BI — exactly the stack you need for this project. Here's my approach for your 3,900-record retail dataset: 1. Data Cleaning (Python/Pandas): I'll handle missing Review Rating values using median imputation, rename columns for consistency, create age-group bins, and engineer new features (e.g., spend per visit, discount sensitivity). I'll then push the clean data into your PostgreSQL database. 2. SQL Analysis: I'll write optimized queries for revenue by gender/age group, customer segmentation (New/Returning/Loyal based on purchase frequency), top-rated products by category, subscription vs. non-subscription spending, and discount impact analysis. 3. Power BI Dashboard: I'll build an interactive dashboard with slicers for category, gender, season, and subscription status — delivering clear visual insights that are easy to explore. Deliverables: clean, commented Python script, SQL queries with output screenshots, a fully interactive Power BI .pbix file, and a concise findings summary. I have hands-on experience delivering similar BI projects for pharma and retail clients at Axtria using MicroStrategy and QlikView. I deliver clean, well-documented work on time. Can we start immediately? Happy to clarify any requirements!

@sonika1419

**DO NOT PAY ME UNTIL I COMPLETE! :)** Hello my valuable client :) My profile is new over here but I have 7 years of experience in this field. I have completely understood about your project. Also I will provide you free maintenance on your project for 1 year after project completion. I can definitely complete this in your timeframe. Give me one chance to prove myself. Hit the chat button to get started. If you will not like my work then you dont need to pay me any money so dont worry and have faith in me :) I am eagerly waiting for your message.

@Srashtasoft

A Warm Hello! I’d be happy to help you turn your retail dataset into a complete end-to-end analytics project using Python, PostgreSQL, and Power BI. With experience in data processing, dashboard development, and business analytics, I can deliver a clean and well-structured solution that provides actionable insights from your 3,900 customer purchase records. Scope of work: Data cleaning and preprocessing using Python/Pandas Handling missing Review Rating values and feature engineering PostgreSQL integration with optimized SQL analysis queries Customer segmentation and spending behavior analysis Revenue, discount, subscription, and product performance insights Interactive Power BI dashboard with dynamic filters and visuals Final delivery including Python scripts, SQL files, PBIX dashboard, and summary report I’ll ensure the code is clean, modular, and easy to maintain for future analysis or dashboard expansion. I also have strong experience building business-focused dashboards with clear KPIs and drill-down insights. A few quick questions: Do you already have the PostgreSQL schema/database ready? Would you like the dashboard designed for executive-level insights or detailed operational analysis? Let's discuss it more in chat. Let's set up a quick call to discuss things better. Best Regards, Jemin Sagar

@dushyant317

We can deliver the complete retail analytics workflow end-to-end — Python/Pandas data cleaning & feature engineering, PostgreSQL analysis queries, and a professional interactive Power BI dashboard with segmentation, revenue, subscription, and discount insights

@rishi9343

I can help you complete this quickly and cleanly, handling missing values in the Review Rating column, creating age groups, and engineering new features using Python and Pandas, then performing SQL analysis in PostgreSQL to segment customers and compare spending, and finally building an interactive Power BI dashboard with filters, delivering a clean Python script, SQL queries, and a Power BI.

@canturiasabbey

Hello. Your brief is clear, and I see that your requirement centers on transforming raw retail data into structured, decision-ready business intelligence through Python/Pandas cleaning, PostgreSQL analysis, and Power BI visualization. As a former daily English newspaper editor turned data analyst and visualization strategist, I combine analytical precision, data storytelling, SQL interpretation, and dashboard design to produce clear, actionable insights from customer behavior datasets. I will clean and structure your 3,900-record dataset, handle missing review ratings, engineer new features, create age-group segmentation, and connect the processed data to PostgreSQL for advanced SQL analysis covering revenue patterns, customer segmentation, product performance, subscription behavior, and discount impact. I will then build an interactive Power BI dashboard with filters by category, gender, season, and subscription status. You will receive clean Python scripts, optimized SQL queries with results, a fully functional Power BI .pbix dashboard, and a concise summary report highlighting key business findings and customer trends. If clarity, analytical depth, and executive-ready visualization matter, let us begin immediately.

@ziedb4

Hi , ​I’ve reviewed your project details regarding the retail dataset analysis. The workflow you’ve outlined—from data cleaning in Pandas to SQL querying and Power BI visualization—is exactly where my expertise lies. ​How I will handle this project: ​Data Preparation: I’ll use Python/Pandas to handle the missing values in 'Review Rating' and perform the necessary feature engineering (like Age Grouping) to ensure the data is ready for deep analysis. ​Database Integration: I will set up the pipeline to push the cleaned data into PostgreSQL, ensuring the schema is optimized for your reporting needs. ​SQL Insights: I’ll write optimized queries to extract the specific metrics you requested, such as revenue by demographics, customer segmentation, and discount impact analysis. ​Power BI Dashboard: I’ll build a clean, interactive dashboard with all the required filters (Season, Category, Gender, etc.) to give you a clear view of your KPIs. ​Deliverables: You will receive the full Python script, the SQL documentation, and the .pbix file, along with a concise summary of the key findings. ​I’m ready to start immediately and can ensure clean, well-documented code throughout the process. Looking forward to discussing this further with you.

@snath88

Hi, Drop me a message — I'll share a quick prototype based on what I understood. If it matches your expectations, we can move forward. Thanks!

@mubashir021

I am excited to help you analyze your retail dataset and deliver actionable insights that drive business decisions. With extensive experience in Python, Pandas, SQL, and Power BI, I will ensure a thorough and efficient analysis of your customer shopping behavior. My approach will start with meticulous data cleaning to address missing values and create meaningful features. I will then perform SQL analysis to derive key metrics such as revenue segmentation, customer classifications, and product performance. Finally, I will build an interactive Power BI dashboard to visualize insights effectively, allowing for dynamic filtering by various categories. I will provide a clean Python script, SQL queries with their results, and a concise summary report of findings to accompany the dashboard. I anticipate completing this project in 14 days, ensuring ample time for revisions and quality assurance. Let's collaborate to turn your data into valuable insights.

@serviceaxisgroup

Hi, I can help with a complete analysis and Power BI dashboard that explains revenue, segments, and discount impact from your 3,900 retail records. I’ll start by profiling and cleaning the Review Rating missing values in Python/Pandas, engineering age groups/features, and setting up the PostgreSQL connection. I’ll then validate each step with row counts, reconciliation checks between Pandas and SQL, and a clear script so results are easy to reproduce. Do you already have the PostgreSQL schema/table name for the 18 columns? Also, should segmentation be defined purely from purchase history status fields or from spend/frequency thresholds? If you share the table details, we can get started right away.

@ravikumarsingh1

I can complete the full retail customer shopping behavior analysis project including Python/Pandas cleaning, PostgreSQL analysis, and an interactive Power BI dashboard. I reviewed the dataset/project scope including: • 3,900 customer records • Missing Review Rating handling • Feature engineering and age grouping • PostgreSQL integration • Revenue, segmentation, discount, and subscription analysis • Power BI dashboard requirements I have experience with: • Python (Pandas, NumPy) • PostgreSQL and SQL analytics • Power BI dashboard development • Data cleaning and feature engineering • KPI and customer-segmentation reporting I can deliver: • Clean and documented Python script • PostgreSQL queries with outputs • Interactive Power BI (.pbix) dashboard • Short business-insight summary report Dashboard features can include: • Revenue analysis • Customer segmentation • Product/category insights • Subscription vs non-subscription comparisons • Discount impact analysis • Interactive filters and slicers My approach focuses on: Clean and reproducible analysis Proper SQL structuring Interactive executive-friendly dashboard design Actionable business insights I can also help optimize the Power BI model for performance and visual clarity. Ready to start immediately and discuss timeline/deliverables further.

@saadacious

I've worked with retail customer datasets like this before — and I can tell you exactly how I'd handle yours. Your Review Rating column likely has random or systematic missingness. Before I just fill it with a mean, I'll check if the missing values correlate with product category or subscription status — that tells me whether to impute by group median or flag it as a separate analytical signal. That's the difference between cleaning data and understanding it. Here's precisely what you're getting: Python/Pandas script — column renaming, age group bins (18–25, 26–35, 36–50, 50+), engineered features like spend-per-visit and discount sensitivity score, and a clean SQLAlchemy connection pushing the final frame directly into your PostgreSQL instance. SQL queries — I'll write all five analyses you listed plus one you didn't ask for: cohort overlap between high-rating customers and subscription holders. That's usually where the most interesting segment hides in retail data. Power BI dashboard — slicers for category, gender, season, and subscription status wired to a star schema model (not flat table), so your filters are fast even as the dataset grows. Revenue KPIs, customer segment donut, top-10 products by rating, discount impact bar — all on one canvas. One question: is the PostgreSQL database already set up, or do I need to include schema creation and table loading in the script? Ready to start today.

@bizoolssoftware

As an experienced Python developer skilled in Pandas and SQL, I am confident that I can provide a comprehensive analysis of your retail dataset that matches all your project requirements. My proficiency in Python and Pandas will help me efficiently handle missing values, rename columns, create age groups, and engineer new features—all the necessary steps for thorough data cleaning. Additionally, my skills in SQL will be pivotal in deriving valuable insights for your business such as revenue by gender and age group, customer segmentation, top products analysis, and much more. To emphasize further on why I’m a good fit for this job: I am committed to delivering reliable and efficient solutions on-time ensuring quality and scalability. This aligns perfectly with your requirement of clean deliverables: a Python script that adheres to best practices, SQL queries with clear results that add value to your business understanding and finally a Power BI Dashboard with a short report summarizing my findings. My aim is not just limited to providing a satisfactory data analyses; I’m focused on delivering powerful insights that can drive long-term strategy and profit making for your business. Rest assured; I will dedicate all the skills, domain knowledge and meticulous approach needed for this task to ensure your utmost satisfaction.