I can help you conduct data analysis and reporting using Python
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Project Details
Why Hire Me?
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I offer Python-based data analysis backed by 7+ years of industry and academic experience. Whether you're working on business data, research projects, or exploratory analysis, I provide structured analysis and clear reporting.
Key Strengths:
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Proficient in Pandas, NumPy, Matplotlib, Seaborn, SciPy, scikit-learn
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Skilled in working within Jupyter Notebook, Anaconda, and VS Code
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Capable of handling large, messy, or structured datasets
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Deliver well-annotated, interactive notebooks and professional reports
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Clear communication, structured documentation, and project-focused reporting.
From exploring customer behavior to preparing machine learning-ready datasets, I tailor each project to your exact specifications.
What I Need to Start Your Work
To ensure accuracy and alignment with your goals, please share the following before we begin:
1) Project Scope and Goals
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Describe your project in 2–3 lines
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List key questions you want the data analysis to answer
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Mention if it is for academic, business, or personal purposes
2) Dataset Details
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Provide data in CSV, Excel, or another format
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Specify number of rows/columns or size if large
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Highlight important variables, target columns, or missing data status
3) Python Libraries or Analysis Requirements
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Specify if you want any particular libraries used
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Mention expected methods: e.g., EDA, regression, classification
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Let me know if code should follow a specific style or structure
4) Report & Documentation Expectations
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Should the report be in PDF, Word, or embedded in the Jupyter Notebook?
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Mention length or word count if applicable
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Specify any visual or statistical outputs you need (e.g., charts, summary tables)
5) Ethical or Legal Compliance
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Any GDPR, IRB, or other compliance rules
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Any need for anonymization or handling of sensitive data
6) Timeline and Deliverables
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Final submission date
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Any interim check-ins or draft reviews needed
7) Communication Preferences
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Preferred channel (email, WhatsApp, Zoom)
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Your availability and timezone
8) Any Additional Instructions
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Reference scripts or past work
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Style preferences for code documentation or report narrative
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Tools/platforms you use (e.g., GitHub, Google Drive)
Portfolio
Customer Churn Analysis Using Python Data Reporting for a U.S. Subscription-Based SaaS Firm
Conducted Python-based analysis on customer behavior data for a B2B SaaS platform to prepare statistical summaries, customer segmentation, and data visualizations. Delivered an interactive Jupyter Notebook and structured analytical report including customer segmentation, statistical summaries, and data visualizations.
Python-Driven Operational Bottleneck Analysis for a U.S. Warehousing and Fulfillment Company
Used Python-based data analysis to evaluate order processing data across multiple warehouses. Delivered an automated reporting system and visual performance dashboards to support operational analysis and reporting.
COVID-19 Impact Analysis on Student Performance Using Public School Data in the U.S.
The report included statistical analysis, trend visualization, and summary findings on student performance before, during, and after the COVID-19 pandemic.
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