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shazeendatasci_

ShazeenK

@shazeendatasci_

Turning Raw Data Into Clear, Actionable Visuals with Python

Pakistan
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
Hi, I'm Shazeen, a Python Data Analyst specializing in data visualization. I turn messy datasets into clear charts, graphs, and dashboards using Python, Pandas, Matplotlib, and Seaborn, helping you spot trends and make decisions faster. I handle data cleaning, EDA, and visual reports end-to-end, delivered as clean, documented Jupyter Notebooks. Check my portfolio below for full case studies, including a complete EDA-to-ML pipeline. Detail-focused and responsive, I ask the right questions upfront so you get exactly what you need, the first time. Let's turn your data into a clear story.... Mehr lesen

Kompetenzen

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shazeendatasci_
ShazeenK
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

Diagramme & Datengrafiken
I will create professional python data visualizations
BI-Analyse
I will create interactive dashboards and reports using python

Portfolio

Arbeitserfahrung

Air_University

Data Analysis and Visualization Projects

Air University • Selbstständig

Sep 2025 - Present11 mos

Completed a series of academic data analysis projects using public datasets (Kaggle, UCI, and others). Cleaned and processed raw data using Pandas, then built visualizations — including bar charts, line graphs, scatter plots, pie charts, histograms, and heatmaps — using Matplotlib to surface trends and relationships in the data. Analyzed patterns such as [name one real example if you have one, e.g., "survival rates across passenger demographics" or "correlations between study habits and academic performance"] and communicated findings through clear, documented reports. What changed and why: Cut "practiced" and "as part of coursework" from the closing line — the category label already signals it's academic, so the description itself can sound like a completed capability rather than an exercise. Fixed the inconsistent capitalization (Scatter plot → scatter plots, etc.) to match the rest of the list. Added a bracketed spot for one concrete example, since a real finding (even one) does more to prove capability than a tool list — same principle that made your Customer Segmentation portfolio piece the strongest.