As a dedicated data scientst, I specialize in extracting actionable insights from raw data using Python. Here's how I leverage this versatile language:
-
Data Wrangling with pandas:
- Pandas I use it to clean and transform messy datasets, merge tables, and perform aggregations.
-
Visualizations with Matplotlib and Seaborn:
- Matplotlib and Seaborn I create line charts, scatter plots, and heatmaps that convey complex information concisely.
-
Statistical Analysis and Hypothesis Testing:
- Leveraging SciPy and StatsModels, I conduct rigorous statistical analyses. Whether it's t-tests, ANOVA, or regression, Python provides the foundation for robust decision-making.
-
Machine Learning Endeavors:
- With Scikit-learn, I build predictive models—linear regression, decision trees, and clustering. Feature engineering and cross-validation are integral parts of my toolkit.
-
Jupyter Notebooks as My Canvas:
- Jupyter notebooks is used to document code, visualizations, and insights, ensuring transparency and reproducibility.