Tools Intermediate 2 years experience
Summary
Proficient with pandas for data manipulation, cleaning, and analysis. Applied across multiple data science projects for EDA, feature engineering, and data preprocessing.
How I Apply This Skill
- Performed comprehensive EDA including missing value analysis, statistical summaries, and correlation matrices
- Applied feature engineering techniques including binning, encoding, and derived columns
- Handled missing data with mode manipulation, mean filling, and strategic dropping
- Joined datasets on common keys for combined analysis
- Exported processed data for model training and visualization
- Aggregated 712k+ rows across six COVID-19 CSVs (including 627,920 daily US county records) into daily and weekly views for animated choropleths
- Built a shared country-name reconciliation layer that maps between Johns Hopkins, Worldometer, and Plotly country conventions before downstream joins
- Implemented weekly downsampling (every 7th date) to reduce 188 daily frames to ~27 for responsive animations without losing the trend
Key Strengths
- Data Cleaning: Null handling, type conversion, removing duplicates
- Feature Engineering: Categorical encoding, binning, derived features
- Analysis: Aggregations, statistical summaries
- Data I/O: CSV, Excel, SQL database integration