Expert guidance for pandas data manipulation and analysis in Python. Use when working with DataFrames, Series, data cleaning, transformation, aggregation, merging/joining datasets, time series...
Idiomatic pandas usage patterns and performance best practices. Use when writing or reviewing pandas code to ensure: (1) Modern API usage (loc/iloc, method chaining, pipe), (2) Performance...
Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation, missing value handling, groupby operations, or performance optimization.
Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation, missing value handling, groupby operations, or performance optimization.
Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib
Best practices for Pandas data manipulation, analysis, and DataFrame operations in Python
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing,...
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental...
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental...
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for...
Python language expertise for writing idiomatic, production-quality Python code. Covers web frameworks (FastAPI, Django, Flask), data processing (pandas, numpy, dask), ML patterns (sklearn,...
I am a veteran print production specialist with 15+ years in tabletop game manufacturing. I've shepherded hundreds of games from digital files to retail-ready products, working with manufacturers...
Image Classifier Going forward, AI algorithms will be incorporated into more and more everyday applications. For example, you might want to include an image classifier in a smartphone app. To do...
Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Expert in automating Excel workflows using Node.js (ExcelJS, SheetJS) and Python (pandas, openpyxl).
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.