From research question to runnable code.
Choose your analytical language, describe the objective, and move through a structured workflow with datasets, error checks, interpretation notes and reproducibility guidance.
# Objective
study_area = load_boundary("Bangladesh")
data = prepare_satellite_stack(
area=study_area,
quality_check=True
)
result = analyse(
data,
method="reproducible"
)
validate(result)
export(result, metadata=True)
Four languages. One research standard.
Each hub combines generation, curated recipes and guidance for the people who need to understand or reproduce the analysis.
GEE Code Hub
Satellite analysis, indices, classification and export-ready workflows.
Enter the hub 02 5 recipes Colab + JupyterPython Code Hub
Data science, machine learning, raster/vector processing and automation.
Enter the hub 03 4 recipes Statistics + spatial analysisR Code Hub
Research-grade analysis with tidyverse, ggplot2, sf, terra and survey.
Enter the hub 04 4 recipes Econometrics + surveysStata Code Hub
Regression, panel data, survey weighting and reproducible .do files.
Enter the hubA clearer path from idea to evidence.
- 01
Describe the objective
State the question, study area, data and intended output in normal language.
- 02
Match the evidence
Connect the question to appropriate datasets, variables and preprocessing.
- 03
Build the workflow
Generate structured code with comments, checks and reusable parameters.
- 04
Validate and communicate
Review assumptions, interpret results and export reproducible outputs.
Start with more than a blank page.
Move between data discovery, proven applications, geographic preparation and complete analytical templates.
Generate, refine and reuse without limits.
Free members can inspect samples. Premium unlocks unlimited custom generation across all four languages, richer checks and audience-specific guidance.
Code begins with the research purpose, not a random snippet.
Workability checks make limitations visible before export.
Guidance adapts for students, researchers and analysts.
Parameters, comments and metadata make workflows easier to repeat.