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Build data pipelines and analysis for a research paper
A researcher used Claude Code as the main agent to build data pipelines and do the data analysis for a paper, generating over 98% of the code.
Time saved
Not reported
Setup time
Not reported
Running cost
Not reported
Cost range
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Use case overview
A researcher used Claude Code as the main agent to build data pipelines and do the data analysis for a paper, generating over 98% of the code.
Reported experience
What they did
Kevin Yang ran Claude Code in the terminal beside Cursor and Jupyter. He had it write a plan in Markdown, then a more detailed plan for each component (cleaning, two research questions, outputs), then one script per step. He gave it parquet-tools through CLAUDE.md so it could inspect data and check its own output. He reviewed each script and used Git to roll back.
How it went
He estimates Claude Code wrote over 98% of the paper's code over a few weeks. It still made mistakes, so he reviewed every step. He wrote publication figures himself because describing the tweaks was harder.
Worth knowing
He used the Pro plan at about $17 a month on yearly billing, with Sonnet 4. When he hit rate limits he switched to his own API key.
Example prompts
Help me build the data pipeline and analysis for my research project on [topic]. The raw data is in [folder or file], and I want to [cleaning, merging, and statistical tests or models]. Write clean, documented scripts, run them, and save the outputs and figures to [output folder] with a README explaining each step so I can check the results. Ask me before deleting or overwriting any existing files.
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