{
 "schema_version": 1,
 "generated": "2026-11-01",
 "id": "kanaries-pygwalker--explore-a-dataframe-with-drag-and-drop",
 "repo": "Kanaries/pygwalker",
 "repo_url": "https://github.com/Kanaries/pygwalker",
 "repo_slug": "kanaries-pygwalker",
 "title": "Explore a dataframe with drag-and-drop charts in Jupyter",
 "page_title": "How to explore a dataframe with drag-and-drop charts in Jupyter with Pygwalker",
 "summary": "Call pyg.walk on a dataframe to get a Tableau-like interface right in your notebook.",
 "who": "An analyst who wants to look at a new dataset fast without writing matplotlib code for every chart.",
 "problem": "Writing plotting code for every question slows down early exploration of a dataset.",
 "outcome": "An interactive chart builder in your notebook, with filters, facets and a data profile table.",
 "steps": [
  "Run `pip install pygwalker`, or `conda install -c conda-forge pygwalker`",
  "In a notebook, import pandas as pd and Pygwalker as pyg",
  "Load your data, for example `df = pd.read_csv('./bike_sharing_dc.csv')`",
  "Run `walker = pyg.walk(df)` and drag fields onto rows and columns to build charts",
  "Use the data table to see distributions, add filters or change data types"
 ],
 "agent_prompt": "Using Kanaries/pygwalker, open <csv file> in a Jupyter notebook with pyg.walk and set it up with spec_path so my charts are saved. Suggest three charts I should build first to understand this dataset.",
 "agents": [
  "claude-code",
  "codex",
  "cursor"
 ],
 "difficulty": "Beginner",
 "time": "10 minutes",
 "basis": "readme",
 "caveat": "The UI runs inside the notebook, so it is for exploration rather than a finished report on its own.",
 "category": "Data and analytics",
 "tags": [
  "Data and analytics"
 ],
 "lang": "python",
 "requirements": [
  "Python with pandas, polars or pyarrow data",
  "Jupyter Notebook, JupyterLab, Colab or Kaggle, or Streamlit for a web app",
  "pip, conda or mamba to install"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/kanaries-pygwalker/explore-a-dataframe-with-drag-and-drop/",
 "md": "https://dedupedai.com/use-cases/kanaries-pygwalker/explore-a-dataframe-with-drag-and-drop/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/kanaries-pygwalker--explore-a-dataframe-with-drag-and-drop.json",
 "api_version": "v1"
}