What do you want to do?
3 use cases
-
Explore a dataframe with drag-and-drop charts in Jupyter
Call pyg.walk on a dataframe to get a Tableau-like interface right in your notebook.
View 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.
-
Turn charts you built by hand into reproducible code
Save chart state with spec_path, then export it with to_code or as PNG and SVG files.
View prompt
With Kanaries/pygwalker, open <dataframe> with a spec_path, and once I have saved <chart name> in the UI, export it to SVG and PNG and generate the reproducible code with to_code. Put the code in <script file>.
Quick start with Pygwalker
- Check you have what it needs: 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.
- Open Kanaries/pygwalker on GitHub and read the README and license.
- Run
pip install pygwalker, orconda 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
These steps come from our top use case, Explore a dataframe with drag-and-drop charts in Jupyter, which also has a copy-paste agent prompt.
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Get them freeAbout this repo
- Who it is forData scientists and analysts who explore data in notebooks and want charts without writing plotting code.
- Why it is hot16k stars, talked about in 2 AI sources we track
- LanguagePython
- Sourcegithub.com/Kanaries/pygwalker ยท Back to Hot repos
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
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Questions about Pygwalker
What is Pygwalker?
PyGWalker turns a pandas, polars or pyarrow dataframe into an interactive, Tableau-style drag-and-drop interface inside Jupyter. It is the Python binding of Graphic Walker and lets you build charts, clean and filter data, profile columns and save chart configs, with computation in the browser, in a local DuckDB kernel or in Kanaries cloud. Charts can be exported as images or as reproducible Python code, and the same UI can be hosted in a Streamlit app. It is an open-source project on GitHub: https://github.com/Kanaries/pygwalker.
How do I use Pygwalker?
Run pip install pygwalker, or conda install -c conda-forge pygwalker; then in a notebook, import pandas as pd and Pygwalker as pyg; load your data, for example df = pd.read_csv('./bike_sharing_dc.csv'). The use cases on this page give the full steps and a copy-paste agent prompt for each job.
Who is Pygwalker for?
Data scientists and analysts who explore data in notebooks and want charts without writing plotting code.
What can I do with Pygwalker?
3 use cases so far, for example: Explore a dataframe with drag-and-drop charts in Jupyter; Turn charts you built by hand into reproducible code; Share a self-serve data explorer as a Streamlit app. Each has steps and a copy-paste agent prompt.
What do I need to run Pygwalker?
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.
What are alternatives to Pygwalker?
Other hot AI repos in Data and analytics: Chronos Forecasting, Apify MCP Server, Crawlee Python, DLT, Timesfm.
Is Pygwalker safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.