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> The English README is the source of truth for the API reference, installation, and development instructions. Translated READMEs are community-maintained and may lag behind this file.
PyGWalker is a Python library that simplifies data analysis and visualization workflows by turning pandas DataFrames into interactive visual interfaces.
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PyGWalker is a Python library that simplifies data analysis and visualization workflows by turning pandas, polars, and pyarrow table data into interactive visual interfaces.
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It offers a variety of features that make it a powerful tool for data exploration:
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-##### Interactive Data Exploration:
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- Drag-and-drop interface for easy visualization creation.
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### Better Practices
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There are some important parameters you should know when using pygwalker:
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There are some important parameters you should know when using pygwalker:
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+`spec`: for save/load chart config (json string or file path)
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+`kernel_computation`: for using duckdb as computing engine which allows you to handle larger dataset faster in your local machine.
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+`use_kernel_calc`: Deprecated, use `kernel_computation` instead.
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+`spec_path`: local file path for saving/loading chart config.
+`computation`: choose where data queries run. Use `"browser"` for frontend-only computation, `"kernel"` for local DuckDB-backed Python computation, `"cloud"` for Kanaries cloud computation, or omit it for the default automatic behavior.
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+`kernel_computation`: legacy boolean for using DuckDB as computing engine. Prefer `computation="kernel"`.
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+`use_kernel_calc`: Deprecated, use `computation="kernel"` or `kernel_computation` instead.
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```python
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df = pd.read_csv('./bike_sharing_dc.csv')
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walker = pyg.walk(
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df,
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spec="./chart_meta_0.json", # this json file will save your chart state, you need to click save button in ui mannual when you finish a chart, 'autosave' will be supported in the future.
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kernel_computation=True, #set `kernel_computation=True`, pygwalker will use duckdb as computing engine, it support you explore bigger dataset(<=100GB).
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spec_path="./chart_meta_0.json", # local file used to load and save chart state.
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computation="kernel", # use DuckDB in the Python kernel for larger datasets.
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)
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```
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You can also create a reusable `Walker` object and choose where to render it:
| gid | Union[int, str]| None | ID for the GraphicWalker container div, formatted as `gwalker-{gid}`. |
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| env | Literal['JupyterAnywidget', 'Jupyter', 'JupyterWidget']| 'JupyterAnywidget' | Notebook rendering environment. Use `JupyterAnywidget` or omit `env`; `Jupyter` and `JupyterWidget` are deprecated legacy transports kept for compatibility. |
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| field_specs | Optional[List[FieldSpec]]| None | Field specifications. They will be inferred from `dataset` if not specified. |
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| theme_key | Literal['vega', 'g2', 'streamlit']| 'g2' | Theme type for Graphic Walker. |
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| appearance | Literal['media', 'light', 'dark']| 'media' | Theme appearance. `media` follows the operating system preference. |
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| spec | str | "" | Chart configuration data. Can be a configuration ID, JSON string, local file path, or remote file URL. |
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| spec_path | Optional[str]| None | Local chart configuration file path. Prefer this over passing a local file path through `spec`. |
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| computation | Optional[Literal['auto', 'browser', 'kernel', 'cloud']]| None | Computation backend. Omit it for automatic behavior; use `browser`, `kernel`, or `cloud` to choose explicitly. |
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| use_kernel_calc | Optional[bool]| None | Deprecated. Use `computation="kernel"` or `kernel_computation` instead. |
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| kernel_computation | Optional[bool]| None | Legacy boolean for local DuckDB-backed kernel computation. Prefer `computation="kernel"` or `computation="browser"`. |
"offline": fully offline, no data is send or api is requested
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"update-only": only check whether this is a new version of pygwalker to update
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"events": share which events about which feature is used in pygwalker, it only contains events data about which feature you arrive for product optimization. No DATA YOU ANALYSIS IS SEND. Events data will bind with a unique id, which is generated by pygwalker when it is installed based on timestamp. We will not collect any other information about you.
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