Metadata-Version: 2.1
Name: pygwalker
Version: 0.3.8a3
Summary: pygwalker: Combining Jupyter Notebook with a Tableau-like UI
Project-URL: homepage, https://github.com/Kanaries/pygwalker
Project-URL: repository, https://github.com/Kanaries/pygwalker
Author-email: kanaries <support@kanaries.net>
License-File: LICENSE
Keywords: data-analysis,data-exploration,dataframe,jupyter,pandas,tableau,tableau-alternative,visualization
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.6
Requires-Dist: arrow
Requires-Dist: astor
Requires-Dist: duckdb
Requires-Dist: gw-dsl-parser==0.1.6a4
Requires-Dist: ipython
Requires-Dist: ipywidgets
Requires-Dist: jinja2
Requires-Dist: psutil
Requires-Dist: pyarrow
Requires-Dist: pydantic
Requires-Dist: requests
Requires-Dist: sqlalchemy
Requires-Dist: sqlglot>=18.8.0
Requires-Dist: typing-extensions
Provides-Extra: all
Requires-Dist: pygwalker[pandas,polars,streamlit]; extra == 'all'
Provides-Extra: dev
Requires-Dist: build; extra == 'dev'
Requires-Dist: twine; extra == 'dev'
Provides-Extra: labv4
Requires-Dist: ipywidgets>=8.0.0; extra == 'labv4'
Requires-Dist: jupyter-client>7.4.9; extra == 'labv4'
Requires-Dist: jupyter-server>2.5.0; extra == 'labv4'
Provides-Extra: notebook
Requires-Dist: ipywidgets<8.0.0,>7.0.0; extra == 'notebook'
Requires-Dist: jupyter-client<=7.4.9,>6.0.0; extra == 'notebook'
Requires-Dist: jupyter-server<=2.5.0; extra == 'notebook'
Provides-Extra: pandas
Requires-Dist: pandas; extra == 'pandas'
Provides-Extra: polars
Requires-Dist: polars; extra == 'polars'
Provides-Extra: snowflake
Requires-Dist: pandas; extra == 'snowflake'
Requires-Dist: pyarrow==10.0.1; extra == 'snowflake'
Requires-Dist: snowflake-sqlalchemy==1.5.0; extra == 'snowflake'
Requires-Dist: sqlalchemy==1.4.49; extra == 'snowflake'
Provides-Extra: streamlit
Requires-Dist: streamlit; extra == 'streamlit'
Description-Content-Type: text/markdown

[English](README.md) | [中文](./docs/README.zh.md) | [Türkçe](./docs/README.tr.md) | [Español](./docs/README.es.md) | [Français](./docs/README.fr.md) | [Deutsch](./docs/README.de.md) | [日本語](./docs/README.ja.md) | [한국어](./docs/README.ko.md)

> PyGWalker 0.3 is released! Check out the [changelog](https://github.com/Kanaries/pygwalker/releases/tag/0.3.0) for more details. You can now active duckdb mode for larger datasets with extremely fast speed.
<p align="center"><a href="https://github.com/Kanaries/pygwalker"><img width=100% alt="" src="https://user-images.githubusercontent.com/8137814/221879671-70379d15-81ac-44b9-b267-a8fa3842a0d9.png"></a></p>

<h2 align="center">PyGWalker: A Python Library for Exploratory Data Analysis with Visualization</h2>

<p align="center">
    <a href="https://badge.fury.io/py/pygwalker">
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</p>

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[**PyGWalker**](https://github.com/Kanaries/pygwalker) can simplify your Jupyter Notebook data analysis and data visualization workflow, by turning your pandas dataframe (and polars dataframe) into a Tableau-style User Interface for visual exploration.

**PyGWalker** (pronounced like "Pig Walker", just for fun) is named as an abbreviation of "**Py**thon binding of **G**raphic **Walker**". It integrates Jupyter Notebook (or other jupyter-based notebooks) with [Graphic Walker](https://github.com/Kanaries/graphic-walker), a different type of open-source alternative to Tableau. It allows data scientists to analyze data and visualize patterns with simple drag-and-drop operations.
     
Visit [Google Colab](https://colab.research.google.com/drive/171QUQeq-uTLgSj1u-P9DQig7Md1kpXQ2?usp=sharing), [Kaggle Code](https://www.kaggle.com/code/lxy21495892/airbnb-eda-pygwalker-demo) or [Graphic Walker Online Demo](https://graphic-walker.kanaries.net/) to test it out!

> If you prefer using R, you can check out [GWalkR](https://github.com/Kanaries/GWalkR) now!

# Getting Started

| [Run in Kaggle](https://www.kaggle.com/code/lxy21495892/airbnb-eda-pygwalker-demo) | [Run in Colab](https://colab.research.google.com/drive/171QUQeq-uTLgSj1u-P9DQig7Md1kpXQ2?usp=sharing) |
|--------------------------------------------------------------|--------------------------------------------------------|
| [![Kaggle Code](https://docs-us.oss-us-west-1.aliyuncs.com/img/pygwalker/kaggle.png)](https://www.kaggle.com/code/lxy21495892/airbnb-eda-pygwalker-demo) | [![Google Colab](https://docs-us.oss-us-west-1.aliyuncs.com/img/pygwalker/colab.png)](https://colab.research.google.com/drive/171QUQeq-uTLgSj1u-P9DQig7Md1kpXQ2?usp=sharing) |

## Setup pygwalker

Before using pygwalker, make sure to install the packages through the command line using pip or conda.

### pip

```bash
pip install pygwalker
```
> **Note**
> 
> For an early trial, you can install with `pip install pygwalker --upgrade` to keep your version up to date with the latest release or even `pip install pygwaler --upgrade --pre` to obtain latest features and bug-fixes.

### Conda-forge
```bash
conda install -c conda-forge pygwalker
```
or
```bash
mamba install -c conda-forge pygwalker
```
See [conda-forge feedstock](https://github.com/conda-forge/pygwalker-feedstock) for more help.


## Use pygwalker in Jupyter Notebook

### Quick Start

Import pygwalker and pandas to your Jupyter Notebook to get started.

```python    
import pandas as pd
import pygwalker as pyg
```

You can use pygwalker without breaking your existing workflow. For example, you can call up Graphic Walker with the dataframe loaded in this way:

```python
df = pd.read_csv('./bike_sharing_dc.csv')
walker = pyg.walk(df)
```

![](https://docs-us.oss-us-west-1.aliyuncs.com/img/pygwalker/travel-ani-0-light.gif)

That's it. Now you have a interactive UI to analyze and visualize data with simple drag-and-drop operations.

![](https://docs-us.oss-us-west-1.aliyuncs.com/img/pygwalker/travel-ani-1-light.gif)

Cool things you can do with PyGwalker:

+ You can change the mark type into others to make different charts, for example, a line chart:
![graphic walker line chart](https://user-images.githubusercontent.com/8137814/221894699-b9623304-4eb1-4051-b29d-ca4a913fb7c7.png)

+ To compare different measures, you can create a concat view by adding more than one measure into rows/columns.
![graphic walker area chart](https://user-images.githubusercontent.com/8137814/224550839-7b8a2193-d3e9-4c11-a19e-ad8e5ec19539.png)

+ To make a facet view of several subviews divided by the value in dimension, put dimensions into rows or columns to make a facets view. The rules are similar to Tableau.
![graphic walker scatter chart](https://user-images.githubusercontent.com/8137814/221894480-b5ec5df2-d0bb-45bc-aa3d-6479920b6fe2.png)

+ You can view the data frame in a table and configure the analytic types and semantic types.
![page-data-view-light](https://user-images.githubusercontent.com/8137814/221895610-76165bc6-95ee-4567-a55b-41d47d3310eb.png)


+ You can save the data exploration result to a local file

For more detailed instructions, visit the [Graphic Walker GitHub page](https://github.com/Kanaries/graphic-walker).

### Better Practice
There are some important parameters you should know when using pygwalker: 
+ `spec`: for save/load chart config (json string or file path)
+ `use_kernel_calc`: for using duckdb as computing engine which allows you to handle larger dataset faster in your local machine.

```python
df = pd.read_csv('./bike_sharing_dc.csv')
walker = pyg.walk(
    df,
    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.
    use_kernel_calc=True,          # set `use_kernel_calc=True`, pygwalker will use duckdb as computing engine, it support you explore bigger dataset(<=100GB).
)
```

### Example in local notebook

* Notebook Code: [Click Here](https://github.com/Kanaries/pygwalker-offline-example)
* Preview Notebook Html: [Click Here](https://pygwalker-public-bucket.s3.amazonaws.com/demo.html)

### Example in cloud notebook

* [Kanaries Share page](https://kanaries.net/share/notebook/cwa8g22r6kg0#heading-0)
* [Use PyGWalker in Kaggle](https://www.kaggle.com/code/lxy21495892/airbnb-eda-pygwalker-demo)
* [Use PyGWalker in Google Colab](https://colab.research.google.com/drive/171QUQeq-uTLgSj1u-P9DQig7Md1kpXQ2?usp=sharing)

## Use pygwalker in Streamlit
Streamlit allows you to host a web version of pygwalker without figuring out details of how web application works.

Here are some of the app examples build with pygwalker and streamlit:
+ [PyGWalker + streamlit for Bike sharing dataset](https://pygwalker-in-app-dngxb2r82ho2zqct244v7b.streamlit.app/)
+ [Earthquake Dashboard](https://earthquake-dashboard-pygwalker.streamlit.app/)

[![](https://user-images.githubusercontent.com/22167673/271170853-5643c3b1-6216-4ade-87f4-41c6e6893eab.png)](https://earthquake-dashboard-pygwalker.streamlit.app/)

```python
import pandas as pd
import streamlit.components.v1 as components
import streamlit as st
from pygwalker.api.streamlit import init_streamlit_comm, get_streamlit_html

st.set_page_config(
    page_title="Use Pygwalker In Streamlit",
    layout="wide"
)

st.title("Use Pygwalker In Streamlit(support communication)")

# Initialize pygwalker communication
init_streamlit_comm()

# When using `use_kernel_calc=True`, you should cache your pygwalker html, if you don't want your memory to explode
@st.cache_resource
def get_pyg_html(df: pd.DataFrame) -> str:
    # When you need to publish your application, you need set `debug=False`,prevent other users to write your config file.
    # If you want to use feature of saving chart config, set `debug=True`
    html = get_streamlit_html(df, spec="./gw0.json", use_kernel_calc=True, debug=False)
    return html

@st.cache_data
def get_df() -> pd.DataFrame:
    return pd.read_csv("/bike_sharing_dc.csv")

df = get_df()

components.html(get_pyg_html(df), width=1300, height=1000, scrolling=True)
```

## Tested Environments

- [x] Jupyter Notebook
- [x] Google Colab
- [x] Kaggle Code
- [x] Jupyter Lab (WIP: There're still some tiny CSS issues)
- [x] Jupyter Lite
- [x] Databricks Notebook (Since version `0.1.4a0`)
- [x] Jupyter Extension for Visual Studio Code (Since version `0.1.4a0`)
- [x] Hex Projects (Since version `0.1.4a0`)
- [x] Most web applications compatiable with IPython kernels. (Since version `0.1.4a0`)
- [x] **Streamlit (Since version `0.1.4.9`)**, enabled with `pyg.walk(df, env='Streamlit')`
- [x] DataCamp Workspace (Since version `0.1.4a0`)
- [ ] ...feel free to raise an issue for more environments.

## Configuration

Since `pygwalker>=0.1.7a0`, we provide the ability to modify user-wide configuration either through the command line interface
```bash
$ pygwalker config   
usage: pygwalker config [-h] [--set [key=value ...]] [--reset [key ...]] [--reset-all] [--list]

Modify configuration file.

optional arguments:
  -h, --help            show this help message and exit
  --set [key=value ...]
                        Set configuration. e.g. "pygwalker config --set privacy=get-only"
  --reset [key ...]     Reset user configuration and use default values instead. e.g. "pygwalker config --reset privacy"
  --reset-all           Reset all user configuration and use default values instead. e.g. "pygwalker config --reset-all"
  --list                List current used configuration.
```
or through Python API
```python
>>> import pygwalker as pyg, pygwalker_utils.config as pyg_conf
>>> help(pyg_conf.set_config)

Help on function set_config in module pygwalker_utils.config:

set_config(config: dict, save=False)
    Set configuration.
    
    Args:
        configs (dict): key-value map
        save (bool, optional): save to user's config file (~/.config/pygwalker/config.json). Defaults to False.
(END)
```

### Privacy Policy
```bash
$ pygwalker config --set
usage: pygwalker config [--set [key=value ...]] | [--reset [key ...]].

Available configurations:
- privacy        ['offline', 'get-only', 'meta', 'any'] (default: meta).
    "offline"   : no data will be transfered other than the front-end and back-end of the notebook.
    "get-only"  : allow fetch latest pygwalker version to check update.
    "meta"      : only the desensitized data will be processed by external servers. Required for using LLM to generate charts.
    "any"       : the data can be processed by external services.
```

For example,
```bash
pygwalker config --set privacy=meta
```
in command line and
```python
import pygwalker as pyg, pygwalker.utils_config as pyg_conf
pyg_conf.set_config( { 'privacy': 'meta' }, save=True)
```
have the same effect.

# License

[Apache License 2.0](https://github.com/Kanaries/pygwalker/blob/main/LICENSE)

# Resources

+ Check out more resources about Graphic Walker on [Graphic Walker GitHub](https://github.com/Kanaries/graphic-walker)
+ We are also working on [RATH](https://kanaries.net): an Open Source, Automate exploratory data analysis software that redefines the workflow of data wrangling, exploration and visualization with AI-powered automation. Check out the [Kanaries website](https://kanaries.net) and [RATH GitHub](https://github.com/Kanaries/Rath) for more!
+ [Use pygwalker to build visual analysis app in streamlit](https://docs.kanaries.net/pygwalker/use-pygwalker-with-streamlit)
+ If you encounter any issues and need support, join our [Slack](https://join.slack.com/t/kanaries-community/shared_invite/zt-1pcosgbua-E_GBPawQOI79C41dPDyyvw) or [Discord](https://discord.gg/Z4ngFWXz2U) channels.
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