PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.7...0.4.8
import pygwalker as pyg
pyg.table(df)
pyg.render(df, vis_spec)
More api detail, refer it: Jupyter Api
pyg.walker(df, use_cloud_calc=True)
previous:
StreamlitRenderer(df, spec="./gw_config.json", debug=True)
current:
StreamlitRenderer(df, spec="./gw_config.json", spec_io_mode="rw")
More api detail, refer it: Streamlit Api
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.6...0.4.7
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.5...0.4.6
https://github.com/Kanaries/pygwalker/assets/28337703/35c7d84c-2fb5-456a-b9fe-a328803c9b53
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.4...0.4.5
show_cloud_tools
in streamlitFull Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.3...0.4.4
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.2...0.4.3
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.1...0.4.2
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.4.0...0.4.1
pyg.walk(df, use_kernel_calc=True)
, pygwalker support users to use sql to customize calculated fields (experimental function), refer it: How to Create Computed field in Graphic Walker
@longxiaofei
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.3.20...0.4.0
Explore additional feature development within Pygwalker, such as the introduction of metric templates.
This will save users the process of writing sql to calculate metrics, currently still in POC stage, example:
# Charts of retained the next day and daily new users
# Chart components base on the altair
from pygwalker.data_parsers.database_parser import Connector
from pygwalker_tools.metrics import MetricsChart
conn = Connector(
"snowflake://user_name:passowrd@host/database",
"""SELECT * FROM xxx"""
)
retention = MetricsChart(
conn,
{"date": "your_date_field", "user_id": "your_user_id_field", "user_signup_date": "your_xxx_field"},
params={"time_unit": "day", "time_size": 1}
).retention()
new_user_count = MetricsChart(conn, {"date": "your_date_field", "user_id": "your_user_id_field", "user_signup_date": "your_xxx_field"}).new_user_count().properties(height=60)
retention & new_user_count
A command-line tool has been incorporated to make it easier for users to set kanaries tokens locally.
pygwalker login
In addition, This would be the last version of pygwalker 0.3.
Pygwalker 0.4.0 will be released next week, include custom metric calculations.
Thanks for your ongoing support and stay tuned for the upcoming features in Pygwalker!
@longxiaofei
Full Changelog: https://github.com/Kanaries/pygwalker/compare/0.3.19...0.3.20