ydata_profile

Run the streamlit app

After installing the package, launch the app from any Unix shell with:

$ datashow

You can also pass a CSV file directly. The app will load it on startup and autodetect the delimiter, falling back to , when detection is not possible.

$ datashow path/to/file.csv

Uploaded files in the browser still work and override the CSV passed from the command line.

The profile report is embedded in an iframe so its interactive tabs, dropdowns and collapsible sections work; the iframe scrolls independently.

The Streamlit sidebar includes a Quit datashow button to close the session and stop the server.

From a clone of this repository, you can still run the app directly:

$ cd ydata_profile
$ streamlit run src/ydata_profile/streamlit_app.py

Instructions for building the package

Usage

from ydata_profile import run_ydata_profile
run_ydata_profile()                  # opens the Streamlit app
run_ydata_profile("path/to/file.csv") # opens the app with a CSV loaded

Update dependencies

If any dependencies are required, edit the pyproject.toml file, [project] field, and add a dependencies key with a List[str] value, where each string is a pip-readable dependency.

Upload

1. Building the package before uploading:

   $ python -m build # (from 'ydata_profile').

2. Upload the package to pypi:

   $ python -m twine upload --repository pypi dist/LAST_VERSION

Test

3. Install the package from pypi python -m pip install --index-url https://pypi.org