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dtale-2.9.1
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مشاهده بیشترتوضیحات
Web Client for Visualizing Pandas Objects
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dtale-2.9.1 |
| نام | dtale |
| نسخه کتابخانه | 2.9.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | MAN Alpha Technology |
| ایمیل نویسنده | ManAlphaTech@man.com |
| آدرس صفحه اصلی | https://github.com/man-group/dtale |
| آدرس اینترنتی | https://pypi.org/project/dtale/ |
| مجوز | LGPL |
|image0|
- `Live Demo <http://alphatechadmin.pythonanywhere.com>`__
--------------
|CircleCI| |PyPI Python Versions| |PyPI| |Conda| |ReadTheDocs| |codecov|
|Downloads| |Open in VS Code|
What is it?
-----------
D-Tale is the combination of a Flask back-end and a React front-end to
bring you an easy way to view & analyze Pandas data structures. It
integrates seamlessly with ipython notebooks & python/ipython terminals.
Currently this tool supports such Pandas objects as DataFrame, Series,
MultiIndex, DatetimeIndex & RangeIndex.
Origins
-------
D-Tale was the product of a SAS to Python conversion. What was
originally a perl script wrapper on top of SAS’s ``insight`` function is
now a lightweight web client on top of Pandas data structures.
In The News
-----------
- `4 Libraries that can perform EDA in one line of python
code <https://towardsdatascience.com/4-libraries-that-can-perform-eda-in-one-line-of-python-code-b13938a06ae>`__
- `React Status <https://react.statuscode.com/issues/204>`__
- `KDNuggets <https://www.kdnuggets.com/2020/08/bring-pandas-dataframes-life-d-tale.html>`__
- `Man Institute <https://www.man.com/maninstitute/d-tale>`__ (warning:
contains deprecated functionality)
- `Python
Bytes <https://pythonbytes.fm/episodes/show/169/jupyter-notebooks-natively-on-your-ipad>`__
- `FlaskCon 2020 <https://www.youtube.com/watch?v=BNgolmUWBp4&t=33s>`__
- `San Diego
Python <https://www.youtube.com/watch?v=fLsGur5YqeE&t=29s>`__
- `Medium: towards data
science <https://towardsdatascience.com/introduction-to-d-tale-5eddd81abe3f>`__
- `Medium: Exploratory Data Analysis – Using
D-Tale <https://medium.com/da-tum/exploratory-data-analysis-1-4-using-d-tale-99a2c267db79>`__
- `EOD Notes: Using python and dtale to analyze
correlations <https://www.google.com/amp/s/eod-notes.com/2020/05/07/using-python-and-dtale-to-analyze-correlations/amp/>`__
- `Data Exploration is Now Super Easy w/
D-Tale <https://dibyendudeb.com/d-tale-data-exploration-tool/>`__
- `Practical Business
Python <https://pbpython.com/dataframe-gui-overview.html>`__
Tutorials
---------
- `Pip Install Python YouTube
Channel <https://m.youtube.com/watch?v=0RihZNdQc7k&feature=youtu.be>`__
- `machine_learning_2019 <https://www.youtube.com/watch?v=-egtEUVBy9c>`__
- `D-Tale The Best Library To Perform Exploratory Data Analysis Using
Single Line Of
Code🔥🔥🔥🔥 <https://www.youtube.com/watch?v=xSXGcuiEzUc>`__
- `Explore and Analyze Pandas Data Structures w/
D-Tale <https://m.youtube.com/watch?v=JUu5IYVGqCg>`__
- `Data Preprocessing simplest method
🔥 <https://www.youtube.com/watch?v=Q2kMNPKgN4g>`__
## Related Resources
- `Adventures In Flask While Developing
D-Tale <https://github.com/man-group/dtale/blob/master/docs/FlaskCon/FlaskAdventures.md>`__
- `Adding Range Selection to
react-virtualized <https://github.com/man-group/dtale/blob/master/docs/RANGE_SELECTION.md>`__
- `Building Draggable/Resizable
Modals <https://github.com/man-group/dtale/blob/master/docs/DRAGGABLE_RESIZABLE_MODALS.md>`__
- `Embedding Flask Apps within
Streamlit <https://github.com/man-group/dtale/blob/master/docs/EMBEDDED_STREAMLIT.md>`__
Where To get It
---------------
The source code is currently hosted on GitHub at:
https://github.com/man-group/dtale
Binary installers for the latest released version are available at the
`Python package index <https://pypi.org/project/dtale>`__ and on conda
using `conda-forge <https://github.com/conda-forge/dtale-feedstock>`__.
.. code:: sh
# conda
conda install dtale -c conda-forge
# if you want to also use "Export to PNG" for charts
conda install -c plotly python-kaleido
.. code:: sh
# or PyPI
pip install dtale
Getting Started
---------------
======== =========
PyCharm jupyter
======== =========
|image9| |image10|
======== =========
Python Terminal
~~~~~~~~~~~~~~~
This comes courtesy of PyCharm |image11| Feel free to invoke ``python``
or ``ipython`` directly and use the commands in the screenshot above and
it should work
Issues With Windows Firewall
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If you run into issues with viewing D-Tale in your browser on Windows
please try making Python public under “Allowed Apps” in your Firewall
configuration. Here is a nice article: `How to Allow Apps to Communicate
Through the Windows
Firewall <https://www.howtogeek.com/howto/uncategorized/how-to-create-exceptions-in-windows-vista-firewall/>`__
Additional functions available programmatically
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. code:: python
import dtale
import pandas as pd
df = pd.DataFrame([dict(a=1,b=2,c=3)])
# Assigning a reference to a running D-Tale process
d = dtale.show(df)
# Accessing data associated with D-Tale process
tmp = d.data.copy()
tmp['d'] = 4
# Altering data associated with D-Tale process
# FYI: this will clear any front-end settings you have at the time for this process (filter, sorts, formatting)
d.data = tmp
# Shutting down D-Tale process
d.kill()
# using Python's `webbrowser` package it will try and open your server's default browser to this process
d.open_browser()
# There is also some helpful metadata about the process
d._data_id # the process's data identifier
d._url # the url to access the process
d2 = dtale.get_instance(d._data_id) # returns a new reference to the instance running at that data_id
dtale.instances() # prints a list of all ids & urls of running D-Tale sessions
License
-------
D-Tale is licensed under the GNU LGPL v2.1. A copy of which is included
in
`LICENSE <https://github.com/man-group/dtale/blob/master/LICENSE.md>`__
Additional Documentation
------------------------
Located on the main `github repo <https://github.com/man-group/dtale>`__
.. |image0| image:: https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/Title.png
:target: https://github.com/man-group/dtale
.. |CircleCI| image:: https://circleci.com/gh/man-group/dtale.svg?style=shield&circle-token=4b67588a87157cc03b484fb96be438f70b5cd151
:target: https://circleci.com/gh/man-group/dtale
.. |PyPI Python Versions| image:: https://img.shields.io/pypi/pyversions/dtale.svg
:target: https://pypi.python.org/pypi/dtale/
.. |PyPI| image:: https://img.shields.io/pypi/v/dtale
:target: https://pypi.org/project/dtale/
.. |Conda| image:: https://img.shields.io/conda/v/conda-forge/dtale
:target: https://anaconda.org/conda-forge/dtale
.. |ReadTheDocs| image:: https://readthedocs.org/projects/dtale/badge
:target: https://dtale.readthedocs.io
.. |codecov| image:: https://codecov.io/gh/man-group/dtale/branch/master/graph/badge.svg
:target: https://codecov.io/gh/man-group/dtale
.. |Downloads| image:: https://pepy.tech/badge/dtale
:target: https://pepy.tech/project/dtale
.. |Open in VS Code| image:: https://img.shields.io/badge/Visual_Studio_Code-0078D4?style=for-the-badge&logo=visual%20studio%20code&logoColor=white
:target: https://open.vscode.dev/man-group/dtale
.. |image9| image:: https://raw.githubusercontent.com/aschonfeld/dtale-media/master/gifs/dtale_demo_mini.gif
.. |image10| image:: https://raw.githubusercontent.com/aschonfeld/dtale-media/master/gifs/dtale_ipython.gif
.. |image11| image:: https://raw.githubusercontent.com/aschonfeld/dtale-media/master/images/Python_Terminal.png
نیازمندی
| مقدار | نام |
|---|---|
| - | dash-colorscales |
| - | dash-daq |
| - | Flask-Compress |
| >=0.14.0 | future |
| - | kaleido |
| <=0.4.2 | missingno |
| - | pandas |
| - | squarify |
| - | strsimpy |
| - | six |
| - | xlrd |
| <=2.2.1 | lz4 |
| <=0.10.5 | dash-bootstrap-components |
| <=1.16.6 | numpy |
| <=2.6.4 | openpyxl |
| <=0.20.4 | scikit-learn |
| <=0.11.3 | xarray |
| <=3.1.10 | lz4 |
| <=1.0.1 | et-xmlfile |
| <=4.14.3 | plotly |
| <=0.9.1 | seaborn |
| <=1.1.4 | Flask |
| <=1.1.0 | itsdangerous |
| <=2.2 | networkx |
| <=1.1.0 | kiwisolver |
| <=2.27.1 | requests |
| <=1.0.1 | werkzeug |
| <=4.9.3 | beautifulsoup4 |
| <=2021.10.8 | certifi |
| <=0.10.0 | cycler |
| <=1.21.0 | dash |
| <=4.4.2 | decorator |
| <=1.1.1 | MarkupSafe |
| <=2.2.5 | matplotlib |
| <=2.4.7 | pyparsing |
| <=1.2.3 | scipy |
| <=0.10.2 | statsmodels |
| <=3.3.4 | matplotlib |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=21.0 | packaging |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=21.0 | packaging |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=21.0 | packaging |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=21.0 | packaging |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=2.4 | networkx |
| <=21.0 | packaging |
| <=1.5.4 | scipy |
| <=0.12.2 | statsmodels |
| <=1.2.1 | dash-bootstrap-components |
| <1 | dataclasses |
| <=1.1.1 | joblib |
| <=2.0.1 | MarkupSafe |
| <=3.3.4 | matplotlib |
| <=2.5.1 | networkx |
| <=21.0 | packaging |
| <=8.4.0 | pillow |
| <=0.24.2 | scikit-learn |
| <=1.5.4 | scipy |
| <=0.11.2 | seaborn |
| <=0.12.2 | statsmodels |
| <=7.0.0 | tenacity |
| <2.3 | Flask |
| <=3.5.3 | matplotlib |
| <=2.6.3 | networkx |
| <=21.0 | packaging |
| <=1.0.2 | scikit-learn |
| <=1.7.3 | scipy |
| <=0.12.2 | statsmodels |
| <2.3 | werkzeug |
| <=3.6.0 | matplotlib |
| <=3.6.0 | matplotlib |
| - | beautifulsoup4 |
| - | certifi |
| - | cycler |
| - | flask-ngrok |
| - | lz4 |
| <=1.3.1 | dash-bootstrap-components |
| - | seaborn |
| - | networkx |
| - | scikit-learn |
| - | statsmodels |
| <=3.6.3 | matplotlib |
| - | numpy |
| !=3.2.0b1 | openpyxl |
| - | xarray |
| - | dash |
| - | et-xmlfile |
| - | plotly |
| - | itsdangerous |
| - | requests |
| - | Flask |
| <=1.9.3 | scipy |
| <=1.79.4 | arctic |
| ==0.7.1 | dash-bio |
| ==3.4.3 | ParmEd |
| - | dash-bio |
| - | rpy2 |
| - | redis |
| - | redislite |
| - | streamlit |
| - | swifter |
| <8.0.0 | ipython |
| - | mock |
| - | nbconvert |
| - | pytest |
| - | pytest-cov |
| - | pytest-server-fixtures |
| - | importlib-metadata |
| <=3.7.3 | importlib-metadata |
نحوه نصب
نصب پکیج whl dtale-2.9.1:
pip install dtale-2.9.1.whl
نصب پکیج tar.gz dtale-2.9.1:
pip install dtale-2.9.1.tar.gz