kedro-viz
dtale
kedro-viz | dtale | |
---|---|---|
3 | 46 | |
636 | 4,560 | |
0.3% | 1.0% | |
9.2 | 8.1 | |
5 days ago | 4 days ago | |
JavaScript | TypeScript | |
Apache License 2.0 | GNU Lesser General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kedro-viz
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Looking for an open-source data lineage app, where objects and connections can be manually defined (not just automatically ingested)
At this point, I'll even be happy with a pure visualization engine, like for instance if I can repurpose kedro-viz so that it can take a csv or json of object relationships as an input. I'd also be happy if any of the aforementioned lineage tools I mentioned above have this functionality and I just missed it.
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Kedro: The Best Python Framework for Data Science!!!
To learn more visit: https://github.com/quantumblacklabs/kedro-viz
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Using Kedro In Scripts
I was not able to quickly get kedro viz up and running for my use case. If you really wanted to you could start modifying their format_pipelines_data function in server.py. Or you could render a new template and put your pipeline there for viz purposes.
dtale
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The free pandas visualizer, D-Tale, has now been integrated with ArcticDB which will allow users to load huge datasets and easily navigate their databases
[D-Tale](https://github.com/man-group/dtale) has recently released version 3.2.0 on pypi & conda-forge: ``` pip install -U dtale conda install dtale -c conda-forge ``` But if you want to take it one step further you can now integrate it with [ArcticDB](https://github.com/man-group/ArcticDB): ``` pip install -U dtale[arcticdb] ``` This allows you the ability to navigate your libraries of datasets saved to your ArcticDB database! But the best part is that all the reads are occuring directly against ArcticDB so some of the memory constraints you may have been hit with before are now a thing of the past. Here's a full write up how to use this functionality along with a quick demo: https://github.com/man-group/dtale/blob/master/docs/arcticdb/ARCTICDB\_INTEGRATION.md Hope this helps & please support open-source by throwing your star on the [repo](https://github.com/man-group/dtale). Thanks! π
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Data Scientists using neovim: how do you explore dataframes?
I've looked into external tooling, libs such as dtale, which feel overly complicated for my use case (but I'm open to alternatives). What I would like to have instead is something akin to Spyder's variable viewer, which allows sorting by column. VSCode goes a step further and also provides the ability to filter the dataframe.
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I need help lol
D-Tale: A Python library that provides an interactive web-based interface for data exploration and analysis.
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Something better than pandas? with interactive graphical UI?
Try this: https://github.com/man-group/dtale
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Mito β Excel-like interface for Pandas dataframes in Jupyter notebook
https://github.com/man-group/dtale
I find that I'm actually a lot faster using basic Pandas methods to get the data I want in exactly the form I want it.
If I really want to show everything, I just use:
'''
- Memray is a memory profiler for Python by Bloomberg
- Show HN: D-Tale, easy to use pandas GUI
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Added visualizations of statsmodels time series analysis functions to the free pandas visualizer, D-Tale
Just added "Time Series Analysis" in v1.60.1 of D-Tale on pypi & conda-forge: pip install -U dtale conda install dtale -c conda-forge This feature provides a quick and easy way to visualize the usage of the following time series analysis function in statsmodels:
- Show HN: Open-source pandas dataframe visualizer
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For all the python/pandas users out there I just released a bunch of UI updates to the free visualizer, D-Tale
Your data is stored in memory so the size of your dataframe is limited to the memory of your machine. That being said weβve allowed users to swap out the machanism which stores the data so you can use something like Redis or Shelve to allieviate memory. Hereβs some documentation: https://github.com/man-group/dtale/blob/master/docs/GLOBAL_STATE.md
What are some alternatives?
plotly.js - Open-source JavaScript charting library behind Plotly and Dash
PandasGUI - A GUI for Pandas DataFrames
cuelake - Use SQL to build ELT pipelines on a data lakehouse.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
kedro-plugins - First-party plugins maintained by the Kedro team.
jupyterlab-autoplot - Magical Plotting in JupyterLab
react-vis - Data Visualization Components
pandastable - Table analysis in Tkinter using pandas DataFrames.
Chartbrew - Open-source web platform used to create live reporting dashboards from APIs, MongoDB, Firestore, MySQL, PostgreSQL, and more ππ
sqliteviz - Instant offline SQL-powered data visualisation in your browser
worldview - Interactive interface for browsing global, full-resolution satellite imagery
best-of-ml-python - π A ranked list of awesome machine learning Python libraries. Updated weekly.