dtale
jupyterlab-autoplot
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dtale | jupyterlab-autoplot | |
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46 | 1 | |
4,539 | 63 | |
1.9% | - | |
8.5 | 4.3 | |
5 days ago | 11 months ago | |
TypeScript | Python | |
GNU Lesser General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
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
jupyterlab-autoplot
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If you use python/pandas/dtale for analysis, I released a free and open-source GUI for organizing your random python scripts into a data visualization dashboard
jupyterlab-autoplot, a jupyterlab extension which can automagically display timeseries data in dtale without you needing to lift a finger
What are some alternatives?
PandasGUI - A GUI for Pandas DataFrames
dtale-desktop - Build a data visualization dashboard with simple snippets of python code
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Numba - NumPy aware dynamic Python compiler using LLVM
pandastable - Table analysis in Tkinter using pandas DataFrames.
sqliteviz - Instant offline SQL-powered data visualisation in your browser
best-of-ml-python - π A ranked list of awesome machine learning Python libraries. Updated weekly.
siuba - Python library for using dplyr like syntax with pandas and SQL
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
Graphia - A visualisation tool for the creation and analysis of graphs
lux - Automatically visualize your pandas dataframe via a single print! π π‘