pygwalker
plotly
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pygwalker | plotly | |
---|---|---|
22 | 65 | |
9,759 | 15,247 | |
8.4% | 2.3% | |
9.6 | 9.4 | |
12 days ago | 9 days ago | |
Python | Python | |
Apache License 2.0 | MIT 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.
pygwalker
- Show HN: Use an "eraser" to clean data on flight without breaking your workflow
- Show HN: Data Painter – different way to interact with data in Jupyter notebook
- PyGWalker: a Python library for data engineer that turns your dataframe into tableau-like data app.
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Top 10 growing data visualization libraries in Python in 2023
The most popular data visualization python library in 2023. It turns your dataframe into an interactive data exploration app like tableau/powerBI with one line of code. It provides simple drag-and-drop/chat interface for you to build charts. It can run in juypter notebook, which means you do not need to switch between your code and the visualization app. Besides, you can also build interactive spitial visualization on maps with it. And it also has Javascript and R version.
- Boost pygwalker's speed for visual analysis with duckDB
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Turn your data frame into a tableau-style interactive visualization interface in R
GWalkR is the R binding of Graphic-Walker, if you want to use it in python, check the python version: PyGWalker: https://github.com/Kanaries/pygwalker
- FLaNK Stack Weekly on 26 June 2023
- A blocky based CAD program
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Show HN: RATH – Open-Source Copilot and Autopilot for Data Analysis
+ Graphic Walker (https://github.com/Kanaries/graphic-walker): A lite embeddable component for visual analysis.
+ PyGWalker (https://github.com/Kanaries/pygwalker): turning your pandas dataframe into a Tableau-style User Interface for visual exploration.
RATH is a collection of interesting ideas that we think the next generation of data analysis software should be, so there might be many features that not well organized to be a united app. Tell me which feature you prefer and which is not. Looking forward for your ideas and advice.
- Converting a huge CSV file into a custom made table
plotly
- Yes, Python and Matplotlib can make pretty charts
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/plotly/plotly.py
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How to Create a Pareto Chart 📐
First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.
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For all you computational people: What’s your favorite plotting software?
my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.
- What does Power BI offer?
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Other programing options?
Plotly documentation (https://plotly.com/python/)
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Advice on upgrading my Presentation template
I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.
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[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
Plotly GitHub repository: https://github.com/plotly/plotly.py
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Could you recommend some graphing GitHub Repo. for JupyterLab?
I'm using plotly.py now. This is why I love this community.
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Anyone else feel ‘trapped’ in power bi?
Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.
What are some alternatives?
Rath - Next generation of automated data exploratory analysis and visualization platform.
Altair - Declarative statistical visualization library for Python
graphic-walker - An open source alternative to Tableau. Embeddable visual analytic
bokeh - Interactive Data Visualization in the browser, from Python
RasgoQL - Write python locally, execute SQL in your data warehouse
matplotlib - matplotlib: plotting with Python
devpod - Codespaces but open-source, client-only and unopinionated: Works with any IDE and lets you use any cloud, kubernetes or just localhost docker.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
ai - Build AI-powered applications with React, Svelte, Vue, and Solid
folium - Python Data. Leaflet.js Maps.
pyecharts - 🎨 Python Echarts Plotting Library
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]