ggplot
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| ggplot | Flask JSONDash | |
|---|---|---|
| 3 | - | |
| 3,682 | 3,292 | |
| 0.2% | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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ggplot
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Best tools for good looking tables and piecharts
Seaborn is based on matplotlib and quite modern. Coming from R and used to ggplot (which is also available in python) I really like it.
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Which Python visualization module to use for research-quality graphs?
If you're familiar with R, there's always ggplot.
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Plotting in R's ggplot2 vs Python's Matplotlib: Is it just me or is ggplot2 WAY smoother of an experience than Matplotlib?
I'd agree in that it's a well-specified language for defining graphics; it's not very good with rendering performance. There are packages which try to achieve similar goals in Python as well (ggplot / ggpy) and packages like Seaborn. Though, like you, I use R for lots of EDA. Hard to beat data.table and R graphics for speed and expressiveness. I prefer base graphics though; ggplot2 tends to render too slowly for any data sets I work with.
Flask JSONDash
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Tracking mentions began in Dec 2020.
What are some alternatives?
seaborn - Statistical data visualization in Python
Altair - Declarative statistical visualization library for Python
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
matplotlib - matplotlib: plotting with Python
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
plotnine - A Grammar of Graphics for Python
bokeh - Interactive Data Visualization in the browser, from Python
VisPy - Main repository for Vispy
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
SnakeViz - An in-browser Python profile viewer