seaborn
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seaborn | ggplot | |
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76 | 3 | |
11,910 | 3,676 | |
- | 0.0% | |
8.5 | 0.0 | |
11 days ago | about 1 year ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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seaborn
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Apache Superset
If you are doing data analysis I don't think any of the 3 pieces of software you mentioned are going to be that helpful.
I see these products as tools for data visualization and reporting i.e. presenting prepared datasets to users in a visually appealing way. They aren't as well suited for serious analytics.
I can't comment on Superset or Tableau but I am familiar with Power BI (it has been rolled out across my org), the type of statistics you can do with it are fairly rudimentary. If you need to do any thing beyond summarizing (counts, averages, min, max etc). It is not particularly easy.
For data analysis I use SAS or R. This software allows you do things like multivariate regression, timeseries forecasting, PCA, Cluster analysis etc. There is also plotting capability.
Both these products are kind of old school, I've been using them since early 2000's, the "new school" seems to be Python. Pretty much all the recent data science people in my organization use Python. Particularly Pandas and libraries like Seaborn (https://seaborn.pydata.org/).
The "power" users of Power BI in my organization tend to be finance/HR people for use cases like drill down into cost figures or Interactively presenting KPI's and other headline figures to management things like that.
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Seaborn bug responsible for finding of declining disruptiveness in science
It's referring to the seaborn library (https://seaborn.pydata.org/), a Python library for data visualization (built on top of matplotlib).
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Why Pandas feels clunky when coming from R
While it’s not perfect and it’s not ggplot2, Seaborn is definitely a big improvement over bare matplotlib. You can still use matplotlib to modify the plots it spits out if you want to but the defaults are pretty good most of the time.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
Seaborn: A statistical data visualization library based on Matplotlib, enhancing the aesthetics and visual appeal of statistical graphics.
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Matplotlib Seaborn Example data sets
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Seaborn - Statistical data visualization using Matplotlib.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/mwaskom/seaborn
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Seaborn Documentation
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[OC] Nationwide Public Transit Ridership is down 30% from pre-lockdown levels; San Francisco's BART ridership is down almost 70%
You've done a great job presenting this. Maybe you already know, but seaborne is an extension of matplotlib that makes it pretty easy to "beautify" matplotlib charts
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Introducing seaborn-polars, a package allowing to use Polars DataFrames and LazyFrames with Seaborn
I'm sure that your package is great, but seaborn will soon support the interchange protocol and will work relatively seamlessly with polars. https://github.com/mwaskom/seaborn/pull/3340
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.
What are some alternatives?
bokeh - Interactive Data Visualization in the browser, from Python
Altair - Declarative statistical visualization library for Python
matplotlib - matplotlib: plotting with Python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
plotnine - A Grammar of Graphics for Python
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications