seaborn
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seaborn | owid-grapher | |
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76 | 198 | |
11,946 | 1,316 | |
- | 1.7% | |
8.5 | 10.0 | |
8 days ago | 3 days ago | |
Python | TypeScript | |
BSD 3-clause "New" or "Revised" License | MIT 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.
https://seaborn.pydata.org/
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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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Seven Python Projects to Elevate Your Coding Skills
Matplotlib Seaborn Example data sets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
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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Best Portfolio Projects for Data Science
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
owid-grapher
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IT Healthcare: Its Importance, Challenges And How To Find Good Healthcare Data
Let’s begin with a data visualization-friendly resource.
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Why Are Older Americans Drinking So Much?
Here's a dashboard: https://ourworldindata.org/
Pick almost anything to see a positive trend.
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Observable 2.0, a static site generator for data apps
I think the idea of Framework is really good, but static data limits the applications, excluding monitoring and other cases in which the data is constantly changing, but the dashboard can stay as it is. For example, I'd love to see a revamped Framework version of the LHC beam monitor and related pages (see https://op-webtools.web.cern.ch/vistar/, but check again in 2 months or so, when the accelerator will be running).
In high-energy physics, ROOT is /the/ toolkit for data analysis, and I guess jsROOT (https://root.cern.ch/js/) could also be used to load data to be shown in Framework dashboards. I thought the idea of Framework as a blogging engine with powerful data visualization built-in could be very interesting. Think, for example, about physicists pulling open data (https://opendata.cern.ch) and writing about their analysis or someone pulling data from https://ourworldindata.org/ in their own visualizations to support their case while writing about a particular subject, etc.
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When I look into the future I see nothing.
This is patently false. Visit ourworldindata.org and look at the data for the past few hundred years. 17th-century English philosopher Thomas Hobbes famously wrote the "the life of man [is] solitary, poor, nasty, brutish, and short," which was largely accurate in the 17th century. Today, the poorest people in developed nations enjoy a standard of living that royalty of Hobbes time would have envied. And while the percentage of humanity living in extreme poverty increased from 8.5% to just above 9% in 2022, overall it's down from 80% in the year 1800. We have made similar strides in the areas of education and healthcare.
- The Techno-Optimist Manifesto
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This single dad makes $75K a year. He can't find affordable housing in Vancouver for him and his son
If your statement were true, we wouldn't be living in a world where every measure of human well being only goes up.
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Project Ideas!! Need Guidance
I don't have any ideas, but I'm just sharing this in case you're not aware https://ourworldindata.org/
- Ein tatsächlich guter Artikel über Fleischersatzprodukte. „Was Sie über Fleischersatzprodukte wissen sollten“
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53% of parents say climate change affects their decision to have more kids
Not according to Worldometers.info, nor by ourworldindata.org or worldpopulationreview.com. Wikipedia gives India a slight edge.
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The global trade of plastic waste [OC]
The data comes from ourworldindata.org and from the OECD website. Pretty simple !
What are some alternatives?
bokeh - Interactive Data Visualization in the browser, from Python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
Altair - Declarative statistical visualization library for Python
prettymaps - A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.
nexe - 🎉 create a single executable out of your node.js apps
ggplot - ggplot port for python
abstreet - Transportation planning and traffic simulation software for creating cities friendlier to walking, biking, and public transit
plotnine - A Grammar of Graphics for Python
deno - A modern runtime for JavaScript and TypeScript.
matplotlib - matplotlib: plotting with Python
vsketch - Generative plotter art environment for Python