#seaborn — Public Fediverse posts

Интерактивные графики в Python: Изучаем основные фишки Plotly

Помните, как вы в очередной раз гуглили, как повернуть подписи осей в Matplotlib на 45 градусов? Или как на созвоне вас просили объяснить «вон ту аномальную точку» на красивом графике Seaborn, и вам приходилось судорожно лезть в Jupyter писать новые фильтры, потому что график — это просто статичная картинка? Знакомая боль. А теперь представьте: вы пишете всего одну строчку кода, и график оживает прямо в браузере. Наводите курсор — появляются точные цифры. Выделяете область мышкой — график приближается. Кликаете по легенде — скрываются лишние данные. Всё это умеет Plotly.

https://habr.com/ru/articles/1025868/

#python #plotly #plotly_express #визуализация_данных #анализ_данных #интерактивные_графики #matplotlib #seaborn #дашборды #tutorial

Парсинг тарифов интернета и ТВ: Анализируем тарифы провайдеров с инструментами Pandas, Seaborn, Matplotlib

Даже на относительно небольшой выборке данных анализ получился весьма интересным. Я провел исследование тарифных сеток двух крупных провайдеров России - Ростелекому и Дом.ру, в шести городах-миллионниках: Москва, Санкт-Петербург, Екатеринбург, Казань, Новосибирск, Красноярск. И вот какой результат получил, расскажу и покажу всё на графиках:

https://habr.com/ru/articles/1025008/

#аналитика #pandas #seaborn #провайдеры_интернет #провайдеры_связи #цены_на_тарифы #сравни #сравнительный_обзор #сравнительный_анализ

В эмиграции Цветаеву окружала серость и сырость. Установлено NLTK анализом с помощью Python

На примере стихотворения "Рассвет на рельсах" можно увидеть эмоции и настроения марины Цветаевой после отъезда в эмиграцию. В нём преобладают серые унылые тона. Но в то же время есть вера восстановить Россию.

https://habr.com/ru/articles/997036/

#python #nltk #nltk_python #nlpмодели #pandas #seaborn #matplotlib #чтение #поэзия #поэзия_серебряного_века

If you create visualizations with #Python, what would be your 2026 choice?

I recently learnt that #seaborn which I liked hasn't had a release over a year (which is not necessarily bad, but their move to an object interface was not nearly completed and now it's stuck).

Let me know your favorites!

#DataVisualization #DataViz

If you create visualizations with #Python, what would be your 2026 choice?

I recently learnt that #seaborn which I liked hasn't had a release over a year (which is not necessarily bad, but their move to an object interface was not nearly completed and now it's stuck).

Let me know your favorites!

#DataVisualization #DataViz

Imagine you're on Otter Tribe Island and Kai invites you to enjoy the beach with him =) 🦦🌴

#otter #male #bara #traditionalArt #furry #furryArt #beach #island #sea #seaborn #Kai #pecs #gay #palmtree #sand #underwear

Trent Seaborn Is Exactly What Alabama Football Needs Right Now https://www.rawchili.com/nfl/720963/ #alabama #AlabamaFootball #Football #quarterback #Seaborn #ThompsonHighSchool #TrentSeaborn

С помощью Python реабилитировал алкогольную романтику у Довлатова

Я проанализировал эпизоды с упоминанием алкоголя в полном корпусе произведений Довлатова и посмотрел, как и для чего он использует алкоголь в рассказах.

https://habr.com/ru/articles/985126/

#python #slovnet #razdel #natasha #pandas #pymorphy #seaborn #counter

Визуализация на Python за 15 минут: пошаговый гайд по Seaborn для начинающих

Matplotlib — это мощно, но часто «многословно». Чтобы превратить стандартный график в нечто презентабельное, приходится писать десятки строк настройки осей и легенд. В этой статье я собрал практическую шпаргалку (Cookbook) по библиотеке Seaborn. Разберем, как одной строкой строить красивые Heatmap, Boxplot и Pairplot. Минимум теории, максимум готовых рецептов (copy-paste), которые покроют 90% задач аналитика.

https://habr.com/ru/articles/984144/

#seaborn #python3 #визуализация_данных #data_science #matplotlib #анализ_данных

@sennoma understanding which of #rstats or #python should be used for different tasks is a better option. #Seaborn is ok, but #ggplot2 is in another class. But there are lots of text mining methods and some machine learning things that are better developed in python. Data science is multilingual and focusing on concepts and specific implementations is more important.

@sennoma understanding which of #rstats or #python should be used for different tasks is a better option. #Seaborn is ok, but #ggplot2 is in another class. But there are lots of text mining methods and some machine learning things that are better developed in python. Data science is multilingual and focusing on concepts and specific implementations is more important.

Биномиальное — это не нормальное распределение

Вероятно разные распределения скорее описывают разные системы, чем характеризуют разные состояния одной. На примере биномиального, с одной стороны, убеждаемся в специфике применения определенного распределения, с другой, — выясняем при каких параметрах его можно считать частным случаем нормального, и стоит ли доводить до этого. С графиками и без формул

https://habr.com/ru/articles/976468/

#распределения_вероятностей #python #numpy #seaborn #статистический_анализ #случайность #нормальное_распределение #биноминальное_распределение #графики_и_диаграммы #гистограммы

New to data science? Dive into 5 hands‑on projects that walk you through practical Pandas EDA—cleaning missing values, spotting outliers, visualizing with seaborn, and more. Perfect for absolute beginners who want solid, reproducible workflows. Start exploring your own data today! #DataScience #Pandas #EDA #seaborn

🔗 https://aidailypost.com/news/5-data-science-projects-practical-pandas-eda-absolute-beginners

New to data science? Dive into 5 hands‑on projects that walk you through practical Pandas EDA—cleaning missing values, spotting outliers, visualizing with seaborn, and more. Perfect for absolute beginners who want solid, reproducible workflows. Start exploring your own data today! #DataScience #Pandas #EDA #seaborn

🔗 https://aidailypost.com/news/5-data-science-projects-practical-pandas-eda-absolute-beginners

Making Math Less Stressful with a Python Super-Calculator https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #WolframMathematica #datavisualization #SoftwareHacks #matplotlib #Seaborn #Pandas #python #maple #numpy #scipy #SymPy

Making Math Less Stressful with a Python Super-Calculator https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #WolframMathematica #datavisualization #SoftwareHacks #matplotlib #Seaborn #Pandas #python #maple #numpy #scipy #SymPy

Making Math Less Stressful with a Python Super-Calculator - In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-l... - https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #wolframmathematica #datavisualization #softwarehacks #matplotlib #seaborn #pandas #python #maple #numpy #scipy #sympy

Making Math Less Stressful with a Python Super-Calculator - In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-l... - https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #wolframmathematica #datavisualization #softwarehacks #matplotlib #seaborn #pandas #python #maple #numpy #scipy #sympy

[Перевод] Топ-6 Python-библиотек для визуализации

Команда Python for Devs подготовила перевод статьи о шести библиотеках Python для визуализации данных. Matplotlib, seaborn, Plotly, Altair, Pygal и Bokeh — у каждой свои сильные и слабые стороны: от академических статичных графиков до интерактивных дашбордов для бизнеса. Выбираем самую подходящую для различных кейсов.

https://habr.com/ru/articles/946750/

#визуализация_данных #Matplotlib #seaborn #Plotly #Altair #Pygal #Bokeh #интерактивные_графики

🐊 How do skills acquired through DataCamp translate to a better understanding of biodiversity data?

For Ibrahim Abdel Basir Gomaa, who completed courses in #Pandas, #Seaborn, machine learning, #SQL and statistics, these skills enabled him to confidently query large biodiversity datasets from sources like GBIF. 🔎

“One of my proudest achievements was developing a predictive model to assess species distribution patterns based on environmental factors...."

🐊 How do skills acquired through DataCamp translate to a better understanding of biodiversity data?

For Ibrahim Abdel Basir Gomaa, who completed courses in #Pandas, #Seaborn, machine learning, #SQL and statistics, these skills enabled him to confidently query large biodiversity datasets from sources like GBIF. 🔎

“One of my proudest achievements was developing a predictive model to assess species distribution patterns based on environmental factors...."

Ever thought about learning new data skills? 👩‍💻

Through our partnership with DataCamp Adel learned introductory skills in #Python, #Pandas and #Seaborn. 🎉

"Using DataCamp, I developed a biodiversity monitoring dashboard that streamlined data collection and reporting. This tool is now being used by my team to track species populations more effectively and make data-driven conservation decisions." 🌏

Apply for the 2025 programme: 🔗https://gbif.link/datacampdonates

#DCDonates

Ever thought about learning new data skills? 👩‍💻

Through our partnership with DataCamp Adel learned introductory skills in #Python, #Pandas and #Seaborn. 🎉

"Using DataCamp, I developed a biodiversity monitoring dashboard that streamlined data collection and reporting. This tool is now being used by my team to track species populations more effectively and make data-driven conservation decisions." 🌏

Apply for the 2025 programme: 🔗https://gbif.link/datacampdonates

#DCDonates

#30DayChartChallenge let's go! This #dataviz was for a bit of #Python practice, and I could *not* have sorted out the non-linear gradient for 1 > n > 0 without #claudeai. Made with #seaborn and patience 🎨 #FractionArt #ColorfulMath #PythonDataViz #FractionFunhouse

Инструменты Python для анализа данных на примере данных стриминг-сервиса

В данной статье рассмотрены некоторые методы и инструменты библиотек python для анализа данных. Используем три самые популярные библиотеки: Pandas, Numpy, Seaborn

https://habr.com/ru/articles/894530/

#pand #numpy #seaborn #python3 #analytics #jupyter_notebook

Compare the Best Data Visualisation Libraries for Python and Pandas

@jzsimon @arclight @JosetAEtzel

Check this fresh updated article:
https://codingidol.com/how-to-plot-in-python-without-matplotlib/

#Plotly #Seaborn #Bokeh #Altair #Python #python3 #pandas

#DataViz Decision-Making Guide

"How do you decide between #Plotly and #Seaborn?
* If you need interactive and dynamic visualizations, especially for dashboards or 3D data, Plotly is the way to go.
* If you’re focused on statistical analysis, creating publication-ready visuals, or conducting exploratory data analysis, Seaborn is likely your best choice."
by Amit Yadav: https://medium.com/@amit25173/plotly-vs-seaborn-f7207dd3e642

#dataDev #retrieval #dataMining

Nom.

https://fediscience.org/@tlohde/113412191058419280
@tlohde - Croissant Distribution🥐 📊

or, where am I most likely to have my next croissant, assuming (something something) independence from my previous croissant. 🥐^k * e^(-🥐) / k!
--
2d kernel density estimation of the location of bakeries (blue) and farms (red) across France.

Locations taken from OpenStreetMap, with #osmnx & plotted with #matplotlib & #seaborn. font: Borel, by Rosalie Wagner.

#30DayMapChallenge Day 2: Lines

Croissant Distribution🥐 📊

or, where am I most likely to have my next croissant, assuming (something something) independence from my previous croissant. 🥐^k * e^(-🥐) / k!
--
2d kernel density estimation of the location of bakeries (blue) and farms (red) across France.

Locations taken from OpenStreetMap (considered paying attention to the size of the farm, but didn't), with #osmnx & plotted with #matplotlib & #seaborn. font: Borel, by Rosalie Wagner.

#30DayMapChallenge Day 2: Lines

Are Power Rangers shows getting better? Episodes in 2019 and 2020 seem to be rated higher compared to previous seasons. I didn't even know the show was still going 👀 😅

My contribution to the #TidyTuesday challenge week 35 using the Kaggle Power Rangers data set. #Dataviz made in #python using #matplotlib + #seaborn.

🔗Full code (a bit messy though) https://github.com/Lisa-Ho/small-data-projects?tab=readme-ov-file#092024-power-rangers

Comic - Seaborn chapter 04
Pages 26,27,28
Story & Art by Dash Fox

Previous chapters:
Chapter 1: http://furaffinity.net/view/35710901

Chapter 2: http://furaffinity.net/view/42100017

Chapter 3:
http://rb.gy/ymrn4u

#furry #furryart #comic #TraditionalArt #fantasy #lizard #lion #battle #sword #dagger #spell #seaborn #bulge #armor #swordandsorcery #bara #muscular #muscles #manly #male #anthro #anthroart

Hey #spatial #R folks, is it possible to extract geometries from #ggplot as files? That is, the point, line, and polygon geometries in the graphs to #geopackage or #shapefile etc.

It is possible with #seaborn and #matplotlib, but that's Python not R. There's a nice and lightning fast #EdgeBundling technique in the newest ggplot, which is very promising for the #visualization of massive #mobility data.

There is also something in #HoloViews but I do not understand that library at all.

Late contribution to #TidyTuesday Canadian NHL Player Birth Dates. Trying to get back into the swing of #dataviz. 📊 🤩

Settled on a combination of stripplot, scatter and line to explore the average age of players over time. Looks like the league is getting a bit older overall.

Made in #python using #matplotlib and #seaborn, custom legend and managed to display a discontinued y-axis.

🔗 Full code (not pretty but works): https://github.com/Lisa-Ho/small-data-projects/blob/main/2024/2401-canadian-nhl-players/canadian-nhl-players.ipynb

@stefan_hessbrueggen @lavaeolus – Diese Nähe von #Vega und object-oriented #Seaborn war mir gar nicht klar, halte ich aber für potentiell vorteilhaft. Danke für den Hinweis!

Ansonsten ist mir ehrlich gesagt ganz pragmatisch eine klare API / saubere Code-Struktur viel wichtiger als das Programmier-Paradigma, das diese ermöglicht.

Und ich finde nicht, dass OOP irgendwie "noun"-zentriert wäre, denn jedes Objekt ("noun") hat ja viele Methoden ("verbs"), die man ständig anwendet.

So far, I really like the (relatively) new #object-oriented interface for #Seaborn, one of my favorite #visualization libraries in #Python.

It feels much cleaner, more logical, more compact, and there is indeed less need to go down to #Matplotlib for many tweaks to a plot.

Documentation here: https://seaborn.pydata.org/tutorial/objects_interface.html

Code and result for a very simple bar chart example below. Quite compact and very clean.