Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
What's the difference between this Python project and similar ones?
Several built-in themes that improve on the default matplotlib aesthetics
Tools for choosing color palettes to make beautiful plots that reveal patterns in your data
Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data
Tools that fit and visualize linear regression models for different kinds of independent and dependent variables
Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices
A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate
High-level abstractions for structuring grids of plots that let you easily build complex visualizations
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/713
**Author:** [@sojin](https://github.com/sojin)
**Created:** 8/28/2016
**Status:** ✅ Merged
**Merged:** 9/13/2016
**Merged by:** [@vinta](https://github.com/vinta)
**Base:** `master` ← **Head:** `master`
---
### 📝 Commits (1)
- [`8d07d55`](https://github.com/vinta/awesome-python/commit/8d07d55f406c1fd6e981626fb9693614b8b10454) Add seaborn
### 📊 Changes
**1 file changed** (+1 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+1 -0)
</details>
### 📄 Description
## What is this Python project?
Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
## What's the difference between this Python project and similar ones?
- Several built-in themes that improve on the default matplotlib aesthetics
- Tools for choosing color palettes to make beautiful plots that reveal patterns in your data
- Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data
- Tools that fit and visualize linear regression models for different kinds of independent and dependent variables
- Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices
- A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate
- High-level abstractions for structuring grids of plots that let you easily build complex visualizations
Anyone who agrees with this pull request could vote for it by adding a :+1: to it, and usually, the maintainer will merge it when votes reach **20**.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
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📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/713
Author: @sojin
Created: 8/28/2016
Status: ✅ Merged
Merged: 9/13/2016
Merged by: @vinta
Base:
master← Head:master📝 Commits (1)
8d07d55Add seaborn📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
What is this Python project?
Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
What's the difference between this Python project and similar ones?
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.