项目介绍

carnot-technologies/MapVisualizations 是一个托管在 GitHub 上的开源项目,主要使用 Jupyter Notebook 编写,目前获得 51 个 Star、16 次 Fork。

仓库全名
carnot-technologies/MapVisualizations
Star 数
51
Fork 数
16

README 摘要

Map-based Visualizations in Python :star: Star us on GitHub — it helps! This is the helper repo for the series of map-based visualization tutorial posts on medium, covering several popular python libraries that are generally used for geo-spatial data visualization. Table of contents About Types of Visualizations Libraries Covered Comparison of the libraries Auxiliary Concepts Covered Contributing to this repo About…

完整内容见 GitHub 原始 README 或本页 。

常见问题

MapVisualizations 用什么语言开发?

主要使用 Jupyter Notebook 编写,目前有 51 个 Star。

如何获取 MapVisualizations 的源码?

可以直接克隆仓库:git clone https://github.com/carnot-technologies/MapVisualizations.git,默认分支为 master;安装与运行步骤见仓库 README。

MapVisualizations 最近还在维护吗?

仓库最近一次更新为 2020年8月12日,当前没有未关闭的 Issue;Star 数为 51,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

Helper repo for the 'Map-based Visualizations in Python' tutorial series on Medium.

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
86
价值分
35
活跃状态
活跃

语言占比

HTML
Jupyter Notebook

README

Map-based Visualizations

Map-based Visualizations in Python

HitCount PRs Welcome

:star: Star us on GitHub — it helps!
This is the helper repo for the series of map-based visualization tutorial posts on medium, covering several popular python libraries that are generally used for geo-spatial data visualization.

Table of contents

About

Map-based visualizations are an essential aspect of any data-presentation/ inference. Geo-spatial visualizations become all the more important for IoT companies like Carnot which have their devices scattered across different geographies. We at Carnot realized the need for having a robust map-based visualization infrastructure for all our present and future requirements. When we started building this infrastructure, we realized that there are way too many libraries available for map visualizations and several detailed tutorials for each library. However, what wasn’t readily available was a comparison of the different libraries and a guide on which library is best suited for a particular application.

Hence, we started off with one library at a time, determined what it was best suited for, and then moved on to the next. We kept doing this exercise till we generated nearly all the types of visualizations we could envision. This repo is a helper repo for the series of Medium blog posts on map-based visualizations, where we share a summary of our learning during this entire exercise. It will hopefully serve as a guide to people who find themselves as overwhelmed with choices as we were at the start of our infra-building exercise.

In order to get an overview and comparison of different libraries, Click Here.

Types of Visualizations

  • Scatter
  • Choropleth

Libraries Covered

Library Visualization Covered Visualization Preview Tutorial View Jupyter Notebook
Cartopy Scatter with custom map background Click Here Click Here
GeoPandas Choropleth with shapefile Click Here Click Here
Plotly Interactive Choropleth with GeoJSON Click Here Click Here
Plotly + Mapbox Interactive Choropleth with GeoJSON and base-map Click Here Click Here
Plotly + Mapbox Interactive Scatter with base-map Click Here Click Here
Plotly + Datashader Partly Interactive Large-data Scatter with base-map Click Here Click Here
Folium Partly Interactive Choropleth with TopoJSON Click Here Click Here

Auxiliary Concepts Covered

Along with the tutorial of each library, several auxiliary concepts and processes are covered in the tutorials. They are listed below, linking to the tutorial in which they are covered.

Contributing to this repo

All suggestions, feedback and pull requests are welcome. However, please remember the context of this repo before submitting any contributions. This repo is intended to be a helper repo for the series of medium tutorial posts on the different map-based visualization libraries. At the same time, this repo and the blog posts intend to help the users identify the correct library for their user-case, out of all the available options. Finally, when introducing the users to a new library, the USP and the application areas of that library need to be explicitly made clear to the users. Your contributions should align with these objectives in kind and in spirit.

评论

暂无评论