Skip to main content

gispandas

Project description

GisPandas针对栅格数据进行统计的python包

GisPandas是一个为栅格、矢量数据处理、分析以及可视化而开发的Python包。GisPandas为常见栅格矢量数据提供了快速而简洁的gis操作方法,代码简洁、高效、灵活、易用,可以用简洁的代码实现复杂的数据任务。

主要功能

目前,GisPandas主要提供以下方法:

1.栅格数据进行阿尔伯斯等面积投影,根据矢量区划计算面积并导出json。

2.种植结构变化,自动对齐,导出栅格数据和统计json。

3.gee下载数据的后处理主要包括:栅格数据镶嵌并压缩。

4.矢量数据写入四至、中心经纬度等属性,矢量简化,文本矢量化等。

5.栅格数据像素对齐、裁剪、重采样、投影、插值、切片、格式转换等。

安装

pip install gispandas

相关链接

本项目的github页面:https://github.com/mxhou/gispandas

有bug请在这个页面提交:https://github.com/mxhou/gispandas/issues

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gispandas-0.1.9.tar.gz (11.9 kB view details)

Uploaded Source

Built Distribution

gispandas-0.1.9-py3-none-any.whl (13.9 kB view details)

Uploaded Python 3

File details

Details for the file gispandas-0.1.9.tar.gz.

File metadata

  • Download URL: gispandas-0.1.9.tar.gz
  • Upload date:
  • Size: 11.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.16

File hashes

Hashes for gispandas-0.1.9.tar.gz
Algorithm Hash digest
SHA256 b2d357427b370478670b0d7b5cea909ee065cc7bcfeefe47e05e6b09f07390fd
MD5 d65754a27476d89bcd0154d492a05804
BLAKE2b-256 68f2f646a9fa2f8a218f15e7b48cec65bb743b4ce9e9f6773d34c348c4a330ca

See more details on using hashes here.

File details

Details for the file gispandas-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: gispandas-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 13.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.16

File hashes

Hashes for gispandas-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 886d7548fba4a6f195c74affbc3b118e59ad56f2ace60d0288a2e1d4eaf3adcf
MD5 9af4b749dcb95a60b32fa28f31cbbe00
BLAKE2b-256 a83e7ca770482e8f2cea30f351e97a823e97d87a5e33d2cf5e8cee2f2f66c386

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page