<h4>
cnmaps 是一个可以让中国地图画起来更丝滑的地图类python扩展包
</h4>
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## 安装
安装 cnmaps 需要满足 Python 的解释器在 3.9 版本及以上。
### 使用pip安装
cnmaps 最简单也最快的安装方法是使用 pip 来安装 cnmaps： `$ pip install -U cnmaps`
### 使用conda安装
你也可以使用 conda 安装： ``$ conda install -c conda-forge cnmaps``
## 快速开始
### 绘制国界
用最简单直接的方式，来绘制你的第一张中国地图。
```python
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from cnmaps import get_adm_maps, draw_maps
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
draw_maps(get_adm_maps(level='国'))
plt.show()
```
### 绘制省界
cnmaps还可以绘制各省（特区/直辖市）的地图
```python
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from cnmaps import get_adm_maps, draw_maps
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
draw_maps(get_adm_maps(level='省'), linewidth=0.8, color='r')
plt.show()
```
### 绘制市界
cnmaps可以绘制市级的行政区地图。
```python
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from cnmaps import get_adm_maps, draw_maps
fig = plt.figure(figsize=(15,15))
ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
draw_maps(get_adm_maps(level='市'), linewidth=0.5, color='g')
plt.show()
```
### 绘制区县界
cnmaps可以绘制区县级的行政区地图。
```python
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from cnmaps import get_adm_maps, draw_maps
fig = plt.figure(figsize=(20,20))
ax = fig.add_subplot(111, projection=ccrs.PlateCarree())
draw_maps(get_adm_maps(level='区县'), linewidth=0.8, color='r')
plt.show()
```
## 使用指南
针对本项目更多的使用方法，我们还有一份更详细的文档：[cnmaps使用指南](https://cnmaps.readthedocs.io/zh_CN/latest/index.html)
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"description": "<h4>\n cnmaps \u662f\u4e00\u4e2a\u53ef\u4ee5\u8ba9\u4e2d\u56fd\u5730\u56fe\u753b\u8d77\u6765\u66f4\u4e1d\u6ed1\u7684\u5730\u56fe\u7c7bpython\u6269\u5c55\u5305\n</h4>\n\n<a href=\"https://github.com/cnmetlab/cnmaps/actions/workflows/python-package-conda.yml\">\n<img src=\"https://github.com/cnmetlab/cnmaps/actions/workflows/python-package-conda.yml/badge.svg?branch=main\"\n alt=\"Pytest\" /></a>\n\n<a href=\"https://github.com/cnmetlab/cnmaps/actions/workflows/pypi-publish.yml\">\n<img src=\"https://github.com/cnmetlab/cnmaps/actions/workflows/pypi-publish.yml/badge.svg\" \n alt=\"Pypi publish\"/> </a>\n\n<a href=\"https://anaconda.org/conda-forge/cnmaps\">\n<img src=\"https://anaconda.org/conda-forge/cnmaps/badges/version.svg\"\n alt=\"Anaconda\" /></a>\n\n<a href=\"https://anaconda.org/conda-forge/cnmaps\">\n<img src=\"https://anaconda.org/conda-forge/cnmaps/badges/platforms.svg\" /> </a>\n\n<a href=\"https://anaconda.org/conda-forge/cnmaps\">\n<img 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\u6700\u7b80\u5355\u4e5f\u6700\u5feb\u7684\u5b89\u88c5\u65b9\u6cd5\u662f\u4f7f\u7528 pip \u6765\u5b89\u88c5 cnmaps\uff1a `$ pip install -U cnmaps`\n\n### \u4f7f\u7528conda\u5b89\u88c5\n\u4f60\u4e5f\u53ef\u4ee5\u4f7f\u7528 conda \u5b89\u88c5\uff1a ``$ conda install -c conda-forge cnmaps``\n\n\n## \u5feb\u901f\u5f00\u59cb\n\n### \u7ed8\u5236\u56fd\u754c\n\n\u7528\u6700\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\uff0c\u6765\u7ed8\u5236\u4f60\u7684\u7b2c\u4e00\u5f20\u4e2d\u56fd\u5730\u56fe\u3002 \n\n```python\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\nfrom cnmaps import get_adm_maps, draw_maps\n\nfig = plt.figure(figsize=(10,10))\nax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n\ndraw_maps(get_adm_maps(level='\u56fd')) \nplt.show()\n```\n\n### \u7ed8\u5236\u7701\u754c\n\ncnmaps\u8fd8\u53ef\u4ee5\u7ed8\u5236\u5404\u7701\uff08\u7279\u533a/\u76f4\u8f96\u5e02\uff09\u7684\u5730\u56fe\n\n```python\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\nfrom cnmaps import get_adm_maps, draw_maps\n\nfig = plt.figure(figsize=(10,10))\nax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n\ndraw_maps(get_adm_maps(level='\u7701'), linewidth=0.8, color='r') \n\nplt.show()\n```\n\n### \u7ed8\u5236\u5e02\u754c\n\ncnmaps\u53ef\u4ee5\u7ed8\u5236\u5e02\u7ea7\u7684\u884c\u653f\u533a\u5730\u56fe\u3002\n\n```python\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\nfrom cnmaps import get_adm_maps, draw_maps\n\nfig = plt.figure(figsize=(15,15))\nax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n\ndraw_maps(get_adm_maps(level='\u5e02'), linewidth=0.5, color='g') \n\nplt.show()\n```\n\n### \u7ed8\u5236\u533a\u53bf\u754c\n\ncnmaps\u53ef\u4ee5\u7ed8\u5236\u533a\u53bf\u7ea7\u7684\u884c\u653f\u533a\u5730\u56fe\u3002\n\n```python\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\nfrom cnmaps import get_adm_maps, draw_maps\n\nfig = plt.figure(figsize=(20,20))\nax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n\ndraw_maps(get_adm_maps(level='\u533a\u53bf'), linewidth=0.8, color='r') \n\nplt.show()\n```\n\n## \u4f7f\u7528\u6307\u5357\n\n\u9488\u5bf9\u672c\u9879\u76ee\u66f4\u591a\u7684\u4f7f\u7528\u65b9\u6cd5\uff0c\u6211\u4eec\u8fd8\u6709\u4e00\u4efd\u66f4\u8be6\u7ec6\u7684\u6587\u6863\uff1a[cnmaps\u4f7f\u7528\u6307\u5357](https://cnmaps.readthedocs.io/zh_CN/latest/index.html)\n\n",
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