#!/usr/bin/env python# -*- coding: utf-8 -*-# @File : map02.py# @Author: huifer# @Date : 2018/6/28import foliumimport pandas as pdimport requestsimport matplotlib.pyplot as pltimport cartopy.crs as ccrsimport zipfileimport cartopy.io.shapereader as shapereadfrom matplotlib import cmfrom cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatterimport osdataurl = "http://image.data.cma.cn/static/doc/A/A.0012.0001/SURF_CHN_MUL_HOR_STATION.xlsx"shpurl = "http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_0_countries.zip"def download_file(url): """ 根据url下载文件 :param url: str """ r = requests.get(url, allow_redirects=True) try: open(url.split('/')[-1], 'wb').write(r.content) except Exception as e: print(e)def degree_conversion_decimal(x): """ 度分转换成十进制 :param x: float :return: integer float """ integer = int(x) integer = integer + (x - integer) * 1.66666667 return integerdef unzip(zip_path, out_path): """ 解压zip :param zip_path:str :param out_path: str :return: """ zip_ref = zipfile.ZipFile(zip_path, 'r') zip_ref.extractall(out_path) zip_ref.close()def get_record(shp, key, value): countries = shp.records() result = [country for country in countries if country.attributes[key] == value] countries = shp.records() return resultdef read_excel(path): data = pd.read_excel(path) # print(data.head(10)) # 获取几行 # print(data.ix[data['省份']=='浙江',:].shape[0]) # 计数工具 # print(data.sort_values('观测场拔海高度（米）',ascending=False).head(10))# 根据值排序 # 判断经纬度是什么格式(度分 、 十进制) 判断依据 %0.2f 是否大于60 # print(data['经度'].apply(lambda x:x-int(x)).sort_values(ascending=False).head()) # 结果判断为度分保存 # 坐标处理 data['经度'] = data['经度'].apply(degree_conversion_decimal) data['纬度'] = data['纬度'].apply(degree_conversion_decimal) ax = plt.axes(projection=ccrs.PlateCarree()) ax.set_extent([70, 140, 15, 55]) ax.stock_img() ax.scatter(data['经度'], data['纬度'], s=0.3, c='g') # shp = shaperead.Reader('ne_10m_admin_0_countries/ne_10m_admin_0_countries.shp') # # 抽取函数 州：国家 # city_list = [country for country in countries if country.attributes['ADMIN'] == 'China'] # countries = shp.records() plt.savefig('test.png') plt.show()def gdp(shp_path): """ GDP 着色图 :return: """ shp = shaperead.Reader(shp_path) cas = get_record(shp, 'SUBREGION', 'Central Asia') gdp = [r.attributes['GDP_MD_EST'] for r in cas] gdp_min = min(gdp) gdp_max = max(gdp) ax = plt.axes(projection=ccrs.PlateCarree()) ax.set_extent([45, 90, 35, 55]) for r in cas: color = cm.Greens((r.attributes['GDP_MD_EST'] - gdp_min) / (gdp_max - gdp_min)) ax.add_geometries(r.geometry, ccrs.PlateCarree(), facecolor=color, edgecolor='black', linewidth=0.5) ax.text(r.geometry.centroid.x, r.geometry.centroid.y, r.attributes['ADMIN'], horizontalalignment='center', verticalalignment='center', transform=ccrs.Geodetic()) ax.set_xticks([45, 55, 65, 75, 85], crs=ccrs.PlateCarree()) # x坐标标注 ax.set_yticks([35, 45, 55], crs=ccrs.PlateCarree()) # y 坐标标注 lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax.xaxis.set_major_formatter(lon_formatter) ax.yaxis.set_major_formatter(lat_formatter) plt.title('GDP TEST') plt.savefig("gdb.png") plt.show()def run_excel(): if os.path.exists("SURF_CHN_MUL_HOR_STATION.xlsx"): read_excel("SURF_CHN_MUL_HOR_STATION.xlsx") else: download_file(dataurl) read_excel("SURF_CHN_MUL_HOR_STATION.xlsx")def run_shp(): if os.path.exists("ne_10m_admin_0_countries"): gdp("ne_10m_admin_0_countries/ne_10m_admin_0_countries.shp") else: download_file(shpurl) unzip('ne_10m_admin_0_countries.zip', "ne_10m_admin_0_countries") gdp("ne_10m_admin_0_countries/ne_10m_admin_0_countries.shp")if __name__ == '__main__': # download_file(dataurl) # download_file(shpurl) # cas = get_record('SUBREGION', 'Central Asia') # print([r.attributes['ADMIN'] for r in cas]) # read_excel('SURF_CHN_MUL_HOR_STATION.xlsx') # gdp() run_excel() run_shp() 
