1. 程式人生 > >【python】關於excel和shp的使用在matplotlib

【python】關於excel和shp的使用在matplotlib

關於excel和shp的使用在matplotlib

  • 使用pandas 對excel進行簡單操作
  • 使用cartopy 讀取shpfile 展示到matplotlib中
  • 利用shpfile檔案中的一些欄位進行一些著色處理
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @File  : map02.py
# @Author: huifer
# @Date  : 2018/6/28
import folium
import pandas as pd
import requests
import matplotlib.pyplot as
plt import cartopy.crs as ccrs import zipfile import cartopy.io.shapereader as shaperead from matplotlib import cm from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter import os dataurl = "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): """ 根據url下載檔案 :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): """ 度分轉換成十進位制 :param x: float :return: integer float """
integer = int(x) integer = integer + (x - integer) * 1.66666667 return integer def unzip(zip_path, out_path): """ 解壓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 result def read_excel(path): data = pd.read_excel(path) # print(data.head(10)) # 獲取幾行 # print(data.ix[data['省份']=='浙江',:].shape[0]) # 計數工具 # print(data.sort_values('觀測場拔海高度(米)',ascending=False).head(10))# 根據值排序 # 判斷經緯度是什麼格式(度分 、 十進位制) 判斷依據 %0.2f 是否大於60 # print(data['經度'].apply(lambda x:x-int(x)).sort_values(ascending=False).head()) # 結果判斷為度分儲存 # 座標處理 data['經度'] = data['經度'].apply(degree_conversion_decimal) data['緯度'] = data['緯度'].apply(degree_conversion_decimal) ax = plt.axes(projection=ccrs.PlateCarree()) ax.set_extent([70, 140, 15, 55]) ax.stock_img() ax.scatter(data['經度'], data['緯度'], s=0.3, c='g') # shp = shaperead.Reader('ne_10m_admin_0_countries/ne_10m_admin_0_countries.shp') # # 抽取函式 州:國家 # 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 著色圖 :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座標標註 ax.set_yticks([35, 45, 55], crs=ccrs.PlateCarree()) # y 座標標註 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()

excelTest

GDB