python读取nc数据绘图

from netCDF4 import Dataset
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt

path = "F:\\OCO2.SIF.all.daily.2001.nc"
csv_path = "F:\\test.csv"
dst = Dataset(path, mode='r', format="netCDF4")

 print(dst.variables.keys())
    data = dst.variables['all_daily_sif'][:]
    print(data.shape)
    # 输出结果如下:
    # dict_keys(['lat', 'lon', 'doy', 'all_daily_sif'])
    # (92, 360, 720)
    #可见有92个时间序列，经度(lon)、纬度(lat)的取值有720,360个

    # # 查看数据经纬度范围，经度-179.75~179.75，其中负值为西经，正值为东经；纬度正为北纬，负为南纬
    # # 格点分辨率为0.5度
    long = dst.variables['lon'][:]
    lati = dst.variables['lat'][:]
    print(long[0], long[-1], lati[0], lati[-1])
    print(long.shape, lati.shape)

 # plt对某个doy的全球sif值作图。左半部分为西半球，右边是东半球
    # 选了doy为10的sif数据作图
    plt.contourf(long, lati, data[10, :, :] )
    plt.colorbar(label="Sif", orientation="horizontal")
    plt.show()

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt

    lat = dst.variables['lat'][:]
    lon = dst.variables['lon'][:]
    data = dst.variables['all_daily_sif'][:]    
    data[10] = data[10]
    # use .shape function to check that arrays have
    # the correct size.
    # e.g. lon.shape
    print(data[10].shape)

    lon0 = lon.mean()
    lat0 = lat.mean()
    # 设置投影方式：cyl为圆柱投影、还可设置merc为mercator投影 llcrnrlat为起始lat；urcrnrlat为终止lat
    # m = Basemap(projection='merc', llcrnrlat=lat[0], urcrnrlat=lat[-1], \
    #              llcrnrlon=lon[0], urcrnrlon=lon[-1], ax=ax1)
   # 参数 "resolution" 用于控制地图面积边缘的精细程度，有'l'和'h'两种取值
    m = Basemap(lat_0=lat0, lon_0=lon0,projection='cyl',resolution='l')
    # 绘制等经纬度线 纬度每隔20度画一条线，且标注经纬度
    m.drawparallels(np.arange(-90., 91., 20.), labels=[1, 0, 0, 0], fontsize=10)
    m.drawmeridians(np.arange(-180., 181., 40.), labels=[0, 0, 0, 1], fontsize=10)
    m.drawcoastlines()# 绘制海岸线
    # m.drawcountries(linewidth=0.25)  # 绘制国界线
    # m.readshapefile('F:\E\data\grass_yield\shp\quhua\\省', 'states')  # 读取中国各省边界，并绘图

    lon, lat = np.meshgrid(lon, lat)
    xi, yi = m(lon, lat)
    # cmap是颜色，还可选‘jet'、‘spring'、‘winter'、'summer'、'autumn'
    cs = m.contourf(xi, yi, data[10],  cmap='summer')
    # pad指位置，
    cbar = m.colorbar(cs, location='bottom', pad="10%",format='%.1f')
    # cbar = m.colorbar(C, 'right', ticks=np.arange(-128, 128, 40), format='%.1f')
    font1 = {'family': 'DejaVu Sans', 'weight': 'normal', 'size': 16}
    plt.title('CSIF', font1)
    plt.show()