d3 visualization tutorial

] = uin[::-1]; U[:,-1] = Uin[::-1,0]v = Np.zeros ((vin.shape[0],vin.shape[1]+1), np.float64) v[:,0:-1] = vin[::-1]; V[:,-1] = vin[::-1,0]longitudes.append (360.); longitudes = Np.array (longitudes) lons, lats = Np.meshgrid (longitudes,latitudes) 5) Set and draw the diagram m = Basemap (resolution= ' C ', projection= ' ortho ', lat_0=60.,lon_0=-60.) FIG1 = Plt.figure (figsize= (8,10)) ax = Fig1.add_axes ([0.1,0.1,0.8,0.8]) Clevs = Np.arange (960,1061,5) x, y = m (lons, lats) Parallels = Np.arange

,timevar) 3) Data preprocessing sst = dataset.variables['sst'][timeindex,:].squeeze()ice = dataset.variables['ice'][timeindex,:].squeeze()lats = dataset.variables['lat'][:]lons = dataset.variables['lon'][:]lons, lats = np.meshgrid(lons,lats) 4) set and draw an illustration fig = plt.figure()ax = fig.add_axes([0.05,0.05,0.9,0.9])m = Basemap(projection='kav7',lon_0=0,resolution=None)m.drawmapboundary(fill_color='0.3')im1 = m.pcolormesh(lons,lats,sst,shading='flat',cmap=plt.cm.jet,latlon=True)im2 =

This article mainly introduces examples of Python Tornado framework to achieve data visualization of the tutorial, Tornado is an asynchronous development framework for high man, the need for friends can refer to the Expansion module used XLRD: In the Python language, read the extension tool for Excel. You can implement the specified form, read the specified cell. Must be installed before use. Download