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import PIL

image_frames = [] # creating a empty list to be appended later on
days = np.arange(1,365)

for k in days:
    new_fram = PIL.Image.open(r'path\where\images\are\downloaded' + '\\' + str(k) + '.jpg') 
    image_frames.append(new_fram)

image_frames[0].save('tave_timelapse.gif',format='GIF',

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# this will create 365 images in the path given 
# please set the path before executing 
lon, lat = np.meshgrid(long,lats)
x,y = mp(lon,lat)
plt.figure(figsize=(6,8))

# loop for all the days 
days = np.arange(0,365)  # for considering all days of the year

for i in days:

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lon, lat = np.meshgrid(long,lats)  #this converts coordinates into 2D arrray
x,y = mp(lon,lat) #mapping them together 
plt.figure(figsize=(6,8)) #figure size 
c_scheme = mp.pcolor(x,y,np.squeeze(tave[0,:,:]),cmap = 'jet') # [0,:,:] is for the first day of the year

# consider this as the outline for the map that is to be created 
mp.drawcoastlines()
mp.drawstates()
mp.drawcountries()

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mp = Basemap(projection='merc',
             llcrnrlon=68.42,   # lower longitude
             llcrnrlat=7.45,    # lower latitude
             urcrnrlon=99.98,   # uppper longitude
             urcrnrlat=37.78,   # uppper latitude
            resolution = 'i')

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lats = data.variables['lat'][:]  
longs = data.variables['lon'][:]
time = data.variables['time'][:]

tave = data.variables['tave'][:]

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file = '1966.nc' # mention the path to the downloaded file
data = Dataset(file, mode='r') # read the data 
print(type(data)) # print the type of the data 
print(data.variables.keys()) # print the variables in the data

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