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

# make up some data for scatter plot
df = pd.read_csv('dust.csv')
x = df[['y']].values
y = df[['x']].values
fig = plt.gcf()
fig.set_size_inches(8, 6.5)

m = Basemap(projection='mill',
            llcrnrlat = 6.5,#llcrncrlat=lower left corner latitude
            llcrnrlon = 66,
            urcrnrlat = 36,
            urcrnrlon = 98,
            resolution = 'l')

#m.bluemarble(scale=0.2)   # full scale will be overkill
m.drawcoastlines(linewidth=1)# add coastlines
m.drawcountries(linewidth=1)

# transform coordinates
#plt.subplot(221)
x,y=m(x,y)
plt.scatter(x, y,s=df.iloc[1:,2], alpha = 0.5, cmap='viridis')
plt.colorbar()

plt.show()

**问题：**如何在底图的顶部绘制不同密度的散点图？
**数据：**我有印度各城市的纬度和经度沿着各年的污染水平。
**方法：**最初，我将数据结构分配给变量'df'。将纬度指定为“y”，将经度指定为“x”。由于纬度和经度也拥有变量'y'和'x'，在其中，我使用'df['x'].values'来单独获取数值。考虑到印度的几何位置，我绘制了这张Map.下一个设置是将这些纬度和经度作为Map的变量。这一点至关重要，否则我无法观察散点图。以颜色作为第三个变量，我绘制了散点图，污染水平具有不同的密度。

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

# make up some data for scatter plot
df = pd.read_csv('dust.csv')
x = df[['y']].values
y = df[['x']].values
fig = plt.gcf()
fig.set_size_inches(8, 6.5)

m = Basemap(projection='mill',
            llcrnrlat = 6.5,#llcrncrlat=lower left corner latitude
            llcrnrlon = 66,
            urcrnrlat = 36,
            urcrnrlon = 98,
            resolution = 'l')

#m.bluemarble(scale=0.2)   # full scale will be overkill
m.drawcoastlines(linewidth=1)# add coastlines
m.drawcountries(linewidth=1)

# transform coordinates
#plt.subplot(221)
x,y=m(x,y)
plt.scatter(x, y,s=df.iloc[1:,2], alpha = 0.5, cmap='viridis')
plt.colorbar()

plt.show()