为什么我在 python 中的散点图在使用“s”参数时给出全红色

Question

当我将 s 参数用于气泡整个图时为红色 当使用“s”参数时# Import numpy as npimport numpy as np# Store pop as a numpy array: np_popnp_pop = np.array(pop)# Double np_popnp_pop = np_pop*2# Update: set s argument to np_popplt.scatter(gdp_cap, life_exp ,alpha = 0.8,color ='red', s = np_pop)# Previous customizationsplt.xscale('log') plt.xlabel('GDP per Capita [in USD]')plt.ylabel('Life Expectancy [in years]')plt.title('World Development in 2007')plt.xticks([1000, 10000, 100000],['1k', '10k', '100k'])# Display the plotplt.show()当不使用s参数时，它显示恒定的气泡大小，但是当不使用s参数时，我希望气泡大小取决于填充量 ，所以不显示红色# Import numpy as npimport numpy as np# Store pop as a numpy array: np_popnp_pop = np.array(pop)# Double np_popnp_pop = np_pop*2# Update: set s argument to np_popplt.scatter(gdp_cap, life_exp ,alpha = 0.8,color ='red')# Previous customizationsplt.xscale('log') plt.xlabel('GDP per Capita [in USD]')plt.ylabel('Life Expectancy [in years]')plt.title('World Development in 2007')plt.xticks([1000, 10000, 100000],['1k', '10k', '100k'])# Display the plotplt.show()

Answer 1

尝试使用较小的np_pop：

np_pop = np_pop/5000 # or any other value that decrease the population(?)