fig,ax=plt.subplots()  #一个画布

fig,(ax1,ax2) = plt.subplots( ncols=2)  #两个画布

fig,(ax1,ax2) = plt.subplots(ncols=2) #一个画布，两个轴

sn.barplot(data=train,x='holiday',y='cnt',hue='weathersit',ax=ax1) #hue='weathersit'，通过weathersit来区分

sn.barplot(data=train,x='workingday',y='cnt',hue='season',ax=ax2) #hue='season'，通过season来区分

fig,ax = plt.subplots()

sn.pointplot(data=train[['dayofyear','cnt', 'yr']],x='dayofyear',y='cnt',hue='yr',ax=ax)

# hue='yr'指的是区分开年份。hue指颜色

ax.set(title="dayly distribution of counts")

plt.show()

corrMatt = train[["temp","atemp","hum","windspeed","cnt"]].corr()

mask = np.array(corrMatt)

mask[np.tril_indices_from(mask)] = False

sn.heatmap(corrMatt, mask=mask,

      vmax=1, square=True,annot=True)

plt.show()

sn.scatterplot(x=train.GrLivArea,y=train.SalePrice)

plt.title("Looking for outliers") #图形标题

plt.show()