plt.hist(x, bins=10, range=None, normed=False, weights=None, cumulative=False, bottom=None, 
histtype='bar', align='mid', orientation='vertical',rwidth=None, log=False, color=None, label=None, 
stacked=False, hold=None, data=None, **kwargs)

# 直方圖+密度圖
s = pd.Series(np.random.randn(1000))
s.hist(bins = 20,
       histtype = 'bar',
       align = 'mid',
       orientation = 'vertical',
       alpha=0.5,
       normed =True)
# bin：箱子的寬度
# normed 標準化
# histtype 風(fēng)格，bar，barstacked，step，stepfilled
# orientation 水平還是垂直{‘horizontal’, ‘vertical’}
# align : {‘left’, ‘mid’, ‘right’}, optional(對齊方式)

# 密度圖
s.plot(kind='kde',style='k--')

image.png

# 堆疊直方圖

plt.figure(num=1)
df = pd.DataFrame({'a': np.random.randn(1000) + 1, 'b': np.random.randn(1000),
                    'c': np.random.randn(1000) - 1, 'd': np.random.randn(1000)-2},
                   columns=['a', 'b', 'c','d'])
# 使用DataFrame.plot.hist()和Series.plot.hist()方法繪制
# stacked：是否堆疊
df.plot.hist(stacked=True,
             bins=20,
             colormap='Greens_r',
             alpha=0.5,
             grid=True)


# 生成多個直方圖
df.hist(bins=50)

image.png