5.直方图

histogram

import plotly.offline as of
import plotly.graph_objs as go
inport numpy as np

s1 = np.random.RandomState(1)
x = s1.randn(1000)

data = [
	go.Histogram(
		x = x,
		histnorm = 'probability'
	)
]
'''
histnorm ----> 如果我们设定histnorm = 'probability' 则纵坐标变为落入区间内的样本频率
               默认状态下表示直方图纵坐标落入区间内的样本数目
'''
fig = go.Figure(data=data)
of.init_notebook_mode()
of.iplot(fig)

重叠垂直直方图
我们在说说重叠垂直直方图的绘制
需要在Layout中设置barmode属性，将其改为‘overlay’
如果我们不对其进行设置，会出现Plotly默认将两个直方图的柱状宽度强制变窄
以满足重叠部分的显示需求。
下面我们来看下，数据有Numpy随机生成

s1 = np.random.RandomState(1)
x0 = s1.randn(1000)
x1 = s1.chisquare(5, 1000)

trace1 = go.Histogram(
	x = x0,
	histnorm = 'probability', # 出现的频率
	opacity = 0.75
)
trace2 = go.Histogram(
	x = x1,
	histnorm = 'probability',
	opacity = 0.75
)
data = [trace1, trace2]

layout = go.Layout(
	barmode = 'overlay'
)
'''
barmode ----> layout中的参数, barmode='overlay'时，两个图会重叠
                              barmode='stack'时，两个图会进行堆叠
'''
fig = go.Figure(data = data, layout = layout)
of.init_notebook_mode()
of.iplot(fig)

层叠直方图
绘制层叠直方图同样需要设置barmode属性，将其设置为‘stack’
下面我们看一下使用Numpy随机生成相同的正态分布数据图的叠加效果

s1.np.random.RandomState(1)
x0 = s1.randn(1000)
x1 = s1.randn(1000)

trace1 = go.Histogram(
	x = x0
)
trace2 = go.Histogram(
	x = x1
)
data = [trace1, trace2]
layout = go.Layout(
	barmode = 'stack'
)
fig = go.Figure(data=data, layout=layout)
of.init_notebook_mode()
of.iplot(fig)