我不确定这实际上是不是一个数学问题,但为什么没有情节箱形图胡须等于熊猫数据框架方法quantile(0.01)
或(0.99)
或类似?原因绝不是,分位数参数不匹配,因为一些计算结果较高而其他计算结果较低。
THX
for col in df.columns:
data.append( go.Box( y=df[col], name=getclearname(col), showlegend=False, boxmean='sd' ) )
df.rename(columns = {col:getclearname(col)}, inplace = True)
df=df.fillna(100)
#print(df)
data.append( go.Scatter( x = df.columns, y = df.median(), mode='marker', name='median' ) )
data.append( go.Scatter( x = df.columns, y = df.quantile(0.25), mode='marker', name='lower quantile' ) )
data.append( go.Scatter( x = df.columns, y = df.quantile(0.75), mode='marker', name='upper quantile' ) )
data.append( go.Scatter( x = df.columns, y = df.fillna(100).quantile(0.01), mode='marker', name='lower percentile' ) )
data.append( go.Scatter( x = df.columns, y = df.fillna(100).quantile(0.99), mode='marker', name='upper percentile' ) )
layout=go.Layout(title=""+cata+" - local spatial properties on placements<br>"+constraintdesc,yaxis=dict(
title='percentage of range between flat extremes'))
fig = go.Figure(data=data, layout=layout)
py.offline.iplot(fig, filename='pandas-box-plot')
导致以下奇怪的行为: downloaded plot from notebook