散景面积图无法绘制

问题描述

由于某种原因，我无法在bokeh中绘制面积图.

I am unable to plot the area chart in bokeh for some reason..

下面是用于此操作的代码.

Below is the code used for the same..

from bokeh.charts import Area, show, output_file

Areadict = dict(
    I = df['IEXT'],
    Date=df['Month'],
    O = df['OT']
)

 area = Area(Areadict, x='Date', y=['I','O'], title="Area Chart",
             legend="top_left",
               xlabel='time', ylabel='memory')

 output_file('area.html')
 show(area)

我所能看到的都是是否绘制了日期轴，但没有看到我感兴趣的两个区域图的迹象.请指教

All i see if the date axis getting plotted, but no signs of the two areacharts that I am interested in.Please advise

推荐答案

我建议您查看 Holoviews 在Bokeh之上构建的非常高级的API，并得到Bokeh团队的认可.您可以在其文档中看到一个区域图示例.基本上看起来像这样:

I would recommend looking at Holoviews which is a very high level API built on top of Bokeh, and is endorsed by the Bokeh team. You can see an Area chart example in their documentation. Basically it looks like:

# create holoviews objects
dims = dict(kdims='time', vdims='memory')
python = hv.Area(python_array, label='python', **dims)
pypy   = hv.Area(pypy_array,   label='pypy',   **dims)
jython = hv.Area(jython_array, label='jython', **dims)

# plot
overlay.relabel("Area Chart") + hv.Area.stack(overlay).relabel("Stacked Area Chart")

会导致

否则，从Bokeh 0.13开始，使用稳定的bokeh.plotting API创建堆积面积图，您将需要自己堆积数据，如此示例:

Otherwise, as of Bokeh 0.13 to create a stacked area chart with the stable bokeh.plotting API, you will need to stack the data yourself, as shown in this example:

import numpy as np
import pandas as pd

from bokeh.plotting import figure, show, output_file
from bokeh.palettes import brewer

N = 20
cats = 10
df = pd.DataFrame(np.random.randint(10, 100, size=(N, cats))).add_prefix('y')

def  stacked(df):
    df_top = df.cumsum(axis=1)
    df_bottom = df_top.shift(axis=1).fillna({'y0': 0})[::-1]
    df_stack = pd.concat([df_bottom, df_top], ignore_index=True)
    return df_stack

areas = stacked(df)
colors = brewer['Spectral'][areas.shape[1]]
x2 = np.hstack((df.index[::-1], df.index))

p = figure(x_range=(0, N-1), y_range=(0, 800))
p.grid.minor_grid_line_color = '#eeeeee'

p.patches([x2] * areas.shape[1], [areas[c].values for c in areas],
          color=colors, alpha=0.8, line_color=None)

show(p)

这将导致

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