用散景和 pandas 绘制多条线 [英] Plotting multiple lines with Bokeh and pandas

问题描述

我想给Bokeh一个熊猫数据框，以绘制多条折线图.

I would like to give a pandas dataframe to Bokeh to plot a line chart with multiple lines.

x轴应为df.index，每个df.columns应为单独的行.

The x-axis should be the df.index and each df.columns should be a separate line.

这就是我想做的:

import pandas as pd
import numpy as np
from bokeh.plotting import figure, show

toy_df = pd.DataFrame(data=np.random.rand(5,3), columns = ('a', 'b' ,'c'), index = pd.DatetimeIndex(start='01-01-2015',periods=5, freq='d'))   

p = figure(width=1200, height=900, x_axis_type="datetime") 
p.multi_line(df)
show(p)

但是，我得到了错误:

RuntimeError: Missing required glyph parameters: ys

相反，我设法做到了:

import pandas as pd
import numpy as np
from bokeh.plotting import figure, show

toy_df = pd.DataFrame(data=np.random.rand(5,3), columns = ('a', 'b' ,'c'), index = pd.DatetimeIndex(start='01-01-2015',periods=5, freq='d'))   

ts_list_of_list = []
for i in range(0,len(toy_df.columns)):
    ts_list_of_list.append(toy_df.index)

vals_list_of_list = toy_df.values.T.tolist()

p = figure(width=1200, height=900, x_axis_type="datetime") 
p.multi_line(ts_list_of_list, vals_list_of_list)
show(p)

(勉强地)完成了工作，但是它对所有3行使用相同的颜色，请参见下文:

That (ineligantly) does the job but it uses the same color for all 3 lines, see below:

问题:

1)如何将熊猫数据框传递到bokeh的multi_line?

2)如果无法直接实现，该如何处理数据框数据，以便multi_line将创建具有不同颜色的每一行?

谢谢.

推荐答案

您需要为multi_line提供颜色列表.在您的示例中，您将执行以下操作:

You need to provide a list of colors to multi_line. In your example, you would do, something like this:

p.multi_line(ts_list_of_list, vals_list_of_list, line_color=['red', 'green', 'blue'])

这是第二个示例的更通用的修改，它或多或少地完成了您最终得到的结果，但更加简洁一些，也许更像Python了:

Here's a more general purpose modification of your second example that does more or less what you ended up with, but is a little more concise and perhaps more Pythonic:

import pandas as pd
import numpy as np
from bokeh.palettes import Spectral11
from bokeh.plotting import figure, show, output_file
output_file('temp.html')

toy_df = pd.DataFrame(data=np.random.rand(5,3), columns = ('a', 'b' ,'c'), index = pd.DatetimeIndex(start='01-01-2015',periods=5, freq='d'))   

numlines=len(toy_df.columns)
mypalette=Spectral11[0:numlines]

p = figure(width=500, height=300, x_axis_type="datetime") 
p.multi_line(xs=[toy_df.index.values]*numlines,
                ys=[toy_df[name].values for name in toy_df],
                line_color=mypalette,
                line_width=5)
show(p)

产生:

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