[雪峰磁针石博客]Bokeh数据可视化工具4层

2018-08-06 本文已影响94人 oychw

同一行创建多个图
同一列创建多个图
行和列中创建多个图
选项卡式布局创建多个绘图
创建强大的网格布局
将多个图表链接在一起

同一行创建多个图

bokeh自带了很多数据，可以用如下方式下载：

In [2]: import bokeh

In [3]: bokeh.sampledata.download()
Creating /home/andrew/.bokeh directory
Creating /home/andrew/.bokeh/data directory
Using data directory: /home/andrew/.bokeh/data
Downloading: CGM.csv (1589982 bytes)
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Unpacking: US_Counties.csv
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Downloading: unemployment09.csv (253301 bytes)
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Downloading: AAPL.csv (166698 bytes)
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Downloading: FB.csv (9706 bytes)
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Downloading: MSFT.csv (161614 bytes)
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Downloading: WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.zip (5148539 bytes)
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Unpacking: WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.csv
Downloading: gapminder_fertility.csv (64346 bytes)
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Downloading: gapminder_life_expectancy.csv (73243 bytes)
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Downloading: world_cities.zip (646858 bytes)
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Unpacking: world_cities.csv
Downloading: airports.json (6373 bytes)
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Downloading: airports.csv (203190 bytes)
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#Preparing all the plots needed for this chapter

import pandas as pd
from bokeh.sampledata.stocks import AAPL

df_apple = pd.DataFrame(AAPL)
df_apple['date'] = pd.to_datetime(df_apple['date'])


#Import the required packages

from bokeh.io import output_file, show
from bokeh.plotting import figure
from bokeh.plotting import ColumnDataSource


#Create the ColumnDataSource object

data = ColumnDataSource(data = {
    'x' : df_apple['high'],
    'y' : df_apple['low'],
    'x1': df_apple['open'],
    'y1': df_apple['close'],
    'x2': df_apple['date'],
    'y2': df_apple['volume'], 
})


#Create the first scatter plot
plot1 = figure()
plot1.cross(x = 'x', y = 'y', source = data, color = 'red', size = 10, alpha = 0.8)

#Create the second scatter plot
plot2 = figure()
plot2.circle(x = 'x1', y = 'y1', source = data, color = 'green', size = 10, alpha = 0.3)

#Create the third scatter plot
plot3 = figure(x_axis_type = 'datetime', x_axis_label = 'date', y_axis_label = 'Volume Traded')
plot3.line(x = 'x2', y = 'y2', source = data, color = 'red')
plot3.circle(x = 'x2', y = 'y2', source = data, fill_color = 'white', size = 3)


#Output the 3 plots
#Output the plot1
output_file('first_plot.html')
show(plot1)

#Output the plot2
output_file('second_plot.html')
show(plot2)


#Output the plot3
output_file('third_plot.html')
show(plot3)


#Creating multiple plots along the same row
#Import the required packages
from bokeh.layouts import row
from bokeh.io import output_file, show

#Group the 3 plots into a 'row' layout
row_layout = row(plot1,plot2,plot3)

#Output the plot
output_file('horizontal.html')
show(row_layout)


#Creating multiple plots along the same column

#Import the required packages

from bokeh.layouts import column
from bokeh.io import output_file, show

#Group the 2 plots into a 'column' layout
col_layout = column(plot1,plot2)

#Output the plot
output_file('vertical.html')
show(col_layout)

#Creating multiple plots along a row and column

#Import the required packages

from bokeh.layouts import column, row
from bokeh.io import output_file, show

#Construct the nested layout
nested_layout = column(row(plot1,plot2), plot3)

#Output the plot
output_file('nested.html')
show(nested_layout)



#Creating multiple plots on a tabbed layout

#Import the required packages
from bokeh.models.widgets import Tabs, Panel
from bokeh.io import output_file, show
from bokeh.layouts import column, row

#Create the two panels 

tab1 = Panel(child = plot1, title = 'Tab One')
tab2 = Panel(child = column(plot2,plot3), title = 'Tab Two')

#Feed the tabs into a Tabs object
tabs_object = Tabs(tabs = [tab1, tab2])

#Output the plot
output_file('tab_layout.html')
show(tabs_object)



#Creating a grid layout
#Import required packages

from bokeh.io import output_file, show
from bokeh.layouts import gridplot

#Create the grid layout
grid_layout = gridplot([plot1, plot2], [plot3, None])

#Output the plot
output_file('grid.html')
show(grid_layout)


#Linking multiple plots along the y axis
#Import the required packages

from bokeh.io import output_file, show
from bokeh.layouts import row

#Creating equal y axis ranges
plot3.y_range = plot1.y_range

#Create the row layout
row_layout = row(plot3, plot1)

#Output the plot
output_file('grid.html')
show(row_layout)



#Linking multiple plots along the x axis
#Import the required packages
from bokeh.io import output_file, show
from bokeh.layouts import row

#Creating equal x-axis ranges
plot2.x_range = plot1.x_range

#Create the row layout
row_layout = row(plot2, plot1)

#Output the plot
output_file('row.html')
show(row_layout)

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[雪峰磁针石博客]Bokeh数据可视化工具4层

同一行创建多个图

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