散景图中的条柱未与 X-axis 刻度线和第一条柱线 cut-off 对齐
Bars not aligning with X-axis tick and first bar cut-off in Bokeh plot
我根据我的问题标题浏览了 auto-populated 的帖子，但找不到与我的古怪结果完全一致的内容。
我正在输入数据包捕获的 CSV 文件并收集协议，分别对每个协议的每个协议的长度求和，然后除以协议总数以获得每个协议的平均数据包大小。
使用我的显示命令，我能够确认列协议和字节具有相同的大小（有 18 个协议和 18 个平均字节大小）。除了可能被视为一个问题的两件事之外，我还能够确认图表绘制正确。
- “DNS”的第一个柱状图提前开始并且是一半 cut-off
- 条柱未在 x-axis 个刻度上对齐
我试图在他们的文档中使用简单的 Bokeh 水果示例来复制这个问题，但它绘制正常，但这只是用 x 和 y 创建一个虚拟数组。
Off-Center Plot
这是代码，但请记住，CSV 文件未附加并且由于 IP 地址，我不得不避免分享它，但如果有人看到它，我们将不胜感激。
此外，这是 temp.head() 的结果。
# Here is the myriad of declarations that helps this program work
import pandas as pd
import math as m
import ipympl
import ipywidgets
import numpy as np
# Bokeh libraries and modules (I am aware not all of these are required, just
# occasionally trying a few fun features, though let me know if this could be
# the problem)
from bokeh.io import show, reset_output, output_notebook, export_png
from bokeh.plotting import figure, output_file
from bokeh.models import Range1d, FactorRange, ColumnDataSource, LabelSet, HoverTool
from bokeh.models import ColorBar, LogColorMapper, LogTicker
from bokeh.layouts import gridplot, row, column
from bokeh.transform import factor_cmap, linear_cmap
from bokeh.models.annotations import Label
from bokeh.models.tools import HoverTool
from bokeh.palettes import Spectral6, Category20, viridis, turbo, linear_palette
# Set up plots to stay inside the notebook
# Remove this when you want to bring up a separate window display
output_notebook()
# Set up Bokeh visualtization toolset
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
data_r = pd.read_csv(r'C:\Users\xxx\Desktop\xxx.csv')
data_s = data_r.groupby('Protocol').Length.sum()
data_p = data_r.groupby('Protocol').Source.count()
data_a_p = data_s / data_p
data_a_p_df = data_a_p.to_frame()
temp = data_a_p_df.reset_index()
temp.columns = ['Protocol', 'bytes']
# Setting up the ColumnDataSource
cds = ColumnDataSource(temp)
p = figure(x_range=cds.data['Protocol'],
plot_height=300,
plot_width=800,
title="Average Packet Size by Protocol",
y_axis_label='Size in Bytes',
tools=TOOLS)
p.vbar(range(len(cds.data['Protocol'])),
width=.8,
top=cds.data['bytes'],
line_color='black',
fill_color=turbo(len(cds.data['Protocol'])),
fill_alpha=.5)
# To help the labels fit nicely, rotate the x-axis labels 45 degrees
p.xaxis.major_label_orientation = 45
# Display the graph
show(p)
display (len(cds.data['Protocol'])) # Results in 18
display (len(cds.data['bytes'])) # Results in 18
编辑： 为了制作一个显示错误的功能示例，这里是使用虚拟数据框的更新代码：
# Here is the myriad of declarations that helps this program work
# Note I added prettytable to make the dummy csv file
import pandas as pd
import math as m
import ipympl
import ipywidgets
import numpy as np
# Bokeh libraries and modules (I am aware not all of these are required, just
# occasionally trying a few fun features, though let me know if this could be
# the problem)
from bokeh.io import show, reset_output, output_notebook, export_png
from bokeh.plotting import figure, output_file
from bokeh.models import Range1d, FactorRange, ColumnDataSource, LabelSet, HoverTool
from bokeh.models import ColorBar, LogColorMapper, LogTicker
from bokeh.layouts import gridplot, row, column
from bokeh.transform import factor_cmap, linear_cmap
from bokeh.models.annotations import Label
from bokeh.models.tools import HoverTool
from bokeh.palettes import Spectral6, Category20, viridis, turbo, linear_palette
# Set up plots to stay inside the notebook
# Remove this when you want to bring up a separate window display
output_notebook()
# Set up Bokeh visualtization toolset
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
# For this example I created a dummy dataframe for the data
data_r = pd.DataFrame({
'Protocol': ['DNS','DNS', 'TCP', 'ICMPv6', 'TCP', 'TCP',
'HTTP', 'HTTP', 'TCP', 'TCP', 'TCP', 'TCP',
'TCP', 'ICMPv6', 'TCP', 'TCP', 'TCP',
'ICMPv6', 'ICMPv6', 'AJP13', 'AJP13'],
'Length': [96, 154, 66, 110, 171, 171, 208, 209, 56, 56,
56, 56, 66, 110, 54, 55, 56, 110, 110, 171, 171]
})
data_s = data_r.groupby('Protocol').Length.sum()
data_p = data_r.groupby('Protocol').Protocol.count()
data_a_p = data_s / data_p
data_a_p_df = data_a_p.to_frame()
temp = data_a_p_df.reset_index()
temp.columns = ['Protocol', 'bytes']
# Setting up the ColumnDataSource
cds = ColumnDataSource(temp)
p = figure(x_range=cds.data['Protocol'],
plot_height=300,
plot_width=800,
title="Average Packet Size by Protocol",
y_axis_label='Size in Bytes',
tools=TOOLS)
p.vbar(range(len(cds.data['Protocol'])),
width=.8,
top=cds.data['bytes'],
line_color='black',
fill_color=turbo(len(cds.data['Protocol'])),
fill_alpha=.5)
# To help the labels fit nicely, rotate the x-axis labels 45 degrees
p.xaxis.major_label_orientation = 45
# Display the graph
show(p)
首先，当您提供依赖于某些数据的代码时，请务必同时提供该数据。不是作为 temp.head() 的图片，而是作为可以复制的东西。理想情况下，只在代码本身中包含一些玩具数据。
关于您的问题 - 不要在 p.vbar 中使用 range(len(...))。只需提供 cds.data['Protocol'] 作为第一个参数。
我根据我的问题标题浏览了 auto-populated 的帖子，但找不到与我的古怪结果完全一致的内容。
我正在输入数据包捕获的 CSV 文件并收集协议，分别对每个协议的每个协议的长度求和，然后除以协议总数以获得每个协议的平均数据包大小。
使用我的显示命令，我能够确认列协议和字节具有相同的大小（有 18 个协议和 18 个平均字节大小）。除了可能被视为一个问题的两件事之外，我还能够确认图表绘制正确。
- “DNS”的第一个柱状图提前开始并且是一半 cut-off
- 条柱未在 x-axis 个刻度上对齐
我试图在他们的文档中使用简单的 Bokeh 水果示例来复制这个问题，但它绘制正常，但这只是用 x 和 y 创建一个虚拟数组。
Off-Center Plot
这是代码，但请记住，CSV 文件未附加并且由于 IP 地址，我不得不避免分享它，但如果有人看到它，我们将不胜感激。
此外，这是 temp.head() 的结果。
# Here is the myriad of declarations that helps this program work
import pandas as pd
import math as m
import ipympl
import ipywidgets
import numpy as np
# Bokeh libraries and modules (I am aware not all of these are required, just
# occasionally trying a few fun features, though let me know if this could be
# the problem)
from bokeh.io import show, reset_output, output_notebook, export_png
from bokeh.plotting import figure, output_file
from bokeh.models import Range1d, FactorRange, ColumnDataSource, LabelSet, HoverTool
from bokeh.models import ColorBar, LogColorMapper, LogTicker
from bokeh.layouts import gridplot, row, column
from bokeh.transform import factor_cmap, linear_cmap
from bokeh.models.annotations import Label
from bokeh.models.tools import HoverTool
from bokeh.palettes import Spectral6, Category20, viridis, turbo, linear_palette
# Set up plots to stay inside the notebook
# Remove this when you want to bring up a separate window display
output_notebook()
# Set up Bokeh visualtization toolset
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
data_r = pd.read_csv(r'C:\Users\xxx\Desktop\xxx.csv')
data_s = data_r.groupby('Protocol').Length.sum()
data_p = data_r.groupby('Protocol').Source.count()
data_a_p = data_s / data_p
data_a_p_df = data_a_p.to_frame()
temp = data_a_p_df.reset_index()
temp.columns = ['Protocol', 'bytes']
# Setting up the ColumnDataSource
cds = ColumnDataSource(temp)
p = figure(x_range=cds.data['Protocol'],
plot_height=300,
plot_width=800,
title="Average Packet Size by Protocol",
y_axis_label='Size in Bytes',
tools=TOOLS)
p.vbar(range(len(cds.data['Protocol'])),
width=.8,
top=cds.data['bytes'],
line_color='black',
fill_color=turbo(len(cds.data['Protocol'])),
fill_alpha=.5)
# To help the labels fit nicely, rotate the x-axis labels 45 degrees
p.xaxis.major_label_orientation = 45
# Display the graph
show(p)
display (len(cds.data['Protocol'])) # Results in 18
display (len(cds.data['bytes'])) # Results in 18
编辑： 为了制作一个显示错误的功能示例，这里是使用虚拟数据框的更新代码：
# Here is the myriad of declarations that helps this program work
# Note I added prettytable to make the dummy csv file
import pandas as pd
import math as m
import ipympl
import ipywidgets
import numpy as np
# Bokeh libraries and modules (I am aware not all of these are required, just
# occasionally trying a few fun features, though let me know if this could be
# the problem)
from bokeh.io import show, reset_output, output_notebook, export_png
from bokeh.plotting import figure, output_file
from bokeh.models import Range1d, FactorRange, ColumnDataSource, LabelSet, HoverTool
from bokeh.models import ColorBar, LogColorMapper, LogTicker
from bokeh.layouts import gridplot, row, column
from bokeh.transform import factor_cmap, linear_cmap
from bokeh.models.annotations import Label
from bokeh.models.tools import HoverTool
from bokeh.palettes import Spectral6, Category20, viridis, turbo, linear_palette
# Set up plots to stay inside the notebook
# Remove this when you want to bring up a separate window display
output_notebook()
# Set up Bokeh visualtization toolset
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
# For this example I created a dummy dataframe for the data
data_r = pd.DataFrame({
'Protocol': ['DNS','DNS', 'TCP', 'ICMPv6', 'TCP', 'TCP',
'HTTP', 'HTTP', 'TCP', 'TCP', 'TCP', 'TCP',
'TCP', 'ICMPv6', 'TCP', 'TCP', 'TCP',
'ICMPv6', 'ICMPv6', 'AJP13', 'AJP13'],
'Length': [96, 154, 66, 110, 171, 171, 208, 209, 56, 56,
56, 56, 66, 110, 54, 55, 56, 110, 110, 171, 171]
})
data_s = data_r.groupby('Protocol').Length.sum()
data_p = data_r.groupby('Protocol').Protocol.count()
data_a_p = data_s / data_p
data_a_p_df = data_a_p.to_frame()
temp = data_a_p_df.reset_index()
temp.columns = ['Protocol', 'bytes']
# Setting up the ColumnDataSource
cds = ColumnDataSource(temp)
p = figure(x_range=cds.data['Protocol'],
plot_height=300,
plot_width=800,
title="Average Packet Size by Protocol",
y_axis_label='Size in Bytes',
tools=TOOLS)
p.vbar(range(len(cds.data['Protocol'])),
width=.8,
top=cds.data['bytes'],
line_color='black',
fill_color=turbo(len(cds.data['Protocol'])),
fill_alpha=.5)
# To help the labels fit nicely, rotate the x-axis labels 45 degrees
p.xaxis.major_label_orientation = 45
# Display the graph
show(p)
首先，当您提供依赖于某些数据的代码时，请务必同时提供该数据。不是作为 temp.head() 的图片，而是作为可以复制的东西。理想情况下，只在代码本身中包含一些玩具数据。
关于您的问题 - 不要在 p.vbar 中使用 range(len(...))。只需提供 cds.data['Protocol'] 作为第一个参数。