英文:
factor_cmap in Bokeh is not being applied correctly for categorical chart
问题
我刚刚开始学习Bokeh，我试图创建一个带有抖动的条带图，以显示7个类别上的变化，其中x轴是错误，y轴是类别。我希望每个类别都有不同的颜色。
似乎在bokeh.transform下应该使用factor_cmap：
https://docs.bokeh.org/en/latest/docs/reference/transform.html
代码运行没有错误，但颜色从未应用（图表以默认颜色绘制，即蓝色）。
df = pd.read_csv(r'E:\Bokeh\Charting_vars.csv')
category = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
source = ColumnDataSource(df)
p = figure(width=800, height=800, y_range=category, title="Variation across 7 samples")
p.circle(
x='Error',
y=jitter('Category', width=0.6, range=p.y_range),
source=source,
fill_color=factor_cmap('Category', palette="Spectral7", factors=category)
)
p.ygrid.grid_line_color = None
show(p)
我漏掉了什么？
英文:
I just started learning Bokeh and I am trying to create a strip plot if you will with jitter to show variation over 7 categories where x axis is the error and y-axis is the category. I would like for each category to be a different color.
Seems like factor_cmap is what I should be using under bokeh.transform:
https://docs.bokeh.org/en/latest/docs/reference/transform.html
The code runs without errors but the colors are never applied (the graph draws with default colors which is blue).
df = pd.read_csv(r'E:\Bokeh\Charting_vars.csv')
category = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
source = ColumnDataSource(df)
p = figure(width=800, height=800, y_range=category, title="Variation across 7 samples")
p.circle(
x='Error',
y=jitter('Category', width=0.6, range=p.y_range),
source=source,
fill_color=factor_cmap('Category', palette="Spectral7", factors=category)
)
p.ygrid.grid_line_color = None
show(p)
What am I missing?
答案1
得分: 1
您的代码看起来很好，就我所看到的而言。也许有拼写错误。您能否请向我们展示您的数据框？希望我们可以重现您的问题。
为了帮助您，我从官方文档中修改了scatter_jitter示例。我只是添加了factor_cmap。
示例代码
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show, output_notebook
from bokeh.sampledata.commits import data
from bokeh.transform import jitter, factor_cmap
output_notebook()
DAYS = ['Sun', 'Sat', 'Fri', 'Thu', 'Wed', 'Tue', 'Mon']
source = ColumnDataSource(data)
p = figure(
width=800,
height=300,
y_range=DAYS,
x_axis_type='datetime',
title="Commits by Time of Day (US/Central) 2012-2016"
)
p.scatter(
x='time',
y=jitter('day', width=0.6, range=p.y_range),
source=source,
alpha=0.3,
fill_color=factor_cmap('day', palette='Spectral7', factors=DAYS)
)
p.xaxis.formatter.days = '%Hh'
p.x_range.range_padding = 0
p.ygrid.grid_line_color = None
show(p)
输出
这是使用 bokeh 2.4.3 创建的。
英文:
Your code looks fine as far as I can tell. Maybe there is a typo somewhere. Could you please show us your DataFrame? Hopefully we can reproduce your problem.
To help you I modified the scatter_jitter example from the official documentation. I just added factor_cmap.
Example Code
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show, output_notebook
from bokeh.sampledata.commits import data
from bokeh.transform import jitter, factor_cmap
output_notebook()
DAYS = ['Sun', 'Sat', 'Fri', 'Thu', 'Wed', 'Tue', 'Mon']
source = ColumnDataSource(data)
p = figure(
width=800,
height=300,
y_range=DAYS,
x_axis_type='datetime',
title="Commits by Time of Day (US/Central) 2012-2016"
)
p.scatter(
x='time',
y=jitter('day', width=0.6, range=p.y_range),
source=source,
alpha=0.3,
fill_color=factor_cmap('day', palette='Spectral7', factors=DAYS)
)
p.xaxis.formatter.days = '%Hh'
p.x_range.range_padding = 0
p.ygrid.grid_line_color = None
show(p)
Output
This was created with bokeh 2.4.3.
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