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我正在尝试使用示例中的方式制作plotly 甘特图plotly.express，但是plotly会根据给定的名称以某种方式改变条形厚度（参见图片，红色>绿色>蓝色）：

在此处输入图像描述

代码如下所示：

import pandas as pd
import plotly.express as px

df = pd.read_csv('stackoverflow.csv')
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
fig.update_yaxes(autorange="reversed")
fig.update_xaxes(
    dtick="1000",
    tickformat="%M:%S",
    ticklabelmode="instant")
fig.update_layout(xaxis_range=[df.Start.min(), df.Finish.max()])
fig.show()

存在stackoverflow.csv：

Task,Start,Finish,Workstation,Resource
1,1970-01-01 01:00:00.000,1970-01-01 01:00:05.400,1,ABL
2,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,2,ABS
3,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,3,ABU
4,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,4,ACC
5,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,4,ACC
6,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,4,ACC
7,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,5,ABS
8,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,6,ACT
9,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,7,ACC
10,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,7,ACC
11,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,7,ACC
12,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,8,ABS
13,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,9,ABU
14,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,10,ACC
15,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,11,ABS
16,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,12,ABU
17,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,13,ACC
18,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,13,ACC
19,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,14,ABS
20,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,15,ABP
21,1970-01-01 01:00:00.000,1970-01-01 01:00:01.500,16,ABZ
22,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,17,ACC
23,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,17,ACC
24,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,18,ABS
25,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,19,AAW
26,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,20,ACC
27,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,20,ACC
28,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,21,ABS
29,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,22,ABU
30,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,23,ACC

我希望所有的条都具有相同的厚度，令人惊讶的是，当我将 的名称更改Resource为某个随机的 3 字符值时，这会起作用： 在此处输入图像描述

AB*我认为这与以or开头的资源有关AC*。不幸的是，资源的名称取决于真实世界的名称，所以我不能随意更改它们。当资源的名称类似于FooBar-Axx-FOOwith时，也会发生不同的条形厚度xx = [CC, BS, CT...]。有谁知道为什么会发生这种情况或如何防止它？

PS：该

fig.update_xaxes(
    dtick="1000",
    tickformat="%M:%S")

有必要在甘特图中显示秒数而不是天数......有没有更好的方法来实现这一点？

更新： conda我用来创建问题的环境 yaml 文件：

name: stack
channels:
  - conda-forge
  - pytorch
  - plotly
dependencies:
    - python>=3.5,<3.8
    - pandas
    - pip
    - pip:
      - plotly

稍作修改的代码仍然产生与上图相同的问题：

import pandas as pd
import plotly.express as px
from io import StringIO


csv = """Task,Start,Finish,Workstation,Resource
1,1970-01-01 01:00:00.000,1970-01-01 01:00:05.400,1,ABL
2,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,2,ABS
3,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,3,ABU
4,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,4,ACC
5,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,4,ACC
6,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,4,ACC
7,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,5,ABS
8,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,6,ACT
9,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,7,ACC
10,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,7,ACC
11,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,7,ACC
12,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,8,ABS
13,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,9,ABU
14,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,10,ACC
15,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,11,ABS
16,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,12,ABU
17,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,13,ACC
18,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,13,ACC
19,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,14,ABS
20,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,15,ABP
21,1970-01-01 01:00:00.000,1970-01-01 01:00:01.500,16,ABZ
22,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,17,ACC
23,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,17,ACC
24,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,18,ABS
25,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,19,AAW
26,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,20,ACC
27,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,20,ACC
28,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,21,ABS
29,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,22,ABU
30,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,23,ACC"""

df = pd.read_csv(StringIO(csv))
# df = pd.read_csv("stackoverflow.csv")
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
fig.update_yaxes(autorange="reversed")
fig.update_xaxes(
    dtick="1000",
    tickformat="%M:%S",
    ticklabelmode="instant")
fig.update_layout(xaxis_range=[df.Start.min(), df.Finish.max()])
fig.show()

的输出conda list：

pip                       20.2.4                     py_0    conda-forge
plotly                    4.12.0                   pypi_0    pypi
python                    3.7.8           h6f2ec95_1_cpython    conda-forge
4

1 回答 1

1

（这是一个正在进行的答案，容易发生变化）

一个可能的解决方案：

但只有一个可能的解决方案，因为我仍然无法 100% 重现您的代码片段和相应的情节。但我们将在细节中仔细研究。你需要最新的 Plotly 版本和 Kaleido。但这些都是非常直接的安装，是 plotly 向前迈出的一大步。至少在我的拙见中......

代码 0：

df = pd.read_csv(StringIO(csv))
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
f2 = fig.full_figure_for_development(warn=False)
f2.layout.barmode = 'group'
f2.show()

情节 0：

在此处输入图像描述

细节：

我们将不得不一步一步地做到这一点。首先，当我运行您提供的代码时，我得到了这个：

情节1：

在此处输入图像描述

代码 1：

import pandas as pd
import plotly.express as px
from io import StringIO


csv = """Task,Start,Finish,Workstation,Resource
1,1970-01-01 01:00:00.000,1970-01-01 01:00:05.400,1,ABL
2,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,2,ABS
3,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,3,ABU
4,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,4,ACC
5,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,4,ACC
6,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,4,ACC
7,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,5,ABS
8,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,6,ACT
9,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,7,ACC
10,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,7,ACC
11,1970-01-01 01:00:03.300,1970-01-01 01:00:05.300,7,ACC
12,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,8,ABS
13,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,9,ABU
14,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,10,ACC
15,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,11,ABS
16,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,12,ABU
17,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,13,ACC
18,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,13,ACC
19,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,14,ABS
20,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,15,ABP
21,1970-01-01 01:00:00.000,1970-01-01 01:00:01.500,16,ABZ
22,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,17,ACC
23,1970-01-01 01:00:01.300,1970-01-01 01:00:03.300,17,ACC
24,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,18,ABS
25,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,19,AAW
26,1970-01-01 01:00:00.000,1970-01-01 01:00:02.000,20,ACC
27,1970-01-01 01:00:02.000,1970-01-01 01:00:03.300,20,ACC
28,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,21,ABS
29,1970-01-01 01:00:00.000,1970-01-01 01:00:01.000,22,ABU
30,1970-01-01 01:00:00.000,1970-01-01 01:00:01.300,23,ACC"""

df = pd.read_csv(StringIO(csv))
# df = pd.read_csv("stackoverflow.csv")
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
fig.update_yaxes(autorange="reversed")
fig.update_xaxes(
    dtick="1000",
    tickformat="%M:%S",
    ticklabelmode="instant")
fig.update_layout(xaxis_range=[df.Start.min(), df.Finish.max()])
fig.show()

为了接近您提供的屏幕截图，我必须注释掉几行，如下所示。但它仍然和你的数字不一样。

情节2：

在此处输入图像描述

代码 2（相同数据集）：

df = pd.read_csv(StringIO(csv))
# df = pd.read_csv("stackoverflow.csv")
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
# fig.update_yaxes(autorange="reversed")
# fig.update_xaxes(
#     dtick="1000",
#     tickformat="%M:%S",
#     ticklabelmode="instant")
# fig.update_layout(xaxis_range=[df.Start.min(), df.Finish.max()])
fig.show()

我觉得这有点奇怪。可能的解决方案更奇怪。如果您查看帖子Plotly：如何检查和更改情节图？您将看到如何使用f2 = fig.full_figure_for_development. 您对 的任何更改f2也应该可以对fig. 但在这种情况下不是。为了获得类似于您想要的输出的结果，我必须执行以下操作：

代码 3：

df = pd.read_csv(StringIO(csv))
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
f2 = fig.full_figure_for_development(warn=False)
f2.layout.barmode = 'group'
f2.show()

情节3：

在此处输入图像描述

也许我们正在这里的某个地方？但现在你可能会想“为什么不fig.layout.barmode = 'group'呢？”。好吧，结果如下：

情节4：

在此处输入图像描述

代码 4：

df = pd.read_csv(StringIO(csv))
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Resource", text="Task", width=1600, height=800)
f2 = fig.full_figure_for_development(warn=False)
# f2.layout.barmode = 'group'
# f2.show()
fig.layout.barmode = 'group'
fig.show()

我觉得这整件事有点奇怪。但是请尝试一下，让我知道这一切对你有用！

于 2020-11-10T20:06:44.730 回答