带有颜色条的 plotly 甘特图

Question

我正在制作像这里一样的甘特图 https://plot.ly/python/gantt/#index-by-numeric-variable 但是，我想用作索引的数字变量是一个远大于 100 的正数。当我使用示例代码时，颜色条限制为 [0,100]，导致条形全部为 100 的颜色。有没有办法提升使用示例中的代码创建的绘图甘特图中的最大值？

我希望颜色 "proportional" 到索引的值。

这是示例代码：

import plotly.figure_factory as ff

df = [dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Complete=10),
      dict(Task="Job B", Start='2008-12-05', Finish='2009-04-15', Complete=60),
      dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30', Complete=95)]

fig = ff.create_gantt(df, colors='Viridis', index_col='Complete', show_colorbar=True)
fig.show()

明确一点：在我的例子中，变量 Complete 的值可以高达 700000

Answer 1

根据文档，它应该在给定数字索引时缩放。但是，查看代码，似乎 min/max 值已被硬编码为 0 和 100。请参阅 code 第 285 和 286 行。

一种解决方法是在 0-100 之间缩放索引并手动将颜色条的标签设置为原始 min/max:

import warnings
warnings.filterwarnings('ignore', category=FutureWarning)  # plotly returns a FutureWarning due to using .ix

from sklearn import preprocessing
import plotly.figure_factory as ff

# create a dataframe for easier processing wrt the scaled index
df = pd.DataFrame([dict(Task="Job A", Start='2009-01-01', Finish='2009-02-28', Complete=10),
      dict(Task="Job B", Start='2008-12-05', Finish='2009-04-15', Complete=60),
      dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30', Complete=995)])

# scale index (0-100) and add as new column
min_max_scaler = preprocessing.MinMaxScaler()
index_scaled = min_max_scaler.fit_transform(df.Complete.values.reshape(-1,1))
df['index_scaled'] = index_scaled * 100

# create figure based on scaled index
fig = ff.create_gantt(df, index_col='index_scaled', colors='Viridis', show_colorbar=True)

# set scale of color bar
fig.data[-1]['marker']['cmin'] = df.Complete.min()
fig.data[-1]['marker']['cmax'] = df.Complete.max()
fig.data[-2]['marker']['cmin'] = df.Complete.min()
fig.data[-2]['marker']['cmax'] = df.Complete.max()

# Due to indexing on the scaled value, the tooltip of the bars shows this values instead of its original.
# You could iterate over them and adjust, but you'll need to match the sorting of fig.data to the sorting of the dataframe.
# fig.data[0].name = original_value

fig.show()

请注意，如上面的评论所述，您可能需要注意条形图的工具提示（显示索引值）。这些也可以手动设置，但您需要将 fig.data 的顺序与原始数据帧的顺序相匹配。

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