如何绘制堆积事件持续时间（甘特图）

问题描述 投票：0回答：5

我有一个 Pandas DataFrame，其中包含流量计开始测量流量的日期以及该站退役的日期。我想生成一个以图形方式显示这些日期的图。这是我的数据框的示例：

import pandas as pd

data = {'index': [40623, 40637, 40666, 40697, 40728, 40735, 40742, 40773, 40796, 40819, 40823, 40845, 40867, 40887, 40945, 40964, 40990, 41040, 41091, 41100],
        'StationId': ['UTAHDWQ-5932100', 'UTAHDWQ-5932230', 'UTAHDWQ-5932240', 'UTAHDWQ-5932250', 'UTAHDWQ-5932253', 'UTAHDWQ-5932254', 'UTAHDWQ-5932280', 'UTAHDWQ-5932290', 'UTAHDWQ-5932750', 'UTAHDWQ-5983753', 'UTAHDWQ-5983754', 'UTAHDWQ-5983755', 'UTAHDWQ-5983756', 'UTAHDWQ-5983757', 'UTAHDWQ-5983759', 'UTAHDWQ-5983760', 'UTAHDWQ-5983775', 'UTAHDWQ-5989066', 'UTAHDWQ-5996780', 'UTAHDWQ-5996800'],
        'amin': ['1994-07-19 13:15:00', '2006-03-16 13:55:00', '1980-10-31 16:00:00', '1981-06-11 17:45:00', '2006-06-28 13:15:00', '2006-06-28 13:55:00', '1981-06-11 15:30:00', '1992-06-10 15:45:00', '2005-10-03 16:30:00', '2006-04-25 09:56:00', '2006-04-25 11:05:00', '2006-04-25 13:50:00', '2006-04-25 14:20:00', '2006-04-25 12:45:00', '2008-04-08 13:03:00', '2008-04-08 13:15:00', '2008-04-15 12:47:00', '2005-10-04 10:15:00', '1995-03-09 13:59:00', '1995-03-09 15:13:00'],
        'amax': ['1998-06-30 14:51:00', '2007-01-24 12:55:00', '2007-07-31 11:35:00', '1990-08-01 08:30:00', '2007-01-24 13:35:00', '2007-01-24 14:05:00', '2006-08-22 16:00:00', '1998-06-30 11:33:00', '2005-10-22 15:00:00', '2006-04-25 10:00:00', '2008-04-08 12:16:00', '2008-04-08 09:10:00', '2008-04-08 09:30:00', '2008-04-08 11:27:00', '2008-04-08 13:05:00', '2008-04-08 13:23:00', '2009-04-07 13:15:00', '2005-10-05 11:40:00', '1996-03-14 10:40:00', '1996-03-14 11:05:00']}
df = pd.DataFrame(data)
df.set_index('index', inplace=True)

# display(df.head())

             StationId                 amin                 amax
index                                                           
40623  UTAHDWQ-5932100  1994-07-19 13:15:00  1998-06-30 14:51:00
40637  UTAHDWQ-5932230  2006-03-16 13:55:00  2007-01-24 12:55:00
40666  UTAHDWQ-5932240  1980-10-31 16:00:00  2007-07-31 11:35:00
40697  UTAHDWQ-5932250  1981-06-11 17:45:00  1990-08-01 08:30:00
40728  UTAHDWQ-5932253  2006-06-28 13:15:00  2007-01-24 13:35:00

我想创建一个与此类似的图（请注意，我没有使用上述数据制作此图）：

绘图不必沿每条线显示文本，只需在 y 轴上显示车站名称。

虽然这看起来像是熊猫的一个小众应用，但我知道一些科学家会从这种绘图能力中受益。

我能找到的最接近的答案在这里：

最后一个答案最接近我的需求。

虽然我更喜欢通过 Pandas 包装器来完成此操作，但我会开放并感激直接的 matplotlib 解决方案。

python pandas matplotlib time-series gantt-chart
5个回答
26
投票
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as dt

# using df from the OP

# convert columns to a datetime dtype
df.amin = pd.to_datetime(df.amin)
df.amax = pd.to_datetime(df.amax)

fig, ax = plt.subplots(figsize=(8, 5))
ax = ax.xaxis_date()
ax = plt.hlines(df.index, dt.date2num(df.amin), dt.date2num(df.amax))

  • 以下代码也有效
# using df from the OP

df.amin = pd.to_datetime(df.amin)
df.amax = pd.to_datetime(df.amax)

fig, ax = plt.subplots(figsize=(8, 5))
ax = plt.hlines(df.index, df.amin, df.amax)
12
投票

您可以使用Bokeh制作甘特图。

这是取自此笔记本的代码。它已更新以删除已弃用的方法并使用标准别名。

'Start'
和 
'End'
必须保留字符串才能获得正确的悬停注释，因此为 x 轴添加单独的列，如 
datetime64[ns] Dtype
。

导入和示例数据帧

import pandas as pd
from bokeh.plotting import figure, show, output_notebook, output_file
from bokeh.models import ColumnDataSource, Range1d
from bokeh.models.tools import HoverTool
output_notebook()
#output_file('GanntChart.html') #use this to create a standalone html file to send to others

# create sample dataframe
items =\
[['Completion of Project', '2016-11-1', '2016-11-30', 'red'],
 ['Stakeholder Meeting', '2016-10-20', '2016-10-21', 'blue'],
 ['Finalize Improvement Concepts', '2016-10-1', '2016-10-31', 'gray'],
 ['Determine Passability', '2016-9-15', '2016-10-1', 'gray'],
 ['Finalize Hydrodynamic Models', '2016-9-15', '2016-10-15', 'gray'],
 ['Retrieve Water Level Data', '2016-8-15', '2016-9-15', 'gray'],
 ['Improvement Conceptual Designs', '2016-5-1', '2016-6-1', 'gray'],
 ['Prepare Suitability Curves', '2016-2-1', '2016-3-1', 'gray'],
 ['Init. Hydrodynamic Modeling', '2016-1-2', '2016-3-15', 'gray'],
 ['Topographic Procesing', '2015-9-1', '2016-6-1', 'gray'],
 ['Initial Field Study', '2015-8-17', '2015-8-21', 'gray'],
 ['Submit SOW', '2015-8-10', '2015-8-14', 'gray'],
 ['Contract Review & Award', '2015-7-22', '2015-8-7', 'red']]

df = pd.DataFrame(data=items, columns=['Item', 'Start', 'End', 'Color'])

# add separate columns with the Start and End with a datetime dtype
df[['Start_dt', 'End_dt']] = df[['Start', 'End']].apply(pd.to_datetime)

# add id columns for plotting
df['ID'] = df.index + 0.8
df['ID1'] = df.index + 1.2


df

                              Item       Start         End Color   Start_dt     End_dt    ID   ID1
0            Completion of Project   2016-11-1  2016-11-30   red 2016-11-01 2016-11-30   0.8   1.2
1              Stakeholder Meeting  2016-10-20  2016-10-21  blue 2016-10-20 2016-10-21   1.8   2.2
2    Finalize Improvement Concepts   2016-10-1  2016-10-31  gray 2016-10-01 2016-10-31   2.8   3.2
3            Determine Passability   2016-9-15   2016-10-1  gray 2016-09-15 2016-10-01   3.8   4.2
4     Finalize Hydrodynamic Models   2016-9-15  2016-10-15  gray 2016-09-15 2016-10-15   4.8   5.2
5        Retrieve Water Level Data   2016-8-15   2016-9-15  gray 2016-08-15 2016-09-15   5.8   6.2
6   Improvement Conceptual Designs    2016-5-1    2016-6-1  gray 2016-05-01 2016-06-01   6.8   7.2
7       Prepare Suitability Curves    2016-2-1    2016-3-1  gray 2016-02-01 2016-03-01   7.8   8.2
8      Init. Hydrodynamic Modeling    2016-1-2   2016-3-15  gray 2016-01-02 2016-03-15   8.8   9.2
9            Topographic Procesing    2015-9-1    2016-6-1  gray 2015-09-01 2016-06-01   9.8  10.2
10             Initial Field Study   2015-8-17   2015-8-21  gray 2015-08-17 2015-08-21  10.8  11.2
11                      Submit SOW   2015-8-10   2015-8-14  gray 2015-08-10 2015-08-14  11.8  12.2
12         Contract Review & Award   2015-7-22    2015-8-7   red 2015-07-22 2015-08-07  12.8  13.2

绘图

G = figure(title='Project Schedule', x_axis_type='datetime', width=800, height=400, y_range=df.Item,
           x_range=Range1d(df.Start_dt.min(), df.End_dt.max()), tools='save')

hover = HoverTool(tooltips="Task: @Item<br>\
Start: @Start<br>\
End: @End")
G.add_tools(hover)

CDS = ColumnDataSource(df)
G.quad(left='Start_dt', right='End_dt', bottom='ID', top='ID1', source=CDS, color="Color")
#G.rect(,"Item",source=CDS)
show(G)

实时版本的情节具有交互式悬停注释。

3
投票

也可以使用水平条来做到这一点：

broken_barh(xranges, yrange, **kwargs)

1
投票

虽然我不知道在 MatplotLib 中有什么方法可以做到这一点，但您可能想看看使用 D3 以您想要的方式可视化数据的选项，例如，使用此库：

https://github.com/jia Huang/d3-timeline

如果您必须使用 Matplotlib 来完成此操作，这里是完成此操作的一种方法：

Matplotlib 时间线

0
投票

这已经有几年历史了，但是使用 seaborn 对象接口

有一个非常漂亮和简洁的解决方案 
# follows from original questions code

import seaborn.objects as so

# transform date values into datetimes
df = df.assign(
    amin=pd.to_datetime(df["amin"]),
    amax=pd.to_datetime(df["amax"]),
)

# encode min and max values to Range marker
p = (
    so.Plot(df, xmin="amin", xmax="amax", y="StationId", color="StationId")
    .add(so.Range(linewidth=3))
    .scale(x=so.Temporal().tick(upto=16), color="Set1")
)
# hack to remove color legend
p._layers[0]["legend"] = False
p.show()

Gantt chart of example data

但是，仅在很短的时间内收集的站点的数据不会显示，因此以稍微复杂一点为代价（并且由于某种原因无法再清除图例）我发现了一个让点出现在开始和结束处的方法：

import seaborn.objects as so

df = df.assign(
    amin=pd.to_datetime(df["amin"]),
    amax=pd.to_datetime(df["amax"]),
)

x1 = df["amin"].dt.year
x2 = df["amax"].dt.year
y = df["StationId"].str.removeprefix("UTAHDWQ-")
p = (
    so.Plot(xmin=x1, xmax=x2, y=y, color=y)
    .add(so.Range(linewidth=3))
    .add(so.Dot(), x=x1)
    .add(so.Dot(), x=x2)
    .scale(color="tab20")
    .layout(extent=(0,0,0.75,1))
    
)
p.show()

Dumbell Gantt chart using dots to show short intervals

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