如何使用Python Pandas绘制堆叠事件持续时间（Gantt Charts）？

4 回答

• 11

  我想你正试图创造一个甘特图 . This建议使用 hlines ：

  from datetime import datetime
  import pandas as pd
  import matplotlib.pyplot as plt
  import matplotlib.dates as dt
  
  df = pd.read_csv('data.csv')
  df.amin = pd.to_datetime(df.amin).astype(datetime)
  df.amax = pd.to_datetime(df.amax).astype(datetime)
  
  fig = plt.figure()
  ax = fig.add_subplot(111)
  ax = ax.xaxis_date()
  ax = plt.hlines(df.index, dt.date2num(df.amin), dt.date2num(df.amax))
  

  

  回复于 2024-05-18T22:25:05+08:00
• 1

  您可以使用Bokeh（一个python库）制作甘特图，它非常漂亮 . 这是我从twiiter复制的代码 . http://nbviewer.jupyter.org/gist/quebbs/10416d9fb954020688f2

  from bokeh.plotting import figure, show, output_notebook, output_file
  from bokeh.models import ColumnDataSource, Range1d
  from bokeh.models.tools import HoverTool
  from datetime import datetime
  from bokeh.charts import Bar
  output_notebook()
  #output_file('GanntChart.html') #use this to create a standalone html file to send to others
  import pandas as ps
  
  DF=ps.DataFrame(columns=['Item','Start','End','Color'])
  Items=[
      ['Contract Review & Award','2015-7-22','2015-8-7','red'],
      ['Submit SOW','2015-8-10','2015-8-14','gray'],
      ['Initial Field Study','2015-8-17','2015-8-21','gray'],
      ['Topographic Procesing','2015-9-1','2016-6-1','gray'],
      ['Init. Hydrodynamic Modeling','2016-1-2','2016-3-15','gray'],
      ['Prepare Suitability Curves','2016-2-1','2016-3-1','gray'],
      ['Improvement Conceptual Designs','2016-5-1','2016-6-1','gray'],
      ['Retrieve Water Level Data','2016-8-15','2016-9-15','gray'],
      ['Finalize Hydrodynamic Models','2016-9-15','2016-10-15','gray'],
      ['Determine Passability','2016-9-15','2016-10-1','gray'],
      ['Finalize Improvement Concepts','2016-10-1','2016-10-31','gray'],
      ['Stakeholder Meeting','2016-10-20','2016-10-21','blue'],
      ['Completion of Project','2016-11-1','2016-11-30','red']
      ] #first items on bottom
  
  for i,Dat in enumerate(Items[::-1]):
      DF.loc[i]=Dat
  
  #convert strings to datetime fields:
  DF['Start_dt']=ps.to_datetime(DF.Start)
  DF['End_dt']=ps.to_datetime(DF.End)
  
  
  G=figure(title='Project Schedule',x_axis_type='datetime',width=800,height=400,y_range=DF.Item.tolist(),
          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)
  
  DF['ID']=DF.index+0.8
  DF['ID1']=DF.index+1.2
  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)
  

  回复于 2024-05-18T22:25:05+08:00
• 2

  使用水平条也可以这样做：broken_barh(xranges, yrange, **kwargs)

  回复于 2024-05-18T22:25:05+08:00
• 6

  虽然我不知道在MatplotLib中有什么方法可以做到这一点，但您可能希望通过使用D3以您想要的方式可视化数据来查看选项，例如，使用此库：

  https://github.com/jiahuang/d3-timeline

  如果你必须使用Matplotlib，这里有一种方法：

  Matplotlib timelines

  回复于 2024-05-18T22:25:05+08:00