How to plot stacked event duration (Gantt Charts) using Python Pandas?

I have a Pandas DataFrame containing the date that a stream gage started measuring flow and the date that the station was decommissioned. I want to generate a plot showing these dates graphically. Here is a sample of my DataFrame:

index StationId amin amax 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 40735 UTAHDWQ-5932254 2006-06-28 13:55:00 2007-01-24 14:05:00 40742 UTAHDWQ-5932280 1981-06-11 15:30:00 2006-08-22 16:00:00 40773 UTAHDWQ-5932290 1992-06-10 15:45:00 1998-06-30 11:33:00 40796 UTAHDWQ-5932750 2005-10-03 16:30:00 2005-10-22 15:00:00 40819 UTAHDWQ-5983753 2006-04-25 09:56:00 2006-04-25 10:00:00 40823 UTAHDWQ-5983754 2006-04-25 11:05:00 2008-04-08 12:16:00 40845 UTAHDWQ-5983755 2006-04-25 13:50:00 2008-04-08 09:10:00 40867 UTAHDWQ-5983756 2006-04-25 14:20:00 2008-04-08 09:30:00 40887 UTAHDWQ-5983757 2006-04-25 12:45:00 2008-04-08 11:27:00 40945 UTAHDWQ-5983759 2008-04-08 13:03:00 2008-04-08 13:05:00 40964 UTAHDWQ-5983760 2008-04-08 13:15:00 2008-04-08 13:23:00 40990 UTAHDWQ-5983775 2008-04-15 12:47:00 2009-04-07 13:15:00 41040 UTAHDWQ-5989066 2005-10-04 10:15:00 2005-10-05 11:40:00 41091 UTAHDWQ-5996780 1995-03-09 13:59:00 1996-03-14 10:40:00 41100 UTAHDWQ-5996800 1995-03-09 15:13:00 1996-03-14 11:05:00

I want to create a plot similar to this (please note that I did not make this plot using the above data):

The plot does not have to have the text shown along each line, just the y-axis with station names.

While this may seem like a niche application of pandas, I know several scientists that would benefit from this plotting ability.

The closest answer I could find is here:

The last answer is closest to suiting my needs.

While I would prefer a way to do it through the Pandas wrapper, I would be open and grateful to a straight matplotlib solution.

DTing

I think you are trying to create a gantt plot. This suggests using 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))

You can use Bokeh (a python library) to make gantt chart and its really beautiful. Here is a code I copied from a twiiter. 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)

It's possible to do this with horizontal bars too: broken_barh(xranges, yrange, **kwargs)

MauricioRoman

While I do not know of any way to do this in MatplotLib, you may want to take a look at options with visualizing the data in the way you want by using D3, for example, with this library:

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

If you must do it with Matplotlib, here is one way in which it has been done:

Matplotlib timelines

来源：https://stackoverflow.com/questions/31820578/how-to-plot-stacked-event-duration-gantt-charts-using-python-pandas

标签

python