如何使用 Python Pandas 绘制堆积事件持续时间(甘特图) [英] How to plot stacked event duration (Gantt Charts) using Python Pandas
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问题描述
我有一个 Pandas DataFrame，其中包含一个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 DataFrame 示例:
将pandas导入为pd数据= { '指数':[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-59322230',UTAHDWQ-59322405-250HDW-HDW25040404', 'UTAHDWQ-5932750', 'UTAHDWQ-5983753', 'UTAHDWQ-5983754', 'UTAHDWQ-5983755', 'UTAHDWQ-5983756', 'UTAHDWQ595987W-59800000,'UTAHDWQ5987W-HD9''UTAHDWQ-5983775'、'UTAHDWQ-5989066'、'UTAHDWQ-5996780'、'UTAHDWQ-5996800']、'amin':['1994-07-19 13:15:2006':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(数据)df.set_index('index', inplace=True)# 显示(df.head())StationId amin amax指数40623 UTAHDWQ-5932100 1994-07-19 13:15:00 1998-06-30 14:51:0040637 UTAHDWQ-5932230 2006-03-16 13:55:00 2007-01-24 12:55:0040666 UTAHDWQ-5932240 1980-10-31 16:00:00 2007-07-31 11:35:0040697 UTAHDWQ-5932250 1981-06-11 17:45:00 1990-08-01 08:30:0040728 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):
该图不必沿每条线显示文本，只需显示带有站名的 y 轴.
虽然这看起来像是 Pandas 的一个小众应用，但我知道有几位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:
- 以下代码也有效
# 使用来自 OP 的 dfdf.amin = pd.to_datetime(df.amin)df.amax = pd.to_datetime(df.amax)图, ax = plt.subplots(figsize=(8, 5))ax = plt.hlines(df.index, df.amin, df.amax)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:
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 13:35:00I 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:
- How to plot stacked proportional graph?
- How to plot two columns of a pandas data frame using points?
- Matplotlib timelines
- Create Gantt Plot with python matplotlib
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.
解决方案- I think you are trying to create a gantt plot.
- This suggests using
hlines - Tested in
matplotlib 3.4.2
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))- The following code also works
# 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)这篇关于如何使用 Python Pandas 绘制堆积事件持续时间(甘特图)的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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