如何使用matplotlib自定义甘特图并在图表上显示指示当前时间的垂直线? [英] How to customize the Gantt chart using matplotlib and display the vertical line indicating current time on a graph?

问题描述

这是我的Python代码，基本上可以绘制甘特图:

Here is my Python code which basically plots a Gantt chart:

import pandas as pd
import random
from datetime import datetime
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
%matplotlib inline
import math
plt.style.use('ggplot')

df = pd.read_csv('zpp00141_new.csv')

def timestr_to_num(timestr):
    return mdates.date2num(datetime.strptime('0' + timestr if timestr[1] == ':' else timestr, '%I:%M:%S %p'))

df.rename(columns={"Earl. start / time": "start", "Latest finish / time": "finish"}, inplace = True)

df['Operation/Activity'] = df['Operation/Activity'].astype(str)

fig, ax = plt.subplots(figsize=(10, 5))
operations = pd.unique(df['Operation/Activity'])
#df.assign(start=df['Earl. start / time'])
colors = plt.cm.tab10.colors  # get a list of 10 colors
colors *= math.ceil(len(operations) / (len(colors)))  # repeat the list as many times as needed
for operation, color in zip(operations, colors):
    for row in df[df['Operation/Activity'] == operation].itertuples():
        left = timestr_to_num(row.start)
        right = timestr_to_num(row.finish)
        ax.barh(operation, left=left, width=right - left, height=3, color=color)
ax.set_xlim(timestr_to_num('07:00:00 AM'), timestr_to_num('4:30:00 PM'))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))  # display ticks as hours and minutes
ax.xaxis.set_major_locator(mdates.HourLocator(interval=1))  # set a tick every hour
ax.set_xlabel('Time')
ax.set_ylabel('Operation')
plt.tight_layout()
plt.show()

您可以在所附图片上看到输出:

You can see the output on the attached picture:

我想在x轴上绘制一条与当前时间相对应的垂直直线.我试图将其添加到我的代码中以进行绘制，但是我不知道如何使它工作.我认为我的时间格式可能有问题或类似的问题:

I would like to plot a vertical straight line that would correspond with a current time on the x-axis. I tried to add this to my code to plot it but I can't figure out how to make it work. I assume there might an issue with my time formatting or something like that:

plt.axvline(pd.Timestamp.now(),color='r')

在此问题上的任何帮助，我将非常感谢.这是所需输出的图片，我希望我的绘图也是如此:

I would really appreciate any assistance in this matter. Here is a picture of the desired output, I want my plot to be alike:

此外，我想在我的y轴操作简短文本"中添加/添加另一个类别.连同"Operation/Activity"(操作/活动)#，它不仅将显示操作号，而且还将在其旁边反映对该操作的描述.要了解我的数据的样子，请参见下文(第一行是标题):

Also, I would like to add/append another category to my y-axis "Operation short text" along with the "Operation/Activity"# so it would not only show the operation number, but would also reflect the description of the operation next to it. To have a grasp of what my data looks like,see below (first row is a header):

Operation short text,Operation/Activity,Earl. start / time,Latest finish / time
Mount right racks,0250,7:00:00 AM,9:22:00 AM
Mount right side motion unit carriage,0251,9:22:00 AM,10:30:00 AM
Mount left side motion unit carriage,0252,10:30:00 AM,11:17:00 AM
Install motion unit complete,0253,11:17:00 AM,1:01:00 PM
Move machine to next step + EPA,0254,1:01:00 PM,3:30:00 PM
Mount Left Racks,0200,7:00:00 AM,9:12:00 AM
Mount cable motor & Lubricate guide carr,0201,9:12:00 AM,9:44:00 AM
Mount suction components,0202,9:44:00 AM,11:04:00 AM
Mount extraction,0203,11:04:00 AM,12:34:00 PM
Mount temporary diamond plates,0204,12:34:00 PM,1:04:00 PM
Mount piping inside,0205,1:04:00 PM,1:44:00 PM
Move Machine to next step + EPA,0206,1:44:00 PM,3:30:00 PM

推荐答案

最简单的方法似乎是按操作对数据框进行排序，然后使用数据框的索引作为y坐标绘制水平条.然后，反转y轴的限制(将其从高设置为低)，将获得编号最低的操作在顶部.(代码现在假定每个小节将在新行上，而旧代码假定一次操作将有更多小节.)

The easiest seems to sort the dataframe by operation and then plot the horizontal bars using the index of the dataframe as the y-coordinate. Then, reversing the limits of the y-axis (setting it from high to low), gets the lowest numbered operation on top. (The code now assumes that each bar will be on a new line, while the old code assumed there would be more bars for one operation).

由于这些操作现在似乎属于在一起，因此选择了具有顺序颜色的色图，并且每次操作比上一个操作早开始时，这些颜色便会重新开始.随意使用任何适合您目标的方案.

As the operations now seem to belong together, a colormap with sequential colors is choosen, and the colors are started again each time an operation starts earlier than the previous. Feel free to use any scheme that suits your goals.

由于 datetime.strptime 仅查找时间，因此它将获得默认日期(1900年1月1日).因此，在现在"时间使用相同转换的方法非常明智.

As the datetime.strptime only looks to the time, it gets a default date (January 1st, 1900). So your approach to use the same conversion for the 'now' time is very adecuate.

请注意， pd.read_csv 的类型嗅探器为操作列提供了浮点格式.您可以防止向它提供明确的转换信息.例如. pd.read_csv(...，converters = {1:str})将第二列作为字符串.

Note that pd.read_csv's type sniffer gives a float format to the operations column. You could prevent this giving it explicit conversion information. E.g. pd.read_csv(..., converters={1: str}) to have the second column as string.

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime
import pandas as pd
import math
# % matplotlib inline

def timestr_to_num(timestr):
    return mdates.date2num(datetime.strptime('0' + timestr if timestr[1] == ':' else timestr, '%I:%M:%S %p'))

plt.style.use('ggplot')
# df = pd.read_csv('zpp00141_new.csv')
columns = ['Operation short text', 'Operation/Activity', 'Earl. start / time', 'Latest finish / time']
rows = [['Mount right racks', '0250', '7:00:00 AM', '9:22:00 AM'],
        ['Mount right side motion unit carriage', '0251', '9:22:00 AM', '10:30:00 AM'],
        ['Mount left side motion unit carriage', '0252', '10:30:00 AM', '11:17:00 AM'],
        ['Install motion unit complete', '0253', '11:17:00 AM', '1:01:00 PM'],
        ['Move machine to next step + EPA', '0254', '1:01:00 PM', '3:30:00 PM'],
        ['Mount Left Racks', '0200', '7:00:00 AM', '9:12:00 AM'],
        ['Mount cable motor & Lubricate guide carr', '0201', '9:12:00 AM', '9:44:00 AM'],
        ['Mount suction components', '0202', '9:44:00 AM', '11:04:00 AM'],
        ['Mount extraction', '0203', '11:04:00 AM', '12:34:00 PM'],
        ['Mount temporary diamond plates', '0204', '12:34:00 PM', '1:04:00 PM'],
        ['Mount piping inside', '0205', '1:04:00 PM', '1:44:00 PM'],
        ['Move Machine to next step + EPA', '0206', '1:44:00 PM', '3:30:00 PM']]
df = pd.DataFrame(data=rows, columns=columns)
df.rename(columns={"Earl. start / time": "start", "Latest finish / time": "finish"}, inplace=True)

df['Operation/Activity'] = df['Operation/Activity'].astype(int)
df.sort_values('Operation/Activity', ascending=True, inplace=True, ignore_index=True)

fig, ax = plt.subplots(figsize=(10, 5))

#colors = plt.cm.tab10.colors  # get a list of 10 colors
cmap = plt.cm.get_cmap('plasma_r')
colors = [cmap(i/9) for i in range(10)]   # get a list of 10 colors

previous_start = math.inf  # 'previous_start' helps to indicate we're starting again from the left
color_start = 0
for row in df.itertuples():
    left = timestr_to_num(row.start)
    right = timestr_to_num(row.finish)
    if left <= previous_start:
        color_start = row.Index
    ax.barh(row.Index, left=left, width=right - left, height=1, color=colors[(row.Index - color_start) % len(colors)])
    previous_start = left
ax.set_xlim(timestr_to_num('7:00:00 AM'), timestr_to_num('4:30:00 PM'))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))  # display ticks as hours and minutes
ax.xaxis.set_major_locator(mdates.HourLocator(interval=1))  # set a tick every hour
ax.set_xlabel('Time')
ax.set_ylabel('Operation')
ax.set_ylim(len(df), -1)  # set the limits and reverse the order
ax.set_yticks(range(len(df)))
# ax.set_yticklabels(list(df['Operation/Activity']))
ax.set_yticklabels(list(df['Operation short text']))

now = datetime.now().strftime('%I:%M:%S %p')
ax.axvline(x=timestr_to_num(now),color='r')

plt.tight_layout()
plt.show()

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