是否可以使用类似于这篇文章的方法在Python中创建时间轴仅使用1个vizualiation程序包,而没有其他设置?我尝试使用plotnine包在Python中使用ggplot2,但这要使其工作起来非常麻烦.此外,我尝试了 labella 软件包,但这需要安装Latex发行版.使用matplotlib,我找不到在事件栏旁边添加评论的方法.
Is there any way to create a timeline in Python similar to this post using only 1 vizualiation package and no other setup? I have tried to use the plotnine package to use ggplot2 within Python but this is quite cumbersome to get it to work. Furthermore, I have tried the labella package but this requires installation of a Latex distribution. With matplotlib I can't find a way to include the comments next to the event bars.
推荐答案我也遇到了这个问题……这是我的解决方案.请忽略丑陋的颜色生成" ...这更多的是正在进行的工作.
I also had this issue ... and this is my solution. Please ignore the Ugly Color Generation ... this is more of a work in progress.
这是经过Python 3.6测试的....
It is Python 3.6 tested ....
import numpy as np import matplotlib.pylab as plt import pandas as pd from cycler import cycler from datetime import datetime, timedelta idx = pd.date_range('2018-1-1', '2018-9-10', freq='1D') df = pd.DataFrame({'Offset': 20,'val': 2}, index=idx) df['Offset']=[n for n in range(0,len(df))] sched=[{'name':'tim', 'jobs':{ 1:(datetime(2018,1,1,),datetime(2018,2,1)), 2:(datetime(2018,4,1) ,datetime(2018,5,1)), 3:(datetime(2018,6,1) ,datetime(2018,7,1))} }, {'name':'BiMonthly', 'jobs':{ 1:(datetime(2018,2,1,),datetime(2018,3,1)), 2:(datetime(2018,5,1) ,datetime(2018,6,1)), 3:(datetime(2018,7,1) ,datetime(2018,8,1))} } , {'name':'Monthly', 'jobs':{ 1:(datetime(2018,2,1),datetime(2018,2,10)), 2:(datetime(2018,3,1),datetime(2018,3,10)), 3:(datetime(2018,4,1),datetime(2018,4,10)), 4:(datetime(2018,5,1),datetime(2018,5,10)), 5:(datetime(2018,6,1),datetime(2018,6,10)) }}, {'name':'LongTerm', 'jobs':{ 1:(datetime(2018,2,1),datetime(2018,5,1)) } }] color_cycle = cycler(c=['r', 'g', 'b']) ls_cycle = cycler('ls', ['-', '--']) sty_cycle = ls_cycle * ( color_cycle) def get_offset(when): global df if type(when)==str: when=pd.to_datetime(when) try: return df.loc[when]['Offset'] except KeyError: print("{} Not Found".format(when)) return -1 thickness=0.3 timelines=[] start_period = idx[0].to_period('D').ordinal for a_job_group in sched: timeline=[] print("-----") for keys in a_job_group['jobs']: #print("Dates {} {}".format(a_job_group['jobs'][keys][0], # a_job_group['jobs'][keys][1])) offset_start = get_offset(a_job_group['jobs'][keys][0]) offset_end = get_offset(a_job_group['jobs'][keys][1]) print("offset {} {} TimeSpan {}".format(offset_start, offset_end, offset_end - offset_start)) timeline_data=(start_period + offset_start,offset_end-offset_start) timeline.append(timeline_data) timelines.append(timeline) pos= 0 df.drop(['Offset'],axis=1,inplace=True,) ax = df.plot(color='w') col_schema=[s for s in sty_cycle] for t in timelines: ax.broken_barh(t, [pos, thickness], color=col_schema[pos]['c'], linestyle=col_schema[pos]['ls']) pos+= 1 plt.show()它输出什么?
我必须添加一个索引-并检查我是否可以更改TimeSteps(小时数等),但到目前为止,这是我能找到的最佳解决方案.
I have to add an Index - and to check that I can change the TimeSteps (hours weeks etc) but so far this it the best solution I can find.
我计划向其中添加 mpld3 -然后通过Flask运行它....因此,我还有一些路要走.
I plan to add mpld3 to it - and then to run it via Flask.... So I have a little ways to go.
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