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pythonmatplotlibplottimeline

Plot a binary timeline in matplotlib

I'm trying to plot a binary timeline using matplotlib (I might be able to consider alternative libraries, though).

Now, by "binary timeline" I mean the "display of chronological events, where the event space is made of two opposite events". An example of such an event space could be {no_one_in_the_team_is_sick, at_least_one_person_in_the_team_is_sick}.

The representation I'd like to replicate is this (I did it using d3): enter image description here

I've tried exploring the use of stacked horizontal bars, but it's clearly not the right tool for the job.

Is there an easier and/or more correct way of achieving that result?

Solution

  • You may use broken_barhto plot a binary timeline.

    enter image description here

    import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates

#create a time series s with dates as index and 0 and 1 for events
dates = pd.date_range("2017-04-01","2017-06-15", freq="D")
events = np.random.random_integers(0,1,size=len(dates))
s = pd.Series(events, index=dates)

fig, ax= plt.subplots(figsize=(6,2))

# plot green for event==1
s1 = s[s == 1]
inxval = matplotlib.dates.date2num(s1.index.to_pydatetime())
times= zip(inxval, np.ones(len(s1)))
plt.broken_barh(times, (-1,1), color="green")
# plot red for event==0
s2 = s[s == 0]
inxval = matplotlib.dates.date2num(s2.index.to_pydatetime())
times= zip(inxval, np.ones(len(s2)))
plt.broken_barh(times, (-1,1), color="red")

#format axes
ax.margins(0)
ax.set_yticks([])
ax.xaxis.set_major_locator(matplotlib.dates.MonthLocator())
ax.xaxis.set_minor_locator(matplotlib.dates.DayLocator())
monthFmt = matplotlib.dates.DateFormatter("%b")
ax.xaxis.set_major_formatter(monthFmt)
plt.tight_layout()
plt.show()