如何在 Matplotlib 图中单独标记条形？答案

【问题标题】：How to individually label bars in Matplotlib plot?如何在 Matplotlib 图中单独标记条形？
【发布时间】：2020-11-28 03:18:14
【问题描述】：

有没有办法使用 Matplotlib 标记单个条形？很好的例子of a collection of horizontal bars 是我最需要的，但是我需要为每个条添加标签。例如。将绿色条标记为绿色、橙色条为橙色等。我将如何修改下面的代码来完成此任务？

import datetime as dt
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.collections import PolyCollection

data = [    (dt.datetime(2018, 7, 17, 0, 15), dt.datetime(2018, 7, 17, 0, 30), 'sleep'),
            (dt.datetime(2018, 7, 17, 0, 30), dt.datetime(2018, 7, 17, 0, 45), 'eat'),
            (dt.datetime(2018, 7, 17, 0, 45), dt.datetime(2018, 7, 17, 1, 0), 'work'),
            (dt.datetime(2018, 7, 17, 1, 0), dt.datetime(2018, 7, 17, 1, 30), 'sleep'),
            (dt.datetime(2018, 7, 17, 1, 15), dt.datetime(2018, 7, 17, 1, 30), 'eat'), 
            (dt.datetime(2018, 7, 17, 1, 30), dt.datetime(2018, 7, 17, 1, 45), 'work')
        ]

cats = {"sleep" : 1, "eat" : 2, "work" : 3}
colormapping = {"sleep" : "C0", "eat" : "C1", "work" : "C2"}

verts = []
colors = []
for d in data:
    v =  [(mdates.date2num(d[0]), cats[d[2]]-.4),
          (mdates.date2num(d[0]), cats[d[2]]+.4),
          (mdates.date2num(d[1]), cats[d[2]]+.4),
          (mdates.date2num(d[1]), cats[d[2]]-.4),
          (mdates.date2num(d[0]), cats[d[2]]-.4)]
    verts.append(v)
    colors.append(colormapping[d[2]])

bars = PolyCollection(verts, facecolors=colors)

fig, ax = plt.subplots()
ax.add_collection(bars)
ax.autoscale()
loc = mdates.MinuteLocator(byminute=[0,15,30,45])
ax.xaxis.set_major_locator(loc)
ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(loc))

ax.set_yticks([1,2,3])
ax.set_yticklabels(["sleep", "eat", "work"])
plt.show()

【问题讨论】：

标签： python matplotlib

【解决方案1】：

您可以像创建矩形一样使用ax.text()：

import datetime as dt
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.collections import PolyCollection

data = [(dt.datetime(2018, 7, 17, 0, 15), dt.datetime(2018, 7, 17, 0, 30), 'sleep'),
        (dt.datetime(2018, 7, 17, 0, 30), dt.datetime(2018, 7, 17, 0, 45), 'eat'),
        (dt.datetime(2018, 7, 17, 0, 45), dt.datetime(2018, 7, 17, 1, 0), 'work'),
        (dt.datetime(2018, 7, 17, 1, 0), dt.datetime(2018, 7, 17, 1, 30), 'sleep'),
        (dt.datetime(2018, 7, 17, 1, 15), dt.datetime(2018, 7, 17, 1, 30), 'eat'),
        (dt.datetime(2018, 7, 17, 1, 30), dt.datetime(2018, 7, 17, 1, 45), 'work')]

cats = {"sleep": 1, "eat": 2, "work": 3}
colormapping = {"sleep": "C0", "eat": "C1", "work": "C2"}

verts = []
colors = []
for start, end, cat in data:
    v = [(mdates.date2num(start), cats[cat] - .4),
         (mdates.date2num(start), cats[cat] + .4),
         (mdates.date2num(end), cats[cat] + .4),
         (mdates.date2num(end), cats[cat] - .4),
         (mdates.date2num(start), cats[cat] - .4)]
    verts.append(v)
    colors.append(colormapping[cat])

bars = PolyCollection(verts, facecolors=colors)

fig, ax = plt.subplots()
ax.add_collection(bars)

for start, end, cat in data:
    ax.text((mdates.date2num(start) + mdates.date2num(end)) / 2, cats[cat], cat,
            color='lightgoldenrodyellow', fontsize=15, ha='center', va='center')

ax.autoscale()
loc = mdates.MinuteLocator(byminute=[0, 15, 30, 45])
ax.xaxis.set_major_locator(loc)
ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(loc))

ax.set_yticks([1, 2, 3])
ax.set_yticklabels(["sleep", "eat", "work"])
plt.show()

【讨论】：