随时间绘制总和

dav*_*one 2 python plot datetime graph matplotlib

“绘制 python 日期时间的累积图”提供了使用 matplotlib 绘制日期时间列表(见下文)作为随时间的累积计数的好方法:

[
    datetime.datetime(2015, 12, 22),
    datetime.datetime(2015, 12, 23),
    datetime.datetime(2015, 12, 23), # note duplicate entry (graph increases by 2)
    datetime.datetime(2015, 12, 24),
    datetime.datetime(2015, 12, 25),
    ...
]
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但是,我有一个新数据集,其中每个条目都有一个关联值(见下文)。我如何将其绘制为累积?或者我是否只需要遍历数据并将其累积到 x,y 绘图对中?

[
    (datetime.datetime(2015, 12, 22), 6), # graph increases by 6
    (datetime.datetime(2015, 12, 23), 5),
    (datetime.datetime(2015, 12, 23), 4), # graph increases by 9
    (datetime.datetime(2015, 12, 24), 12),
    (datetime.datetime(2015, 12, 25), 14),
]
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tom*_*m10 5

您需要做的就是拆分xy轴,然后使用np.cumsum或累积 y 值np.add.accumulate。下面是一个例子:

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime
import numpy as np

r = [(datetime.datetime(2015, 12, 22), 6), (datetime.datetime(2015, 12, 23), 5), (datetime.datetime(2015, 12, 23), 4), (datetime.datetime(2015, 12, 24), 12), (datetime.datetime(2015, 12, 25), 14)]

x, v = zip(*[(d[0], d[1]) for d in r])  # same as #x , v = [d[0] for d in r], [d[1] for d in r]
v = np.array(v).cumsum()  # cumulative sum of y values

# now plot the results
fig, ax = plt.subplots(1)
ax.plot(x, v, '-o')
fig.autofmt_xdate()
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %d'))
ax.xaxis.set_major_locator(mdates.DayLocator())
plt.show()
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结果由 matplotlib 绘制