"Plotting a cumulative graph of python datetimes"提供了使用 matplotlib 绘制日期时间列表(见下文)作为随时间累积计数的好方法:
[
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),
...
]
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)。我怎样才能将其绘制为累积?或者我只需要迭代数据并将其累积成 x,y 绘图对?
[
(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),
]
最佳答案
您需要做的就是拆分 x
和 y
轴,然后使用 np.cumsum
累积 y 值。或np.add.accumulate
。这是一个例子:
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()
关于python - 随时间绘制总和,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/37529263/