matplotlib在while循环中更新绘图，日期为x轴

Question

这可能很明显，所以提前对这个小问题表示抱歉。我想用 matplotlib.pyplot 动态更新时间序列。更准确地说，我想在 while 循环中绘制新生成的数据。

这是我目前的尝试：

import numpy as np
import matplotlib.pyplot as plt; plt.ion()
import pandas as pd
import time

n = 100
x = np.NaN
y = np.NaN
df = pd.DataFrame(dict(time=x, value=y), index=np.arange(n)) # not neccessarily needed to have a pandas df here, but I like working with it.

# initialise plot and line
line, = plt.plot(df['time'], df['value'])
i=0

# simulate line drawing
while i <= len(df):

    #generate random data point
    newData = np.random.rand()

    # extend the data frame by this data point and attach the current time as index
    df.loc[i, "value"] = newData
    df.loc[i, "time"] = pd.datetime.now()

    # plot values against indices
    line.set_data(df['time'][:i], df['value'][:i])
    plt.draw()

    plt.pause(0.001)

    # add to iteration counter
    i += 1

    print(i)

这将返回 TypeError: float() argument must be a string or a number, not 'datetime.datetime'。但据我所知，matplotlib 在 x 轴 (?) 上绘制日期没有任何问题。

非常感谢。

Answer 1

正如 Andras Deak 指出的那样，您应该明确告诉 pandas 您的 time 列是日期时间。当您在代码末尾执行df.info() 时，您会看到它采用df['time'] 作为float64。您可以通过df['time'] = pd.to_datetime(df['time']) 实现此目的。

我能够让您的代码运行，但我必须添加几行代码。我在 iPython (Jupyter) 控制台中运行它，并且没有 autoscale_view 和 relim 这两行，它没有正确更新绘图。剩下要做的是很好地格式化 x 轴标签。

import numpy as np
import matplotlib.pyplot as plt; plt.ion()
import pandas as pd
import time

n = 100
x = np.NaN
y = np.NaN
df = pd.DataFrame(dict(time=x, value=y), index=np.arange(n)) # not neccessarily needed to have a pandas df here, but I like working with it.
df['time'] = pd.to_datetime(df['time']) #format 'time' as datetime object

# initialise plot and line
fig = plt.figure()
axes = fig.add_subplot(111)
line, = plt.plot(df['time'], df['value'])

i=0

# simulate line drawing
while i <= len(df):    
    #generate random data point
    newData = np.random.rand()

    # extend the data frame by this data point and attach the current time as index
    df.loc[i, "value"] = newData
    df.loc[i, "time"] = pd.datetime.now()

    # plot values against indices, use autoscale_view and relim to readjust the axes
    line.set_data(df['time'][:i], df['value'][:i])
    axes.autoscale_view(True,True,True)
    axes.relim()
    plt.draw()

    plt.pause(0.01)

    # add to iteration counter
    i += 1

    print(i)