Question

这可能是显而易见的，所以请提前抱歉这个不引人注目的问题。我想用matplotlib.pyplot动态更新时间序列。更确切地说，我想在while循环中绘制新生成的数据。

这是我到目前为止的尝试：

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)

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

非常感谢。

Answer 1

正如Andras Deak指出的那样，你应该明确告诉大熊猫你的time列是日期时间。当您在代码末尾执行df.info()时，您将看到df['time']为float64。您可以使用df['time'] = pd.to_datetime(df['time'])实现此目的。

我能够让你的代码运行，但我不得不添加几行代码。我在iPython（Jupyter）控制台中运行它，没有两行autoscale_view和relim，它没有正确更新绘图。剩下要做的是对x轴标签进行很好的格式化。

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)

matplotlib在while循环中更新绘图，日期为x轴

1 个答案: