Matplotlib和datetime的OverflowError [英] OverflowError with Matplotlib and datetime

问题描述

当我尝试使用日期时间制作散点图时出现溢出错误:

将 numpy 导入为 np将熊猫作为pd导入导入matplotlib.pyplot作为pltlist_data = ['2016-10-06'，'2016-09-24'，55，'虚拟'，0.510823，0.29431]列= ['master'，'slave'，'baseline'，'coh'，'coh_mean'，'coh_std']dict_data = dict(zip(列(list_data)))数据= pd.DataFrame.from_dict(dict_data，orient ='index').Tdata.slave = pd.to_datetime(data.slave)图，轴= plt.subplots()axes.scatter(data.slave，data.baseline)plt.show()

我已经尝试了多种方法，例如使用 datetime.strptime()，更改matplotlib后端，但仅将问题隔离为datetime格式(如果是字符串，则可以很好地工作)

不使用分散绘图 (axes.plot(), axes.plot_date()) 工作正常，但我最终需要为散点着色，散点方法似乎最适合.>

绘制熊猫系列的值 axes.scatter(data.slave.values，data.baseline.values)结果是一个空的图形对象.

谢谢.

解决方案

您不能使用 scatter 绘制 Pandas 系列.您想要的只是绘制其值.

axes.scatter(data.slave.values, data.baseline.values)

完整示例:

将 numpy 导入为 np将熊猫作为pd导入导入matplotlib.pyplot作为pltlist_data = ['2016-10-06', '2016-09-24', 55, 'dummy', 0.510823, 0.29431]列 = ['master', 'slave', 'baseline', 'coh', 'coh_mean', 'coh_std']dict_data = dict(zip(列(list_data)))数据= pd.DataFrame.from_dict(dict_data，orient ='index').Tdata.slave = pd.to_datetime(data.slave)图，轴 = plt.subplots()轴散点(data.slave.values，data.baseline.values)plt.show()

结果

I am getting an overflow error when I try and make a scatter plot with a datetime:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

list_data  = ['2016-10-06', '2016-09-24', 55, 'dummy', 0.510823, 0.29431]
columns    = ['master', 'slave', 'baseline', 'coh', 'coh_mean', 'coh_std']
dict_data  = dict(zip(columns, list_data))
data       = pd.DataFrame.from_dict(dict_data, orient='index').T
data.slave = pd.to_datetime(data.slave)
fig, axes  = plt.subplots()
axes.scatter(data.slave, data.baseline)
plt.show()

I've tried a variety of things, such as using datetime.strptime(), changing matplotlib backends but only have been isolate the problem to the datetime format (works fine if it's a string).

Plotting without scatter (axes.plot(), axes.plot_date()) works fine, but I eventually need to color the scatter points, which the scatter method seems best suited for.

EDIT: Plotting the values of the panda series axes.scatter(data.slave.values, data.baseline.values) Results in an empty figure object.

Thanks.

解决方案

You cannot plot a pandas series with scatter. What you want is to plot its values only.

axes.scatter(data.slave.values, data.baseline.values)

Complete example:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

list_data  = ['2016-10-06', '2016-09-24', 55, 'dummy', 0.510823, 0.29431]
columns    = ['master', 'slave', 'baseline', 'coh', 'coh_mean', 'coh_std']
dict_data  = dict(zip(columns, list_data))
data       = pd.DataFrame.from_dict(dict_data, orient='index').T
data.slave = pd.to_datetime(data.slave)
fig, axes  = plt.subplots()
axes.scatter(data.slave.values, data.baseline.values)
plt.show()

results in

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