如何使用 Pandas Series 绘制两个不同长度/起始日期的时间序列? [英] How to use Pandas Series to plot two Time Series of different lengths/starting dates?

问题描述

我正在绘制几个每周事件总数"的熊猫系列对象. events_per_week 系列中的数据如下:

I am plotting several pandas series objects of "total events per week". The data in the series events_per_week looks like this:

Datetime
 1995-10-09     45
 1995-10-16     63
 1995-10-23     83
 1995-10-30     91
 1995-11-06    101 
Freq: W-SUN, dtype: int64

我的问题如下.所有熊猫系列的长度均相同，即从1995年开始.但是，其中一个阵列于2003年开始. events_per_week2003 从2003年开始

My problem is as follows. All pandas series are the same length, i.e. beginning in same year 1995. One array begins in 2003 however. events_per_week2003 begins in 2003

 Datetime
     2003-09-08     25
     2003-09-15     36
     2003-09-22     74
     2003-09-29     25
     2003-09-05    193 
    Freq: W-SUN, dtype: int64

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(20,5))
ax = plt.subplot(111)
plt.plot(events_per_week)
plt.plot(events_per_week2003)

我得到以下值错误.

ValueError: setting an array element with a sequence.

我该怎么做?

推荐答案

我真的不了解您遇到的问题.我试图重新创建数据框的一部分，并且绘制它没有问题.

I really don't get where you're having problems. I tried to recreate a piece of the dataframe, and it plotted with no problems.

import numpy, matplotlib
data = numpy.array([45,63,83,91,101])
df1 = pd.DataFrame(data, index=pd.date_range('2005-10-09', periods=5, freq='W'), columns=['events'])
df2 = pd.DataFrame(numpy.arange(10,21,2), index=pd.date_range('2003-01-09', periods=6, freq='W'), columns=['events'])
matplotlib.pyplot.plot(df1.index, df1.events)
matplotlib.pyplot.plot(df2.index, df2.events)
matplotlib.pyplot.show()

使用系列而不是数据框:

Using Series instead of Dataframe:

ds1 = pd.Series(data, index=pd.date_range('2005-10-09', periods=5, freq='W'))
ds2 = pd.Series(numpy.arange(10,21,2), index=pd.date_range('2003-01-09', periods=6, freq='W'))
matplotlib.pyplot.plot(ds1)
matplotlib.pyplot.plot(ds2)
matplotlib.pyplot.show()

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