pandas 如何使用月/年分辨率（用几行代码）绘制熊猫时间序列？
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How to plot a pandas timeseries using months/year resolution (with few lines of code)?
提问by Mannaggia
Assume we want to plot a time series, e.g.:
假设我们要绘制时间序列，例如：
import pandas as pd
import numpy as np
a=pd.DatetimeIndex(start='2010-01-01',end='2014-01-01' , freq='D')
b=pd.Series(np.randn(len(a)), index=a)
b.plot()
The result is a figure in which the x-axis has years as labels, I would like to get month-year labels. Is there a fast way to do this (possibly avoiding the use of tens of lines of complex code calling matplotlib)?
结果是一个数字，其中 x 轴有年份作为标签，我想获得月-年标签。有没有快速的方法来做到这一点（可能避免使用几十行复杂的代码调用 matplotlib）？
回答by Paul H
Pandas does some really weird stuff to the Axesobjects, making it hard to avoid matplotlib calls.
Pandas 对Axes对象做了一些非常奇怪的事情，使得很难避免 matplotlib 调用。
Here's how I would do it
这是我将如何做到的
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd
a = pd.DatetimeIndex(start='2010-01-01',end='2014-01-01' , freq='D')
b = pd.Series(np.random.randn(len(a)), index=a)
fig, ax = plt.subplots()
ax.plot(b.index, b)
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
which give me:
这给了我：
