Python: End-to-end Data Analysis

Time series plotting

Pandas comes with great support for plotting, and this holds true for time series data as well.

As a first example, let's take some monthly data and plot it:

>>> rng = pd.date_range(start='2000', periods=120, freq='MS')
>>> ts = pd.Series(np.random.randint(-10, 10, size=len(rng)), rng).cumsum()
>>> ts.head()
2000-01-01    -4
2000-02-01    -6
2000-03-01   -16
2000-04-01   -26
2000-05-01   -24
Freq: MS, dtype: int64

Since matplotlib is used under the hood, we can pass a familiar parameter to plot, such as c for color, or title for the chart title:

>>> ts.plot(c='k', title='Example time series')
>>> plt.show()

The following figure shows an example time series plot:

We can overlay an aggregate plot over 2 and 5 years:

>>> ts.resample('2A').plot(c='0.75', ...