December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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How to do it...
One of the most common data visualizations is of time-series data. Visualizing a time series in pandas is as simple as calling .plot() on a DataFrame or Series object that models a time series.
These are the parameters of the Series.plot function:
Series.plot(kind='line', ax=None, figsize=None, use_index=True, title=None, grid=None, legend=False, style=None, logx=False, logy=False, loglog=False, xticks=None, yticks=None, xlim=None, ylim=None, rot=None, fontsize=None, colormap=None, table=False, yerr=None, xerr=None, label=None, secondary_y=False, **kwds)
The following example demonstrates creating a time series that represents a random walk of values over time, akin to the movements in the price of a stock:
The .plot()
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