pandas.Series.plot

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) [source]

Make plots of Series using matplotlib / pylab.

New in version 0.17.0: Each plot kind has a corresponding method on the Series.plot accessor: s.plot(kind='line') is equivalent to s.plot.line().

Parameters:

data : Series kind : str ‘line’ : line plot (default) ‘bar’ : vertical bar plot ‘barh’ : horizontal bar plot ‘hist’ : histogram ‘box’ : boxplot ‘kde’ : Kernel Density Estimation plot ‘density’ : same as ‘kde’ ‘area’ : area plot ‘pie’ : pie plot ax : matplotlib axes object If not passed, uses gca() figsize : a tuple (width, height) in inches use_index : boolean, default True Use index as ticks for x axis title : string or list Title to use for the plot. If a string is passed, print the string at the top of the figure. If a list is passed and subplots is True, print each item in the list above the corresponding subplot. grid : boolean, default None (matlab style default) Axis grid lines legend : False/True/’reverse’ Place legend on axis subplots style : list or dict matplotlib line style per column logx : boolean, default False Use log scaling on x axis logy : boolean, default False Use log scaling on y axis loglog : boolean, default False Use log scaling on both x and y axes xticks : sequence Values to use for the xticks yticks : sequence Values to use for the yticks xlim : 2-tuple/list ylim : 2-tuple/list rot : int, default None Rotation for ticks (xticks for vertical, yticks for horizontal plots) fontsize : int, default None Font size for xticks and yticks colormap : str or matplotlib colormap object, default None Colormap to select colors from. If string, load colormap with that name from matplotlib. colorbar : boolean, optional If True, plot colorbar (only relevant for ‘scatter’ and ‘hexbin’ plots) position : float Specify relative alignments for bar plot layout. From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center) table : boolean, Series or DataFrame, default False If True, draw a table using the data in the DataFrame and the data will be transposed to meet matplotlib’s default layout. If a Series or DataFrame is passed, use passed data to draw a table. yerr : DataFrame, Series, array-like, dict and str See Plotting with Error Bars for detail. xerr : same types as yerr. label : label argument to provide to plot secondary_y : boolean or sequence of ints, default False If True then y-axis will be on the right mark_right : boolean, default True When using a secondary_y axis, automatically mark the column labels with “(right)” in the legend `**kwds` : keywords Options to pass to matplotlib plotting method

Returns:

axes : matplotlib.axes.Axes or numpy.ndarray of them

Notes

• See matplotlib documentation online for more on this subject
• If kind = ‘bar’ or ‘barh’, you can specify relative alignments for bar plot layout by position keyword. From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)