pandas.Series.plot

Series.plot(self, 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 : bool, 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 : bool, 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 : bool or ‘sym’, default False

Use log scaling or symlog scaling on x axis .. versionchanged:: 0.25.0

logy : bool or ‘sym’ default False

Use log scaling or symlog scaling on y axis .. versionchanged:: 0.25.0

loglog : bool or ‘sym’, default False

Use log scaling or symlog scaling on both x and y axes .. versionchanged:: 0.25.0

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 : bool, 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 : bool, 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 : bool or sequence of ints, default False

If True then y-axis will be on the right

mark_right : bool, 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:
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)
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