pandas.DataFrame.plot¶
- DataFrame.plot(frame=None, x=None, y=None, subplots=False, sharex=True, sharey=False, use_index=True, figsize=None, grid=None, legend=True, rot=None, ax=None, style=None, title=None, xlim=None, ylim=None, logx=False, logy=False, xticks=None, yticks=None, kind='line', sort_columns=False, fontsize=None, secondary_y=False, **kwds)¶
Make line, bar, or scatter plots of DataFrame series with the index on the x-axis using matplotlib / pylab.
Parameters : frame : DataFrame
x : label or position, default None
y : label or position, default None
Allows plotting of one column versus another
yerr : DataFrame (with matching labels), Series, list-type (tuple, list,
ndarray), or str of column name containing y error values
xerr : similar functionality as yerr, but for x error values
subplots : boolean, default False
Make separate subplots for each time series
sharex : boolean, default True
In case subplots=True, share x axis
sharey : boolean, default False
In case subplots=True, share y axis
use_index : boolean, default True
Use index as ticks for x axis
stacked : boolean, default False
If True, create stacked bar plot. Only valid for DataFrame input
sort_columns: boolean, default False
Sort column names to determine plot ordering
title : string
Title to use for the plot
grid : boolean, default None (matlab style default)
Axis grid lines
legend : False/True/’reverse’
Place legend on axis subplots
ax : matplotlib axis object, default None
style : list or dict
matplotlib line style per column
kind : {‘line’, ‘bar’, ‘barh’, ‘kde’, ‘density’, ‘area’, scatter’, ‘hexbin’}
line : line plot bar : vertical bar plot barh : horizontal bar plot kde/density : Kernel Density Estimation plot area : area plot scatter : scatter plot hexbin : hexbin plot
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
secondary_y : boolean or sequence, default False
Whether to plot on the secondary y-axis If a list/tuple, which columns to plot on secondary y-axis
mark_right: boolean, default True
When using a secondary_y axis, should the legend label the axis of the various columns automatically
colormap : str or matplotlib colormap object, default None
Colormap to select colors from. If string, load colormap with that name from matplotlib.
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.
kwds : keywords
Options to pass to matplotlib plotting method
Returns : ax_or_axes : matplotlib.AxesSubplot or list of them
Notes
If kind`=’hexbin’, you can control the size of the bins with the `gridsize argument. By default, a histogram of the counts around each (x, y) point is computed. You can specify alternative aggregations by passing values to the C and reduce_C_function arguments. C specifies the value at each (x, y) point and reduce_C_function is a function of one argument that reduces all the values in a bin to a single number (e.g. mean, max, sum, std).