Specify relative alignments for bar plot layout.
From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
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.
stacked
: boolean, default False in line and
bar plots, and True in area plot. If True, create stacked plot.
sort_columns
: boolean, default False
Sort column names to determine plot ordering
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, 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
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)
If
kind
= ‘scatter’ and the argument
c
is the name of a dataframe
column, the values of that column are used to color each point.
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
).
