pandas.DataFrame.boxplot
-
DataFrame.boxplot(column=None, by=None, ax=None, fontsize=None, rot=0, grid=True, figsize=None, layout=None, return_type=None, **kwds)
[source] -
Make a box plot from DataFrame columns.
Make a box-and-whisker plot from DataFrame columns, optionally grouped by some other columns. A box plot is a method for graphically depicting groups of numerical data through their quartiles. The box extends from the Q1 to Q3 quartile values of the data, with a line at the median (Q2). The whiskers extend from the edges of box to show the range of the data. The position of the whiskers is set by default to
1.5 * IQR (IQR = Q3 - Q1)
from the edges of the box. Outlier points are those past the end of the whiskers.For further details see Wikipedia’s entry for boxplot.
Parameters: column : str or list of str, optional
Column name or list of names, or vector. Can be any valid input to
pandas.DataFrame.groupby()
.by : str or array-like, optional
Column in the DataFrame to
pandas.DataFrame.groupby()
. One box-plot will be done per value of columns inby
.ax : object of class matplotlib.axes.Axes, optional
The matplotlib axes to be used by boxplot.
fontsize : float or str
Tick label font size in points or as a string (e.g.,
large
).rot : int or float, default 0
The rotation angle of labels (in degrees) with respect to the screen coordinate sytem.
grid : boolean, default True
Setting this to True will show the grid.
figsize : A tuple (width, height) in inches
The size of the figure to create in matplotlib.
layout : tuple (rows, columns), optional
For example, (3, 5) will display the subplots using 3 columns and 5 rows, starting from the top-left.
return_type : {‘axes’, ‘dict’, ‘both’} or None, default ‘axes’
The kind of object to return. The default is
axes
.- ‘axes’ returns the matplotlib axes the boxplot is drawn on.
- ‘dict’ returns a dictionary whose values are the matplotlib Lines of the boxplot.
- ‘both’ returns a namedtuple with the axes and dict.
-
when grouping with
by
, a Series mapping columns toreturn_type
is returned.If
return_type
isNone
, a NumPy array of axes with the same shape aslayout
is returned.
**kwds
All other plotting keyword arguments to be passed to
matplotlib.pyplot.boxplot()
.Returns: result :
The return type depends on the
return_type
parameter:- ‘axes’ : object of class matplotlib.axes.Axes
- ‘dict’ : dict of matplotlib.lines.Line2D objects
- ‘both’ : a nametuple with strucure (ax, lines)
For data grouped with
by
:Series
-
array
(forreturn_type = None
)
See also
-
Series.plot.hist
- Make a histogram.
-
matplotlib.pyplot.boxplot
- Matplotlib equivalent plot.
Notes
Use
return_type='dict'
when you want to tweak the appearance of the lines after plotting. In this case a dict containing the Lines making up the boxes, caps, fliers, medians, and whiskers is returned.Examples
Boxplots can be created for every column in the dataframe by
df.boxplot()
or indicating the columns to be used:>>> np.random.seed(1234) >>> df = pd.DataFrame(np.random.randn(10,4), ... columns=['Col1', 'Col2', 'Col3', 'Col4']) >>> boxplot = df.boxplot(column=['Col1', 'Col2', 'Col3'])
Boxplots of variables distributions grouped by the values of a third variable can be created using the option
by
. For instance:>>> df = pd.DataFrame(np.random.randn(10, 2), ... columns=['Col1', 'Col2']) >>> df['X'] = pd.Series(['A', 'A', 'A', 'A', 'A', ... 'B', 'B', 'B', 'B', 'B']) >>> boxplot = df.boxplot(by='X')
A list of strings (i.e.
['X', 'Y']
) can be passed to boxplot in order to group the data by combination of the variables in the x-axis:>>> df = pd.DataFrame(np.random.randn(10,3), ... columns=['Col1', 'Col2', 'Col3']) >>> df['X'] = pd.Series(['A', 'A', 'A', 'A', 'A', ... 'B', 'B', 'B', 'B', 'B']) >>> df['Y'] = pd.Series(['A', 'B', 'A', 'B', 'A', ... 'B', 'A', 'B', 'A', 'B']) >>> boxplot = df.boxplot(column=['Col1', 'Col2'], by=['X', 'Y'])
The layout of boxplot can be adjusted giving a tuple to
layout
:>>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X', ... layout=(2, 1))
Additional formatting can be done to the boxplot, like suppressing the grid (
grid=False
), rotating the labels in the x-axis (i.e.rot=45
) or changing the fontsize (i.e.fontsize=15
):>>> boxplot = df.boxplot(grid=False, rot=45, fontsize=15)
The parameter
return_type
can be used to select the type of element returned byboxplot
. Whenreturn_type='axes'
is selected, the matplotlib axes on which the boxplot is drawn are returned:>>> boxplot = df.boxplot(column=['Col1','Col2'], return_type='axes') >>> type(boxplot) <class 'matplotlib.axes._subplots.AxesSubplot'>
When grouping with
by
, a Series mapping columns toreturn_type
is returned:>>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X', ... return_type='axes') >>> type(boxplot) <class 'pandas.core.series.Series'>
If
return_type
isNone
, a NumPy array of axes with the same shape aslayout
is returned:>>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X', ... return_type=None) >>> type(boxplot) <class 'numpy.ndarray'>
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.DataFrame.boxplot.html