Python bokeh.layouts() Examples
The following are 4
code examples of bokeh.layouts().
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and go to the original project or source file by following the links above each example.
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Example #1
| Source File: geoplot.py From Pandas-Bokeh with MIT License | 5 votes |
|
def _get_figure(col):
"""Gets the bokeh.plotting.figure from a bokeh.layouts.column."""
from bokeh.layouts import column
from bokeh.plotting import figure
for children in col.children:
if isinstance(children, type(figure())):
return children
elif isinstance(children, type(column())):
return _get_figure(children)
Example #2
| Source File: plot.py From Pandas-Bokeh with MIT License | 4 votes |
|
def line(self, x=None, y=None, **kwargs):
"""
Plot DataFrame columns as lines.
This function is useful to plot lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`pandas.DataFrame.plot_bokeh`.
Returns
-------
Bokeh.plotting.figure or Bokeh.layouts.row
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot_bokeh.line()
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> lines = df.plot_bokeh.line(x='pig', y='horse')
"""
return self(kind="line", x=x, y=y, **kwargs)
Example #3
| Source File: plot.py From Pandas-Bokeh with MIT License | 4 votes |
|
def step(self, x=None, y=None, **kwargs):
"""
Plot DataFrame columns as step lines.
This function is useful to plot step lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`pandas.DataFrame.plot_bokeh`.
Returns
-------
Bokeh.plotting.figure or Bokeh.layouts.row
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> steps = df.plot_bokeh.step()
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> steps = df.plot_bokeh.step(x='pig', y='horse')
"""
return self(kind="step", x=x, y=y, **kwargs)
Example #4
| Source File: plot.py From Pandas-Bokeh with MIT License | 4 votes |
|
def point(self, x=None, y=None, **kwargs):
"""
Plot DataFrame columns as points.
This function is useful to plot lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`pandas.DataFrame.plot_bokeh`.
Returns
-------
Bokeh.plotting.figure or Bokeh.layouts.row
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot_bokeh.point()
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> lines = df.plot_bokeh.point(x='pig', y='horse')
"""
return self(kind="point", x=x, y=y, **kwargs)
