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# Matplotlib.axis.Tick.pickable() function in Python

• Last Updated : 10 Jun, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

## Matplotlib.axis.Tick.pickable() Function

The Tick.pickable() function in axis module of matplotlib library is used to return whether the artist is pickable or not.

Syntax: Tick.pickable(self)

Parameters: This method does not accept any parameters.

Return value: This method return whether the artist is pickable.

Below examples illustrate the matplotlib.axis.Tick.pickable() function in matplotlib.axis:
Example 1:

## Python3

 `# Implementation of matplotlib function``from` `matplotlib.axis ``import` `Tick``import` `numpy as np  ``np.random.seed(``19680801``)  ``import` `matplotlib.pyplot as plt  ``       ` `    ` `volume ``=` `np.random.rayleigh(``27``, size ``=` `100``)  ``amount ``=` `np.random.poisson(``10``, size ``=` `100``)  ``ranking ``=` `np.random.normal(size ``=` `100``)  ``price ``=` `np.random.uniform(``1``, ``10``, size ``=` `100``)  ``       ` `fig, ax ``=` `plt.subplots()  ``       ` `scatter ``=` `ax.scatter(volume ``*` `2``, amount ``*` `3``,  ``                     ``c ``=` `ranking ``*``*` `3``,   ``                     ``s ``=` `(price ``*` `5``)``*``*``2``,  ``                     ``vmin ``=` `-``4``, vmax ``=` `4``,   ``                     ``cmap ``=` `"Spectral"``)  ``   ` `      ` `ax.text(``60``, ``30``, ``"Value return : "``        ``+` `str``(Tick.pickable(ax)),   ``        ``fontweight ``=``"bold"``,   ``        ``fontsize ``=` `16``)`` ` `fig.suptitle('matplotlib.axis.Tick.pickable() \``function Example', fontweight ``=``"bold"``)  ``    ` `plt.show() `

Output:

Example 2:

## Python3

 `# Implementation of matplotlib function``from` `matplotlib.axis ``import` `Tick``import` `numpy as np  ``import` `matplotlib.pyplot as plt  ``import` `matplotlib.cbook as cbook  ``       ` `    ` `np.random.seed(``10``*``*``7``)  ``data ``=` `np.random.lognormal(size ``=``(``10``, ``4``),  ``                           ``mean ``=` `4.5``,  ``                           ``sigma ``=` `4.75``)  ``      ` `labels ``=` `[``'G1'``, ``'G2'``, ``'G3'``, ``'G4'``]  ``       ` `result ``=` `cbook.boxplot_stats(data,   ``                             ``labels ``=` `labels,   ``                             ``bootstrap ``=` `1000``)  `` ` `fig, axes1 ``=` `plt.subplots()  ``axes1.bxp(result)  ``      ` `axes1.text(``2``, ``30000``,  ``           ``"Value return : "``           ``+` `str``(Tick.pickable(axes1)),   ``           ``fontweight ``=``"bold"``)`` ` `fig.suptitle('matplotlib.axis.Tick.pickable() \``function Example', fontweight ``=``"bold"``)  ``    ` `plt.show() `

Output:

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