"""

======================

Plotting with keywords

======================

Some data structures, like dict, `structured numpy array

<https://numpy.org/doc/stable/user/basics.rec.html#structured-arrays>`_

or `pandas.DataFrame` provide access to labelled data via string index access

``data[key]``.

For these data types, Matplotlib supports passing the whole datastructure via the

``data`` keyword argument, and using the string names as plot function parameters,

where you'd normally pass in your data.

"""

import matplotlib.pyplot as plt

import numpy as np

np.random.seed(19680801)

data = {'a': np.arange(50),

'c': np.random.randint(0, 50, 50),

'd': np.random.randn(50)}

data['b'] = data['a'] + 10 * np.random.randn(50)

data['d'] = np.abs(data['d']) * 100

fig, ax = plt.subplots()

ax.scatter('a', 'b', c='c', s='d', data=data)

ax.set(xlabel='entry a', ylabel='entry b')

plt.show()