Using matplotlib to plot DataFrame column with different line style depending on a variable in another column

Question

I am trying to plot lines from a GroupbyDataFrame with properties dependant on other column value. So far the task is being solved using conditions and loops on every pair of y-axis values.

Reproducible example:

import pandas as pd
from itertools import cycle
import seaborn as sns

# Setup DataFrame and Groupby object
df = pd.DataFrame({'week': range(1,11)*2,
                   'object':['a']*10 + ['b']*10,
                   'param': [100, 95, 90, 100, 110, 90, 90, 110, 110, 120,
                             110, 110, 110, 100, 100, 110, 110, 100, 100, 110],
                   'event': [0,    0,  1,   0,   0,   1,   1,   0,   0,   0,
                             0,    0,  0,   1,   1,   0,   0,   1,   1,   0]}, index=range(1,21))

print df.head()

groups = df.groupby('object')

# Setup Figure, ax and line properties
color = cycle(sns.color_palette('Set1'))
fig, ax = plt.subplots(figsize=(10,6))
base_line={'ls':'--', 'lw':3}
event_line={'ls':'-', 'lw':2}

# Process each group separately:
for name, g in groups:
    # Assign color for the object:
    label_set = False
    props = {'c':next(color)}
    # Set X axis values:
    x = g['week']

    # Process each pair of points to select desired properties:
    for i in range(g.shape[0]):
        # Make pair of Y values
        y = g.iloc[i:i+2].loc[:,'param'].reindex(g.index).values

        # Select properties of the pair of dots based on value of 'event' column:
        if g.iloc[i:i+2].loc[:,'event'].sum() >= 1:
            props.update(event_line)
            # Set properties for the legend if it has not been set before:
            if not label_set:
                props.update({'label':name})
                label_set = True
            else:
                # Remove label property if legend is already set:
                if props.has_key('label'):
                    props.pop('label')
        else:
            props.update(base_line)
        ax.plot(x, y, **props)

_ = ax.set_ylim(bottom=round(ax.get_yaxis().get_data_interval().min() * .9, -1), 
                top=round(ax.get_yaxis().get_data_interval().max() * 1.1, -1))

plt.legend(bbox_to_anchor=(1.15, 0.5), fontsize='x-large')
for l in ax.get_xticklabels() + ax.get_yticklabels():
    l.set_fontsize('x-large')

plt.show()

This produces desired output:

But I am hoping there is a matplotlib way to achieve the same result, which will also allow to easily manipulate legend for a line as whole (currently it is quite cumbersome).