Almost every element in a Seaborn figure can be further customized via seaborn.set. Here is the list of parameters that are supported:

• context: One of the preset contexts--{paper, notebook, talk, poster}.
• style: One of the axes' styles--{darkgrid, whitegrid, dark, white, ticks}.
• palette: One of the color palettes as defined in https://seaborn.pydata.org/generated/seaborn.color_palette.html#seaborn.color_palette.
• font: A supported font or font family name, such as serif, sans-serif, cursive, fantasy, or monospace. For more information, visit https://matplotlib.org/api/font_manager_api.html.
• font_scale: An independent scaling factor of font elements.
• rc: A dictionary of extra rc parameters mappings. To obtain the full list of all rc parameters, we can run seaborn.axes_style().

Let's try to increase the font scale, increase the line width of the KDE plot, and change the color of several plot elements:

# Get a dictionary of all parameters that can be changed
sns.axes_style()

"""
Returns
{'axes.axisbelow': True,
 'axes.edgecolor': '.8',
 'axes.facecolor': 'white',
 'axes.grid': True,
 'axes.labelcolor': '.15',
 'axes.linewidth': 1.0,
 'figure.facecolor': 'white',
 'font.family': [u'sans-serif'],
 'font.sans-serif': [u'Arial',
 u'DejaVu Sans',
 u'Liberation Sans',
 u'Bitstream Vera Sans',
 u'sans-serif'],
 'grid.color': '.8',
 'grid.linestyle': u'-',
 'image.cmap': u'rocket',
 'legend.frameon': False,
 'legend.numpoints': 1,
 'legend.scatterpoints': 1,
 'lines.solid_capstyle': u'round',
 'text.color': '.15',
 'xtick.color': '.15',
 'xtick.direction': u'out',
 'xtick.major.size': 0.0,
 'xtick.minor.size': 0.0,
 'ytick.color': '.15',
 'ytick.direction': u'out',
 'ytick.major.size': 0.0,
 'ytick.minor.size': 0.0}
 """

# Increase the font scale to 2, change the grid color to light grey, 
# and axes label color to dark blue
sns.set(context="notebook", 
 style="darkgrid",
 font_scale=2, 
 rc={'grid.color': '0.6', 
 'axes.labelcolor':'darkblue',
 "lines.linewidth": 2.5})

# Plot the histogram
ax = sns.distplot(current_bigmac.dollar_price)
plt.show()

The code generates the following histogram:

So far, only functions that control global aesthetics were introduced. What if we want to change the style of a specific plot only?

Luckily, most Seaborn plotting functions come with specific parameters for the customization of styles. This also means that there isn't a universal styling tutorial for all Seaborn plotting functions. However, we can take a closer look at this seaborn.distplot() code excerpt to get an idea:

# Note: Codes related to data preparation and imports are skipped for
# brevity
# Reset the style
sns.set(context="notebook", style="darkgrid")

# Plot the histogram with custom style
ax = sns.distplot(current_bigmac.dollar_price,
                 kde_kws={"color": "g", 
                          "linewidth": 3, 
                          "label": "KDE"},
                 hist_kws={"histtype": "step", 
                           "alpha": 1, 
                           "color": "k",
                           "label": "histogram"})

plt.show()

The expected result:

Some Seaborn functions support a more direct approach of customizing aesthetics. For example, seaborn.barplot can pass through keyword arguments such as facecolor, edgecolor, ecolor, and linewidth to the underlying matplotlib.pyplot.bar function:

# Note: Codes related to data preparation and imports are skipped
# for brevity
# Population Bar chart 
sns.barplot(x="AgeGrp",y="Value", hue="Sex",
            linewidth=2, edgecolor="w",
            data = current_population)

# Use Matplotlib functions to label axes rotate tick labels
ax = plt.gca()
ax.set(xlabel="Age Group", ylabel="Population (thousands)")
ax.set_xticklabels(ax.xaxis.get_majorticklabels(), rotation=45)
plt.title("Population Barchart (USA)")

# Show the figure
plt.show()