How to set a different color to the largest bar in a seaborn barplot?

[Barplot case] If you get data from your dataframe you can do these:

labels = np.array(df.Name)
values = np.array(df.Score) 
clrs = ['grey' if (x < max(values)) else 'green' for x in values ]
#Configure the size
plt.figure(figsize=(10,5))
#barplot
sns.barplot(x=labels, y=values, palette=clrs) # color=clrs)
#Rotate x-labels 
plt.xticks(rotation=40)

The other answers defined the colors before plotting. You can as well do it afterwards by altering the bar itself, which is a patch of the axis you used to for the plot. To recreate iayork's example:

import seaborn
import numpy

values = numpy.array([2,5,3,6,4,7,1])   
idx = numpy.array(list('abcdefg')) 

ax = seaborn.barplot(x=idx, y=values) # or use ax=your_axis_object

for bar in ax.patches:
    if bar.get_height() > 6:
        bar.set_color('red')    
    else:
        bar.set_color('grey')

You can as well directly address a bar via e.g. ax.patches[7]. With dir(ax.patches[7]) you can display other attributes of the bar object you could exploit.

Just pass a list of colors. Something like

values = np.array([2,5,3,6,4,7,1])   
idx = np.array(list('abcdefg')) 
clrs = ['grey' if (x < max(values)) else 'red' for x in values ]
sb.barplot(x=idx, y=values, palette=clrs) # color=clrs)

(As pointed out in comments, later versions of Seaborn use "palette" rather than "color")