Annotate bars with values on Pandas (on Seaborn factorplot bar plot) - python-3.x

Question

I wrote some code to try and solve this question:
https://stackoverflow.com/questions/39477748/how-to-annotate-bars-with-values-on-pandas-on-seaborn-factorplot-bar-plot
I used part of the code that can be found here:
matplotlib advanced bar plot
Why is the graph so small? The code just tells to grab the accuracies from Pandas dataframe .
The code:
sns.set(style="white")
g = sns.factorplot(x="Stages", y="Accuracy", hue="Dataset", data=df, saturation = 5, size=4, aspect=2, kind="bar",
palette= myPalette, legend=False)
ax=g.ax
def annotateBars(row, ax=ax):
if row['Accuracy'] < 20:
color = 'white'
vertalign = 'bottom'
vertpad = 2
else:
color = 'black'
vertalign = 'top'
vertpad = -2
ax.text(row.name, row['Accuracy'] + vertpad, "{:.1f}%".format(row['Accuracy']),
zorder=10, rotation=90, color=color,
horizontalalignment='center',
verticalalignment=vertalign,
fontsize=12, weight='heavy')
junk = df.apply(annotateBars, ax=ax, axis=1)
This is code to annotate each bar, but ...with Pandas and Matplotlib. The only problem is that I do not know how to change colors and group the "x axis" :(
df = df.set_index('Stages')
ax = df.plot.bar(title="Accuracy")
ax.set_ylim(0, 120)
for p in ax.patches:
ax.annotate("%.2f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()),
ha='center', va='center', rotation=90, xytext=(0, 20), textcoords='offset points') #vertical bars

Answer 1

#Seaborn --factorplot
colors = ["windows blue", "orange red", "grey", "amber"]
myPalette = sns.xkcd_palette(colors) #envío "colors" a la función xkcd_palette
sns.set(style="white") #fondo blanco
g = sns.factorplot(x="Stages", y="Accuracy", hue="Dataset", data=df, saturation=5, size=4, aspect=3, kind="bar",
palette= myPalette, legend=False) #se suprime la leyenda
g.set(ylim=(0, 140))
g.despine(right=False)
g.set_xlabels("")
g.set_ylabels("")
g.set_yticklabels("")
#Matplotlib --legend creation
myLegend=plt.legend(bbox_to_anchor=(0., 1.2, 1., .102), prop ={'size':10}, loc=10, ncol=4, #left, bottom, width, height
title=r'TOTAL ACCURACY AND PER STAGE-RANDOM FOREST')
myLegend.get_title().set_fontsize('24')
#Matplotlib --anotación de barras
ax=g.ax #annotate axis = seaborn axis
def annotateBars(row, ax=ax):
for p in ax.patches:
ax.annotate("%.2f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()),
ha='center', va='center', fontsize=11, color='gray', rotation=90, xytext=(0, 20),
textcoords='offset points') verticales
plot = df.apply(annotateBars, ax=ax, axis=1)

Answer 2

This can now be plotted much more concisely
Axes.bar_label automatically labels bars [since matplotlib 3.4]
for container in ax.containers:
ax.bar_label(container)
Axes.legend includes fontsize and title_fontsize params [since matplotlib 3.0]
ax.legend(fontsize=10, title='ACCURACY', title_fontsize=24)
Also note that seaborn.factorplot has been renamed to seaborn.catplot [since seaborn 0.9]
Updated seaborn.catplot
colors = ['xkcd:windows blue', 'xkcd:orange red', 'xkcd:grey', 'xkcd:amber']
g = sns.catplot(x='Stages', y='Accuracy', hue='Dataset', data=df,
kind='bar', height=4, aspect=3, palette=colors, legend=False)
# auto-label bars
for container in g.ax.containers:
g.ax.bar_label(container, fmt='%.2f', padding=2, rotation=90)
# add legend with custom font sizes
ax.legend(bbox_to_anchor=(0, 1.2, 1, 0.102), loc=10, ncol=4, fontsize=10,
title='TOTAL ACCURACY AND PER STAGE-RANDOM FOREST', title_fontsize=24)
# redecorate
g.despine(right=False)
g.set_xlabels('')
g.set_ylabels('')
g.ax.set_yticklabels([])
Updated DataFrame.plot.bar
ax = df.pivot('Stages', 'Dataset', 'Accuracy').plot.bar(legend=False)
# auto-label bars
for container in ax.containers:
ax.bar_label(container, fmt='%.2f', padding=3, rotation=90, size='small')
# add legend with custom font sizes
ax.legend(bbox_to_anchor=(0, 1.1, 1, 0.102), loc=10, ncol=4, fontsize='small',
title='TOTAL ACCURACY AND PER STAGE-RANDOM FOREST', title_fontsize='xx-large')
# redecorate
sns.despine(right=False)
ax.set_yticklabels([])
plt.xticks(rotation=0)