How can I add the number of observations to a Seaborn barplot?

Question

I want to add the number of observations to Seaborn barplots. I created a barplot with four bars that represent percentages on the y axis. I want to add a label on each bar showing the number of observations.

In my code, the first block creates the barplot.

I created the second two blocks of code from examples that I found elsewhere. I get an error message pointing to the row beginning with "medians," and the message says: AttributeError: 'float' object has no attribute 'values'

sns.set_style("whitegrid")
ax = sns.barplot(x=barplot_x, y="trump_margin_pct", 
data=mean_analysis)
sns.palplot(sns.diverging_palette(240, 0))
ax.set(xlabel='Strength of Candidate Support', ylabel='Average Trump 
Margin of Victory/(Loss) (in %)')  
ax.set_title('Average Strength of Candidate Support Across Groups of 
Counties, 2016')

# Calculate number of obs per group & median to position labels
medians = mean_analysis['trump_margin_pct'].median().values
nobs = mean_analysis['trump_margin_pct'].value_counts().values
nobs = [str(x) for x in nobs.tolist()]
nobs = ["n: " + i for i in nobs]

# Add it to the plot
pos = range(len(nobs))
for tick,label in zip(pos,ax.get_xticklabels()):
     ax.text(pos[tick], medians[tick] + 0.03, nobs[tick],
horizontalalignment='center', size='x-small', color='w', 
weight='semibold')

Answer 1

Your approach is almost right. However, you calculate the median and the number of observations over the whole data mean_analysis['trump_margin_pct'] and not over groups. This causes your error. You can use groupby to calculate over groups.

Median:
Simply add groupby to calculate your median.

medians = mean_analysis.groupby(['barplot_x'])['trump_margin_pct'].median().values

Number of obs:
For the number of obervations you have to calculate the aggregated value counts that are grouped. This is how you can do this.

nobs = mean_analysis.groupby(['barplot_x'])['trump_margin_pct'].agg(['count'])
nobs = ["n: " + str(i) for s in nobs.values for i in s]

Example:
I used some dummy data to recreate your example.

import seaborn as sns

sns.set_style("whitegrid")
tips = sns.load_dataset("tips")
ax = sns.barplot(x="day", y="total_bill", data=tips)
ax.set(xlabel='Strength of Candidate Support', ylabel='Average Trump Margin of Victory/(Loss) (in %)')  
ax.set_title('Average Strength of Candidate Support Across Groups of Counties, 2016')

medians = tips.groupby(['day'])['total_bill'].median().values
nobs = tips.groupby(['day'])['total_bill'].agg(['count'])
nobs = ["n: " + str(i) for s in nobs.values for i in s]

pos = range(len(nobs))
for tick,label in zip(pos,ax.get_xticklabels()):
    ax.text(pos[tick], medians[tick] + 0.03, nobs[tick], horizontalalignment='center', size='x-small', color='w', weight='semibold')