Firstly freq_series.plot returns an axis not a figure so to make my answer a little more clear I've changed your given code to refer to it as ax rather than fig to be more consistent with other code examples.
You can get the list of the bars produced in the plot from the ax.patches member. Then you can use the technique demonstrated in this matplotlib gallery example to add the labels using the ax.text method.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Bring some raw data.
frequencies = [6, 16, 75, 160, 244, 260, 145, 73, 16, 4, 1]
# In my original code I create a series and run on that,
# so for consistency I create a series from the list.
freq_series = pd.Series.from_array(frequencies)
x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
121740.0, 123980.0, 126220.0, 128460.0, 130700.0]
# Plot the figure.
plt.figure(figsize=(12, 8))
ax = freq_series.plot(kind='bar')
ax.set_title('Amount Frequency')
ax.set_xlabel('Amount ($)')
ax.set_ylabel('Frequency')
ax.set_xticklabels(x_labels)
rects = ax.patches
# Make some labels.
labels = ["label%d" % i for i in xrange(len(rects))]
for rect, label in zip(rects, labels):
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width() / 2, height + 5, label,
ha='center', va='bottom')
This produces a labeled plot that looks like:
