1# Bring some raw data.
2frequencies = [6, -16, 75, 160, 244, 260, 145, 73, 16, 4, 1]
3
4freq_series = pd.Series(frequencies)
5
6y_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
7 121740.0, 123980.0, 126220.0, 128460.0, 130700.0]
8
9# Plot the figure.
10plt.figure(figsize=(12, 8))
11ax = freq_series.plot(kind='barh')
12ax.set_title('Amount Frequency')
13ax.set_xlabel('Frequency')
14ax.set_ylabel('Amount ($)')
15ax.set_yticklabels(y_labels)
16ax.set_xlim(-40, 300) # expand xlim to make labels easier to read
17
18rects = ax.patches
19
20# For each bar: Place a label
21for rect in rects:
22 # Get X and Y placement of label from rect.
23 x_value = rect.get_width()
24 y_value = rect.get_y() + rect.get_height() / 2
25
26 # Number of points between bar and label. Change to your liking.
27 space = 5
28 # Vertical alignment for positive values
29 ha = 'left'
30
31 # If value of bar is negative: Place label left of bar
32 if x_value < 0:
33 # Invert space to place label to the left
34 space *= -1
35 # Horizontally align label at right
36 ha = 'right'
37
38 # Use X value as label and format number with one decimal place
39 label = "{:.1f}".format(x_value)
40
41 # Create annotation
42 plt.annotate(
43 label, # Use `label` as label
44 (x_value, y_value), # Place label at end of the bar
45 xytext=(space, 0), # Horizontally shift label by `space`
46 textcoords="offset points", # Interpret `xytext` as offset in points
47 va='center', # Vertically center label
48 ha=ha) # Horizontally align label differently for
49 # positive and negative values.
50
51plt.savefig("image.png")
52