Visualize rank changes with a bump chart

Last updated 2020-02-26 Read time 1 min

This bump chart connects quarterly sales ranks with lines. The key is to invert the y-axis so higher ranks sit at the top.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
import numpy as np
import matplotlib.pyplot as plt

quarters = ["Q1", "Q2", "Q3", "Q4"]
brands = ["Alpha", "Bravo", "Charlie", "Delta", "Echo"]
ranks = np.array(
    [
        [1, 2, 3, 3],
        [3, 1, 1, 2],
        [2, 3, 2, 1],
        [4, 4, 5, 4],
        [5, 5, 4, 5],
    ]
)

fig, ax = plt.subplots(figsize=(7, 4))

for brand, rank in zip(brands, ranks):
    ax.plot(quarters, rank, marker="o", linewidth=2, label=brand)

ax.set_ylim(5.5, 0.5)
ax.set_ylabel("Rank")
ax.set_title("Sales rank by brand")
ax.grid(axis="y", alpha=0.2)
ax.legend(loc="upper right", bbox_to_anchor=(1.15, 1))

fig.tight_layout()

plt.show()

Inverting the y-axis makes rank changes easier to read.

Reading tips #

Since smaller ranks mean higher positions, inverting the axis makes the chart more intuitive.
Use line color and markers to distinguish brands, and place the legend on the right to avoid overlaps.
To highlight a specific brand, increase line width or adjust the color.

Slopegraph — Show rank changes between two time points via line slope
Dumbbell Chart — Emphasize differences between two time points with lines and dots