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Matplotlibdata~5 mins

Waterfall chart pattern in Matplotlib

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Introduction

A waterfall chart helps you see how a starting value changes step-by-step to reach a final value. It shows increases and decreases clearly.

To show how monthly sales add up to a yearly total.
To explain how different expenses reduce a budget.
To visualize profit changes from revenue to net income.
To track changes in inventory levels over time.
To display stepwise changes in project costs.
Syntax
Matplotlib
import matplotlib.pyplot as plt

# Define data
labels = ['Start', 'Increase', 'Decrease', 'End']
values = [100, 30, -20, 110]

# Calculate cumulative sums for bar positions
cumulative = [0]
for v in values[:-1]:
    cumulative.append(cumulative[-1] + v)

# Plot bars
for i in range(len(values)):
    plt.bar(labels[i], values[i], bottom=cumulative[i])

plt.title('Waterfall Chart')
plt.show()

You create a waterfall chart by stacking bars on top of each other.

The 'bottom' parameter in plt.bar sets where each bar starts vertically.

Examples
Simple data setup with positive and negative changes.
Matplotlib
labels = ['Start', 'Gain', 'Loss', 'End']
values = [200, 50, -30, 220]
Calculate where each bar should start to stack properly.
Matplotlib
cumulative = [0]
for v in values[:-1]:
    cumulative.append(cumulative[-1] + v)
Draw each bar at the correct position to form the waterfall.
Matplotlib
for i in range(len(values)):
    plt.bar(labels[i], values[i], bottom=cumulative[i])
Sample Program

This program shows a waterfall chart with positive and negative changes. Blue bars go up, red bars go down.

Matplotlib
import matplotlib.pyplot as plt

labels = ['Start', 'Sales', 'Returns', 'Marketing', 'End']
values = [1000, 300, -150, -200, 950]

cumulative = [0]
for v in values[:-1]:
    cumulative.append(cumulative[-1] + v)

colors = ['blue' if v >= 0 else 'red' for v in values]

for i in range(len(values)):
    plt.bar(labels[i], values[i], bottom=cumulative[i], color=colors[i])

plt.title('Waterfall Chart Example')
plt.ylabel('Amount')
plt.show()
OutputSuccess
Important Notes

Waterfall charts are not built-in in matplotlib, so you build them by stacking bars.

Use colors to show increases (e.g., blue) and decreases (e.g., red) clearly.

Label bars clearly so viewers understand each step.

Summary

Waterfall charts show step-by-step changes from a start to an end value.

They are made by stacking bars using the 'bottom' parameter in matplotlib.

Use colors and labels to make the chart easy to read.

Practice

(1/5)
1. What is the main purpose of a waterfall chart in data visualization?
easy
A. To plot continuous data over time
B. To display the distribution of data points in categories
C. To show step-by-step changes from a starting value to an ending value
D. To compare multiple variables side by side

Solution

  1. Step 1: Understand waterfall chart concept

    A waterfall chart visually breaks down how an initial value changes through a series of positive and negative steps to reach a final value.
  2. Step 2: Compare with other chart types

    Other charts like histograms or line charts serve different purposes, such as distribution or trends over time, not stepwise changes.
  3. Final Answer:

    To show step-by-step changes from a starting value to an ending value -> Option C
  4. Quick Check:

    Waterfall charts = stepwise changes [OK]
Hint: Waterfall charts show how values add or subtract stepwise [OK]
Common Mistakes:
  • Confusing waterfall charts with line charts
  • Thinking waterfall charts show data distribution
  • Assuming waterfall charts compare unrelated categories
2. Which of the following is the correct way to set the bottom parameter in plt.bar() to create a waterfall effect?
easy
A. Use cumulative sums of previous bars as the bottom values
B. Set bottom to zero for all bars
C. Use random values for bottom to create spacing
D. Set bottom to the maximum value of the dataset

Solution

  1. Step 1: Understand the bottom parameter in bar charts

    The bottom parameter sets where each bar starts vertically. For waterfall charts, bars start where the previous bar ended.
  2. Step 2: Use cumulative sums for correct stacking

    By using cumulative sums of previous values, each bar stacks correctly to show stepwise changes.
  3. Final Answer:

    Use cumulative sums of previous bars as the bottom values -> Option A
  4. Quick Check:

    Bottom = cumulative sums for waterfall [OK]
Hint: Bottom bars stack by adding previous bar heights [OK]
Common Mistakes:
  • Setting bottom always to zero causes overlapping bars
  • Using random bottoms breaks the waterfall flow
  • Setting bottom to max value misplaces bars
3. What will be the output of this code snippet creating a waterfall chart?
import matplotlib.pyplot as plt
values = [100, -30, 20, -10]
cumulative = [100, 70, 90, 80]
plt.bar(range(4), values, bottom=[0, 100, 70, 90], color=['green', 'red', 'green', 'red'])
plt.show()
medium
A. A waterfall chart showing increases and decreases starting at 100
B. A bar chart with all bars starting at zero
C. A stacked bar chart with bars overlapping incorrectly
D. An error because bottom list length does not match values

Solution

  1. Step 1: Analyze the bottom parameter values

    The bottom list [0, 100, 70, 90] correctly positions each bar to start where the previous ended, matching cumulative sums.
  2. Step 2: Check colors and values

    Positive values are green, negative are red, showing increases and decreases clearly in a waterfall style.
  3. Final Answer:

    A waterfall chart showing increases and decreases starting at 100 -> Option A
  4. Quick Check:

    Bottom aligns bars for waterfall effect [OK]
Hint: Check bottom aligns with cumulative sums for correct waterfall [OK]
Common Mistakes:
  • Confusing bottom values causing bars to overlap
  • Ignoring color coding for increases/decreases
  • Assuming bars start all at zero
4. Identify the error in this waterfall chart code:
import matplotlib.pyplot as plt
values = [50, -20, 30]
cumulative = [50, 30, 60]
plt.bar(range(3), values, bottom=[0, 50, 60], color=['green', 'red', 'green'])
plt.show()
medium
A. The bottom list should be [0, 50, 80] because 30 + 50 = 80
B. The bottom list should be [0, 50, 30] to match cumulative sums
C. The color list length does not match values length
D. The values list contains negative numbers which is not allowed

Solution

  1. Step 1: Analyze cumulative sums and bottoms

    The cumulative sums are [50, 30, 60]. The bottoms are [0, 50, 60]. The third bottom should be 30 (cumulative[1]), not 60.
  2. Step 2: Identify the mismatch

    The bottom list does not correctly match the cumulative sums; it should be [0, 50, 30].
  3. Final Answer:

    The bottom list should be [0, 50, 30] to match cumulative sums -> Option B
  4. Quick Check:

    Bottoms = [0] + cumulative[:-1] [OK]
Hint: Bottom bars must start where previous bar ends [OK]
Common Mistakes:
  • Using incorrect cumulative sums for bottom
  • Mismatching color list length
  • Assuming negative values are invalid
5. You want to create a waterfall chart for monthly profit changes: start at 200, then +50, -30, +20, -10. Which code snippet correctly calculates the bottoms for the bars?
hard
A. bottoms = [0, 50, 20, -10, 0]
B. bottoms = [200, 250, 220, 240, 230]
C. bottoms = [200, 0, 0, 0, 0]
D. bottoms = [0, 200, 250, 220, 240]

Solution

  1. Step 1: Calculate cumulative sums stepwise

    Start at 200, then add +50 = 250, then -30 = 220, then +20 = 240, then -10 = 230.
  2. Step 2: Determine bottoms for each bar

    The first bar starts at 0, second at 200, third at 250, fourth at 220, fifth at 240 to show stepwise changes.
  3. Final Answer:

    bottoms = [0, 200, 250, 220, 240] -> Option D
  4. Quick Check:

    Bottoms = previous cumulative sums [OK]
Hint: Bottoms = cumulative sums before each step [OK]
Common Mistakes:
  • Starting bottoms at data values instead of zero
  • Using incorrect cumulative sums
  • Setting all bottoms to zero
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