Waterfall chart pattern in Matplotlib - Mini Project: Build & Apply

Waterfall Chart Pattern

📖 Scenario: Imagine you work in a company and want to show how different factors contribute to the final profit. A waterfall chart helps visualize how each part adds or subtracts from the total.

🎯 Goal: You will create a waterfall chart using matplotlib to display the step-by-step changes in profit.

📋 What You'll Learn

Create a dictionary with exact revenue and cost values

Create a list of labels for the waterfall steps

Calculate the cumulative values for the waterfall bars

Plot the waterfall chart using matplotlib with correct colors and labels

Display the final waterfall chart

💡 Why This Matters

🌍 Real World

Waterfall charts are used in business to show how different factors contribute to a total, such as profit or budget changes.

💼 Career

Data analysts and business intelligence professionals use waterfall charts to communicate financial and operational insights clearly.

1

Create the data dictionary

Create a dictionary called data with these exact entries: 'Sales': 35000, 'Returns': -5000, 'Marketing': -7000, 'Development': -8000, 'Profit': 15000.

Matplotlib

# Create the data dictionary with exact values
# Your code here

Hint

Use curly braces to create a dictionary with the exact keys and values.

2

Create the labels list

Create a list called labels with these exact strings in order: 'Sales', 'Returns', 'Marketing', 'Development', 'Profit'.

Matplotlib

data = {'Sales': 35000, 'Returns': -5000, 'Marketing': -7000, 'Development': -8000, 'Profit': 15000}
# Create the labels list with exact order
# Your code here

Hint

Use square brackets to create a list with the exact strings in the given order.

3

Calculate cumulative values for the waterfall

Create a list called values that contains the values from data in the order of labels. Then create a list called cumulative that holds the cumulative sums of values starting with 0.

Matplotlib

data = {'Sales': 35000, 'Returns': -5000, 'Marketing': -7000, 'Development': -8000, 'Profit': 15000}
labels = ['Sales', 'Returns', 'Marketing', 'Development', 'Profit']
# Create values list from data using labels order
# Create cumulative list starting with 0
# Your code here

Hint

Use a list comprehension to get values in order. Then use a for loop to build cumulative sums starting from zero.

4

Plot and display the waterfall chart

Import matplotlib.pyplot as plt. Use plt.bar to plot the waterfall bars with labels on x-axis and values as heights. Use bottom=cumulative to stack bars. Color positive bars green and negative bars red. Finally, call plt.show() to display the chart.

Matplotlib

data = {'Sales': 35000, 'Returns': -5000, 'Marketing': -7000, 'Development': -8000, 'Profit': 15000}
labels = ['Sales', 'Returns', 'Marketing', 'Development', 'Profit']
values = [data[label] for label in labels]
cumulative = [0]
for v in values[:-1]:
    cumulative.append(cumulative[-1] + v)

# Import matplotlib.pyplot as plt
# Plot the waterfall bars with colors
# Show the plot
# Your code here

Hint

Use plt.bar with bottom=cumulative and color bars green or red based on positive or negative values. Then call plt.show().

Practice

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