Waterfall chart pattern in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib pyplot module with the common alias.

Matplotlib

import matplotlib.[1] as plt

Drag options to blanks, or click blank then click option'

Apyplot

Bplot

Ccharts

Dgraph

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'pyplot' causes an import error.

Using 'charts' or 'graph' are not valid matplotlib modules.

The matplotlib.pyplot module is imported as plt to create plots easily.

2fill in blank

medium

Complete the code to create a list of values representing changes for the waterfall chart.

Matplotlib

changes = [100, -30, 20, [1], -10]

Drag options to blanks, or click blank then click option'

A0

B50

C-20

D40

Attempts:

3 left

💡 Hint

Common Mistakes

Using a negative number when a positive change is intended.

Using zero which shows no change.

The value 40 represents a positive change in the waterfall chart.

3fill in blank

hard

Fix the error in the code to correctly calculate the cumulative sums for the waterfall chart.

Matplotlib

cumulative = [sum(changes[:[1]]) for i in range(len(changes))]

Drag options to blanks, or click blank then click option'

Ai+1

Blen(changes)

Ci

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using just 'i' excludes the current element from the sum.

Using 'len(changes)' sums the entire list every time.

Using i+1 includes the current element in the sum for cumulative calculation.

4fill in blank

hard

Fill both blanks to create a waterfall chart using matplotlib with bars and labels.

Matplotlib

plt.bar(range(len(cumulative)), cumulative, color=[1])
plt.xticks(range(len(labels)), [2])
plt.show()

Drag options to blanks, or click blank then click option'

A'blue'

Blabels

C'green'

Dcumulative

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'cumulative' as labels causes an error.

Using a color without quotes causes a syntax error.

The bars are colored blue, and the x-axis ticks use the labels list.

5fill in blank

hard

Fill all three blanks to add a title, label y-axis, and set grid lines on the chart.

Matplotlib

plt.title([1])
plt.ylabel([2])
plt.grid([3])

Drag options to blanks, or click blank then click option'

A"Waterfall Chart"

B"Value Change"

CTrue

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting quotes around strings causes errors.

Using False disables grid lines.

The title is set to 'Waterfall Chart', y-axis label to 'Value Change', and grid lines are enabled with True.

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