Waterfall Plot Gallery¶

Waterfall plots are used for visualizing how different positive and negative values contribute to a cumulative total. They're perfect for showing incremental changes, financial breakdowns, and performance analysis.

Waterfall plots excel at:

• Financial Analysis: Track how revenues, costs, and profits contribute to totals
• Performance Breakdown: Show how different factors impact overall metrics
• Change Analysis: Visualize step-by-step changes from starting to ending values
• Budget Tracking: Display how various categories affect total budgets

In [ ]:

import matplotlib.pyplot as plt

from pyretailscience.plots import waterfall

import matplotlib.pyplot as plt from pyretailscience.plots import waterfall

Basic Waterfall Chart¶

Create a basic waterfall chart using lists of amounts and labels. Positive values appear as green bars, negative values as red bars.

---

In [ ]:

# Create sample financial data
amounts = [100, 25, -15, 10, -8, 12]
labels = ["Starting Revenue", "New Sales", "Refunds", "Upsells", "Discounts", "Bonuses"]

waterfall.plot(
    amounts=amounts,
    labels=labels,
    title="Revenue Changes",
    y_label="Revenue ($000s)",
    figsize=(10, 6),
)
plt.show()

# Create sample financial data amounts = [100, 25, -15, 10, -8, 12] labels = ["Starting Revenue", "New Sales", "Refunds", "Upsells", "Discounts", "Bonuses"] waterfall.plot( amounts=amounts, labels=labels, title="Revenue Changes", y_label="Revenue ($000s)", figsize=(10, 6), ) plt.show()

Data Label Formats¶

Use data_label_format to control how values are displayed: "absolute", "percentage", or "both".

---

In [ ]:

# Create sample cost breakdown data
amounts = [50, -12, -8, -15, -3, 7]
labels = ["Gross Profit", "Marketing", "Operations", "Staff Costs", "Technology", "Savings"]

waterfall.plot(
    amounts=amounts,
    labels=labels,
    data_label_format="both",  # Show both absolute values and percentages
    title="Cost Impact Analysis",
    y_label="Impact ($000s)",
    figsize=(10, 6),
)
plt.show()

# Create sample cost breakdown data amounts = [50, -12, -8, -15, -3, 7] labels = ["Gross Profit", "Marketing", "Operations", "Staff Costs", "Technology", "Savings"] waterfall.plot( amounts=amounts, labels=labels, data_label_format="both", # Show both absolute values and percentages title="Cost Impact Analysis", y_label="Impact ($000s)", figsize=(10, 6), ) plt.show()

Net Bar Display¶

Use display_net_bar=True to show the final cumulative total as an additional bar.

---

In [ ]:

# Create sample performance metrics
amounts = [20, 8, -5, 12, -3]
labels = ["Q1 Sales", "Q2 Growth", "Q3 Decline", "Q4 Recovery", "Adjustments"]

waterfall.plot(
    amounts=amounts,
    labels=labels,
    display_net_bar=True,  # Show net total bar
    title="Quarterly Performance Summary",
    y_label="Performance Score",
    figsize=(10, 6),
)
plt.show()

# Create sample performance metrics amounts = [20, 8, -5, 12, -3] labels = ["Q1 Sales", "Q2 Growth", "Q3 Decline", "Q4 Recovery", "Adjustments"] waterfall.plot( amounts=amounts, labels=labels, display_net_bar=True, # Show net total bar title="Quarterly Performance Summary", y_label="Performance Score", figsize=(10, 6), ) plt.show()

Net Line Display¶

Use display_net_line=True to show a horizontal line indicating the final total value.

---

In [ ]:

# Create sample budget variance data
amounts = [100, -25, 15, -10, 8, -12]
labels = ["Budget", "Overspend", "Savings", "Emergency", "Rebate", "Fees"]

waterfall.plot(
    amounts=amounts,
    labels=labels,
    display_net_line=True,  # Show net total line
    data_label_format="absolute",
    title="Budget Variance Analysis",
    y_label="Amount ($000s)",
    figsize=(10, 6),
)
plt.show()

# Create sample budget variance data amounts = [100, -25, 15, -10, 8, -12] labels = ["Budget", "Overspend", "Savings", "Emergency", "Rebate", "Fees"] waterfall.plot( amounts=amounts, labels=labels, display_net_line=True, # Show net total line data_label_format="absolute", title="Budget Variance Analysis", y_label="Amount ($000s)", figsize=(10, 6), ) plt.show()

Remove Zero Amounts¶

Use remove_zero_amounts=False to include zero values in the chart (they are excluded by default).

---

In [ ]:

# Create sample data with zero values
amounts = [80, 15, 0, -10, 0, 5, -8]
labels = ["Revenue", "Growth", "No Change", "Returns", "Flat", "Bonus", "Costs"]

waterfall.plot(
    amounts=amounts,
    labels=labels,
    remove_zero_amounts=False,  # Include zero amounts
    title="Complete Change Analysis",
    y_label="Change ($000s)",
    figsize=(10, 6),
)
plt.show()

# Create sample data with zero values amounts = [80, 15, 0, -10, 0, 5, -8] labels = ["Revenue", "Growth", "No Change", "Returns", "Flat", "Bonus", "Costs"] waterfall.plot( amounts=amounts, labels=labels, remove_zero_amounts=False, # Include zero amounts title="Complete Change Analysis", y_label="Change ($000s)", figsize=(10, 6), ) plt.show()