Tables

Tables are the primary output format. A Table is a 2-D grid of styled cells that can be exported to HTML, Excel, a pandas DataFrame, or displayed inline in Jupyter.

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The model.tables namespace

All table methods live on model.tables.

line_items() — full model table

# All line items, names as row labels
model.tables.line_items().show()

# Specific items only
model.tables.line_items(line_items=["revenue", "gross_profit", "net_income"]).show()

# Show label instead of name
model.tables.line_items(include_name=False, include_label=True).show()

# Without the auto-generated Total row
model.tables.line_items(include_total_row=False).show()

line_item() — single item with optional analysis rows

model.tables.line_item("revenue").show()

# Period-over-period % change
model.tables.line_item("revenue", include_percent_change=True).show()

# Cumulative change from base period
model.tables.line_item("revenue", include_cumulative_change=True).show()

# Cumulative % change from base period
model.tables.line_item("revenue", include_cumulative_percent_change=True).show()

# All analysis rows together
model.tables.line_item(
    "revenue",
    include_percent_change=True,
    include_cumulative_change=True,
    include_cumulative_percent_change=True,
).show()

precedents() — formula dependency view

Shows what feeds into a FormulaLine. Precedent items appear above a border; the calculated item is shown in bold below it. Useful for auditing formulas.

model.tables.precedents("net_income").show()

For non-formula items (like FixedLine), only the item itself is shown in bold.

Convenience shortcut from LineItemResult

model["revenue"].table(include_percent_change=True).show()
# equivalent to model.tables.line_item("revenue", include_percent_change=True)

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Custom tables with from_template()

Build any table layout by passing a list of row type instances to from_template(). This is the most flexible approach.

from pyproforma.tables import HeaderRow, LabelRow, ItemRow, BlankRow, LineItemsTotalRow

table = model.tables.from_template([
    HeaderRow(),
    LabelRow(label="Revenue"),
    ItemRow(name="product_revenue"),
    ItemRow(name="service_revenue", bottom_border="single"),
    LineItemsTotalRow(
        line_item_names=["product_revenue", "service_revenue"],
        label="Total Revenue",
        bold=True,
    ),
    BlankRow(),
    LabelRow(label="Expenses"),
    ItemRow(name="cogs"),
    ItemRow(name="operating_expenses", bottom_border="single"),
    LineItemsTotalRow(
        line_item_names=["cogs", "operating_expenses"],
        label="Total Expenses",
        bold=True,
    ),
])
table.show()

Row configs can also be passed as plain dicts with a "row_type" key if you prefer:

template = [
    {"row_type": "header"},
    {"row_type": "label", "label": "Income Statement"},
    {"row_type": "item", "name": "revenue"},
    {"row_type": "blank"},
]
model.tables.from_template(template).show()

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Row types reference

Row type	Key parameters	Description
HeaderRow(col_labels)	col_labels	Column headers. Defaults to "Label".
ItemRow(name, ...)	name, label, bold, top_border, bottom_border, hardcoded_color	Single line item row.
LabelRow(label, bold)	label, bold	Section header spanning all columns.
BlankRow()	—	Empty row for visual spacing.
PercentChangeRow(name)	name	Period-over-period % change.
CumulativeChangeRow(name)	name	Change from base period, in original units.
CumulativePercentChangeRow(name)	name	% change from base period.
LineItemsTotalRow(line_item_names, label, ...)	line_item_names, label, bold, top_border, bottom_border	Sum of named items.
TagTotalRow(tag, label)	tag, label	Sum of all items with a given tag.

ItemRow options

ItemRow(
    name="revenue",
    label="Custom Label",        # overrides the line item's label
    bold=True,
    top_border="single",         # or "double"
    bottom_border="single",
    hardcoded_color="steelblue", # highlights fixed-value periods in that color
)

hardcoded_color is useful for distinguishing input cells from calculated cells in auditing workflows.

Tag-based rows

TagTotalRow sums all line items with the given tag — the list is resolved at render time from the model, so the table stays correct if you add or remove tagged items.

from pyproforma.tables import TagTotalRow

model.tables.from_template([
    HeaderRow(),
    ItemRow(name="product_revenue"),
    ItemRow(name="service_revenue", bottom_border="single"),
    TagTotalRow(tag="revenue", label="Total Revenue", bold=True),
])

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Exporting a table

Every Table object supports the same set of export methods:

table = model.tables.line_items()

table.show()                      # display inline in Jupyter (renders as HTML)
table.to_html()                   # returns HTML string (inline CSS styling)
table.to_bootstrap_html()         # returns HTML string (Bootstrap CSS classes)
table.to_excel("output.xlsx")     # write to Excel with formatting preserved
table.to_dataframe()              # pandas DataFrame with string-formatted values
table.to_styled_dataframe()       # pandas Styler object
table.to_json()                   # JSON string

Excel export

Formatting (bold, borders, background colours, number formats) is fully preserved in the Excel output via openpyxl.

model.tables.line_items().to_excel("income_statement.xlsx")

HTML export

to_html() produces self-contained HTML with inline CSS — safe to embed in any page without a stylesheet.

to_bootstrap_html() produces HTML that relies on Bootstrap classes — used by the Flask explorer app.