Agent skill
great-tables-5-grouped-rows-and-columns
Sub-skill of great-tables: 5. Grouped Rows and Columns.
Install this agent skill to your Project
npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/_archive/data/analysis/great-tables/5-grouped-rows-and-columns
SKILL.md
5. Grouped Rows and Columns
5. Grouped Rows and Columns
Row Groups:
from great_tables import GT
import pandas as pd
df = pd.DataFrame({
"Region": ["North", "North", "South", "South", "East", "East", "West", "West"],
"Product": ["Widget", "Gadget", "Widget", "Gadget", "Widget", "Gadget", "Widget", "Gadget"],
"Sales": [45000, 32000, 38000, 41000, 52000, 28000, 35000, 39000],
"Units": [450, 160, 380, 205, 520, 140, 350, 195]
})
table = (
GT(df, groupname_col="Region") # Group by Region
.tab_header(
title="Sales by Region and Product",
subtitle="Q4 2025 Performance"
)
.fmt_currency(columns="Sales", currency="USD", decimals=0)
.fmt_integer(columns="Units", use_seps=True)
# Style group labels
.tab_style(
style=[
style.fill(color="#e8e8e8"),
style.text(weight="bold")
],
locations=loc.row_groups()
)
)
table.save("row_groups.html")
Column Spanners:
from great_tables import GT
import pandas as pd
df = pd.DataFrame({
"Product": ["Widget A", "Widget B", "Gadget X"],
"Q1_Sales": [25000, 32000, 18000],
"Q1_Units": [250, 320, 90],
"Q2_Sales": [28000, 35000, 22000],
"Q2_Units": [280, 350, 110],
"Q3_Sales": [31000, 38000, 25000],
"Q3_Units": [310, 380, 125]
})
table = (
GT(df)
.tab_header(title="Quarterly Performance")
# Create column spanners
.tab_spanner(
label="Q1",
columns=["Q1_Sales", "Q1_Units"]
)
.tab_spanner(
label="Q2",
columns=["Q2_Sales", "Q2_Units"]
)
.tab_spanner(
label="Q3",
columns=["Q3_Sales", "Q3_Units"]
)
# Rename columns
.cols_label(
Q1_Sales="Sales",
Q1_Units="Units",
Q2_Sales="Sales",
Q2_Units="Units",
Q3_Sales="Sales",
Q3_Units="Units"
)
# Format numbers
.fmt_currency(columns=["Q1_Sales", "Q2_Sales", "Q3_Sales"], currency="USD", decimals=0)
.fmt_integer(columns=["Q1_Units", "Q2_Units", "Q3_Units"], use_seps=True)
)
table.save("column_spanners.html")
Nested Groups:
from great_tables import GT
import pandas as pd
df = pd.DataFrame({
"Division": ["Consumer", "Consumer", "Consumer", "Enterprise", "Enterprise", "Enterprise"],
"Category": ["Electronics", "Home", "Fashion", "Software", "Hardware", "Services"],
"Product": ["Phones", "Furniture", "Apparel", "Cloud", "Servers", "Consulting"],
"Revenue": [150, 45, 78, 220, 180, 95],
"Growth": [0.12, 0.05, -0.02, 0.25, 0.08, 0.15]
})
table = (
GT(df, groupname_col="Division", rowname_col="Category")
.tab_header(
title="Business Unit Performance",
subtitle="Annual Revenue (Millions USD)"
)
.fmt_currency(columns="Revenue", currency="USD", decimals=0)
.fmt_percent(columns="Growth", decimals=1)
)
table.save("nested_groups.html")
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