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Sub-skill of great-tables: 4. Conditional Formatting.
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| name | great-tables-4-conditional-formatting |
| description | Sub-skill of great-tables: 4. Conditional Formatting. |
| version | 1.0.0 |
| category | data-analysis |
| type | reference |
| scripts_exempt | true |
Color Scales:
from great_tables import GT
from great_tables import style, loc
from great_tables.data import countrypops
import pandas as pd
# Sample heatmap data
df = pd.DataFrame({
"Month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
"North": [85, 92, 88, 95, 91, 97],
"South": [72, 78, 81, 75, 82, 88],
"East": [90, 85, 92, 89, 94, 91],
"West": [68, 75, 79, 82, 78, 85]
})
table = (
GT(df)
.tab_header(title="Regional Performance Scores")
# Apply color scale to data columns
.data_color(
columns=["North", "South", "East", "West"],
palette=["#FF6B6B", "#FFEB3B", "#4CAF50"], # Red -> Yellow -> Green
domain=[60, 100]
)
)
table.save("color_scale.html")
Conditional Icons:
from great_tables import GT, html
import pandas as pd
df = pd.DataFrame({
"Metric": ["Revenue", "Users", "Conversion", "NPS"],
"Current": [1250000, 85000, 3.2, 72],
"Previous": [1180000, 78000, 3.5, 68],
"Change_Pct": [5.9, 9.0, -8.6, 5.9]
})
def trend_icon(value):
"""Return trend icon based on value."""
if value > 0:
return html('<span style="color: green;">▲</span>') # Up arrow
elif value < 0:
return html('<span style="color: red;">▼</span>') # Down arrow
else:
return html('<span style="color: gray;">▶</span>') # Right arrow
# Add trend column
df["Trend"] = df["Change_Pct"].apply(trend_icon)
table = (
GT(df)
.tab_header(title="Key Metrics Dashboard")
.fmt_number(columns="Current", use_seps=True, decimals=0)
.fmt_number(columns=, use_seps=, decimals=)
.fmt_percent(columns=, decimals=, scale_values=)
)
table.save()
Bar Charts in Cells:
from great_tables import GT, html
import pandas as pd
df = pd.DataFrame({
"Product": ["Alpha", "Beta", "Gamma", "Delta", "Epsilon"],
"Sales": [85000, 120000, 65000, 95000, 110000],
"Target": [100000, 100000, 100000, 100000, 100000]
})
def create_bar(value, max_value=150000):
"""Create inline bar chart."""
width = min(value / max_value * 100, 100)
color = "#4CAF50" if value >= 100000 else "#FF9800"
return html(f'''
<div style="background: #eee; width: 100px; height: 20px;">
<div style="background: {color}; width: {width}%; height: 100%;"></div>
</div>
''')
df["Progress"] = df["Sales"].apply(create_bar)
table = (
GT(df)
.tab_header(title="Sales Progress by Product")
.fmt_number(columns="Sales", use_seps=True, decimals=0)
.fmt_number(columns="Target", use_seps=True, decimals=0)
)
table.save("bar_charts.html")