"""Bar chart figure factories for dashboard visualizations."""
from typing import Any
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
def create_ranking_bar(
data: list[dict[str, Any]],
name_column: str,
value_column: str,
title: str | None = None,
top_n: int = 10,
bottom_n: int = 10,
color_top: str = "#4CAF50",
color_bottom: str = "#F44336",
value_format: str = ",.0f",
) -> go.Figure:
"""Create horizontal bar chart showing top and bottom rankings.
Args:
data: List of data records.
name_column: Column name for labels.
value_column: Column name for values.
title: Optional chart title.
top_n: Number of top items to show.
bottom_n: Number of bottom items to show.
color_top: Color for top performers.
color_bottom: Color for bottom performers.
value_format: Number format string for values.
Returns:
Plotly Figure object.
"""
if not data:
return _create_empty_figure(title or "Rankings")
df = pd.DataFrame(data).sort_values(value_column, ascending=False)
# Get top and bottom
top_df = df.head(top_n).copy()
bottom_df = df.tail(bottom_n).copy()
top_df["group"] = "Top"
bottom_df["group"] = "Bottom"
# Combine with gap in the middle
combined = pd.concat([top_df, bottom_df])
combined["color"] = combined["group"].map(
{"Top": color_top, "Bottom": color_bottom}
)
fig = go.Figure()
# Add top bars
fig.add_trace(
go.Bar(
y=top_df[name_column],
x=top_df[value_column],
orientation="h",
marker_color=color_top,
name="Top",
text=top_df[value_column].apply(lambda x: f"{x:{value_format}}"),
textposition="auto",
hovertemplate=f"%{{y}}
{value_column}: %{{x:{value_format}}}",
)
)
# Add bottom bars
fig.add_trace(
go.Bar(
y=bottom_df[name_column],
x=bottom_df[value_column],
orientation="h",
marker_color=color_bottom,
name="Bottom",
text=bottom_df[value_column].apply(lambda x: f"{x:{value_format}}"),
textposition="auto",
hovertemplate=f"%{{y}}
{value_column}: %{{x:{value_format}}}",
)
)
fig.update_layout(
title=title,
barmode="group",
showlegend=True,
legend={"orientation": "h", "yanchor": "bottom", "y": 1.02},
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
xaxis={"gridcolor": "rgba(128,128,128,0.2)", "title": None},
yaxis={"autorange": "reversed", "title": None},
margin={"l": 10, "r": 10, "t": 40, "b": 10},
)
return fig
def create_stacked_bar(
data: list[dict[str, Any]],
x_column: str,
value_column: str,
category_column: str,
title: str | None = None,
color_map: dict[str, str] | None = None,
show_percentages: bool = False,
) -> go.Figure:
"""Create stacked bar chart for breakdown visualizations.
Args:
data: List of data records.
x_column: Column name for x-axis categories.
value_column: Column name for values.
category_column: Column name for stacking categories.
title: Optional chart title.
color_map: Mapping of category to color.
show_percentages: Whether to normalize to 100%.
Returns:
Plotly Figure object.
"""
if not data:
return _create_empty_figure(title or "Breakdown")
df = pd.DataFrame(data)
# Default color scheme
if color_map is None:
categories = df[category_column].unique()
colors = px.colors.qualitative.Set2[: len(categories)]
color_map = dict(zip(categories, colors, strict=False))
fig = px.bar(
df,
x=x_column,
y=value_column,
color=category_column,
color_discrete_map=color_map,
barmode="stack",
text=value_column if not show_percentages else None,
)
if show_percentages:
fig.update_traces(texttemplate="%{y:.1f}%", textposition="inside")
fig.update_layout(
title=title,
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
xaxis={"gridcolor": "rgba(128,128,128,0.2)", "title": None},
yaxis={"gridcolor": "rgba(128,128,128,0.2)", "title": None},
legend={"orientation": "h", "yanchor": "bottom", "y": 1.02},
margin={"l": 10, "r": 10, "t": 60, "b": 10},
)
return fig
def create_horizontal_bar(
data: list[dict[str, Any]],
name_column: str,
value_column: str,
title: str | None = None,
color: str = "#2196F3",
value_format: str = ",.0f",
sort: bool = True,
) -> go.Figure:
"""Create simple horizontal bar chart.
Args:
data: List of data records.
name_column: Column name for labels.
value_column: Column name for values.
title: Optional chart title.
color: Bar color.
value_format: Number format string.
sort: Whether to sort by value descending.
Returns:
Plotly Figure object.
"""
if not data:
return _create_empty_figure(title or "Bar Chart")
df = pd.DataFrame(data)
if sort:
df = df.sort_values(value_column, ascending=True)
fig = go.Figure(
go.Bar(
y=df[name_column],
x=df[value_column],
orientation="h",
marker_color=color,
text=df[value_column].apply(lambda x: f"{x:{value_format}}"),
textposition="outside",
hovertemplate=f"%{{y}}
Value: %{{x:{value_format}}}",
)
)
fig.update_layout(
title=title,
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
xaxis={"gridcolor": "rgba(128,128,128,0.2)", "title": None},
yaxis={"title": None},
margin={"l": 10, "r": 10, "t": 40, "b": 10},
)
return fig
def _create_empty_figure(title: str) -> go.Figure:
"""Create an empty figure with a message."""
fig = go.Figure()
fig.add_annotation(
text="No data available",
xref="paper",
yref="paper",
x=0.5,
y=0.5,
showarrow=False,
font={"size": 14, "color": "#888888"},
)
fig.update_layout(
title=title,
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
xaxis={"visible": False},
yaxis={"visible": False},
)
return fig