feat(plotly): implement bar-basic

plots/plotly/bar/bar-basic/default.py

@@ -3,123 +3,30 @@
 Library: plotly
 """
 
-from typing import TYPE_CHECKING
-
 import pandas as pd
 import plotly.graph_objects as go
 
 
-if TYPE_CHECKING:
-    pass
-
-
-def create_plot(
-    data: pd.DataFrame,
-    category: str,
-    value: str,
-    figsize: tuple[int, int] = (1600, 900),
-    color: str = "steelblue",
-    edgecolor: str = "black",
-    alpha: float = 0.8,
-    title: str | None = None,
-    xlabel: str | None = None,
-    ylabel: str | None = None,
-    rotation: int = 0,
-    **kwargs,
-) -> go.Figure:
-    """
-    Create a basic vertical bar chart for categorical data comparison.
-
-    A fundamental bar chart that displays rectangular bars with heights
-    proportional to the values they represent. Each bar corresponds to
-    a category, making it ideal for comparing quantities across discrete
-    categories.
-
-    Args:
-        data: Input DataFrame containing the data to plot.
-        category: Column name for category labels (x-axis).
-        value: Column name for numeric values (bar heights).
-        figsize: Figure size as (width, height) in pixels. Defaults to (1600, 900).
-        color: Bar fill color. Defaults to "steelblue".
-        edgecolor: Bar edge/outline color. Defaults to "black".
-        alpha: Transparency level for bars (0-1). Defaults to 0.8.
-        title: Plot title. Defaults to None.
-        xlabel: X-axis label. Defaults to column name if None.
-        ylabel: Y-axis label. Defaults to column name if None.
-        rotation: Rotation angle for x-axis labels in degrees. Defaults to 0.
-        **kwargs: Additional parameters passed to go.Bar.
-
-    Returns:
-        Plotly Figure object containing the bar chart.
-
-    Raises:
-        ValueError: If data is empty.
-        KeyError: If required columns are not found in data.
-
-    Example:
-        >>> data = pd.DataFrame({
-        ...     'category': ['A', 'B', 'C', 'D'],
-        ...     'value': [45, 78, 52, 91]
-        ... })
-        >>> fig = create_plot(data, 'category', 'value', title='Sales by Product')
-    """
-    # Input validation
-    if data.empty:
-        raise ValueError("Data cannot be empty")
-
-    for col in [category, value]:
-        if col not in data.columns:
-            available = ", ".join(data.columns)
-            raise KeyError(f"Column '{col}' not found. Available: {available}")
-
-    # Set default labels from column names
-    x_label = xlabel if xlabel is not None else category
-    y_label = ylabel if ylabel is not None else value
-
-    # Create figure
-    fig = go.Figure()
-
-    # Add bar trace
-    fig.add_trace(
-        go.Bar(
-            x=data[category],
-            y=data[value],
-            marker={"color": color, "opacity": alpha, "line": {"color": edgecolor, "width": 1}},
-            **kwargs,
-        )
-    )
-
-    # Update layout with styling
-    fig.update_layout(
-        title={"text": title, "x": 0.5, "xanchor": "center"} if title else None,
-        xaxis={"title": {"text": x_label, "font": {"size": 14}}, "tickangle": -rotation, "tickfont": {"size": 12}},
-        yaxis={
-            "title": {"text": y_label, "font": {"size": 14}},
-            "tickfont": {"size": 12},
-            "rangemode": "tozero",
-            "showgrid": True,
-            "gridwidth": 1,
-            "gridcolor": "rgba(128, 128, 128, 0.3)",
-        },
-        template="plotly_white",
-        width=figsize[0],
-        height=figsize[1],
-        showlegend=False,
-        margin={"l": 80, "r": 40, "t": 80 if title else 40, "b": 80},
-    )
-
-    return fig
+# Data
+data = pd.DataFrame(
+    {"category": ["Product A", "Product B", "Product C", "Product D", "Product E"], "value": [45, 78, 52, 91, 63]}
+)
 
+# Create figure
+fig = go.Figure()
 
-if __name__ == "__main__":
-    # Sample data for testing
-    sample_data = pd.DataFrame(
-        {"category": ["Product A", "Product B", "Product C", "Product D", "Product E"], "value": [45, 78, 52, 91, 63]}
-    )
+fig.add_trace(go.Bar(x=data["category"], y=data["value"], marker_color="#306998"))
 
-    # Create plot
-    fig = create_plot(sample_data, "category", "value", title="Sales by Product")
+# Layout
+fig.update_layout(
+    title={"text": "Basic Bar Chart", "font": {"size": 20}, "x": 0.5, "xanchor": "center"},
+    xaxis_title="Category",
+    yaxis_title="Value",
+    template="plotly_white",
+    font={"size": 16},
+    xaxis={"tickfont": {"size": 16}},
+    yaxis={"tickfont": {"size": 16}},
+)
 
-    # Save
-    fig.write_image("plot.png", width=1600, height=900, scale=2)
-    print("Plot saved to plot.png")
+# Save as PNG (4800 × 2700 px)
+fig.write_image("plot.png", width=1600, height=900, scale=3)