feat(seaborn): implement bar-basic

plots/seaborn/barplot/bar-basic/default.py

@@ -3,114 +3,35 @@
 Library: seaborn
 """
 
-from typing import TYPE_CHECKING
-
 import matplotlib.pyplot as plt
 import pandas as pd
 import seaborn as sns
 
 
-if TYPE_CHECKING:
-    from matplotlib.figure import Figure
-
-
-def create_plot(
-    data: pd.DataFrame,
-    category: str,
-    value: str,
-    figsize: tuple[float, float] = (10, 6),
-    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,
-) -> "Figure":
-    """
-    Create a basic vertical bar chart for categorical data comparison.
-
-    A fundamental bar chart displaying rectangular bars with heights proportional
-    to their numeric values, ideal for comparing quantities across 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 inches
-        color: Bar fill color
-        edgecolor: Bar edge color
-        alpha: Transparency level for bars (0-1)
-        title: Plot title (optional)
-        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
-        **kwargs: Additional parameters passed to seaborn.barplot
-
-    Returns:
-        Matplotlib Figure object
-
-    Raises:
-        ValueError: If data is empty
-        KeyError: If required columns not found in data
-
-    Example:
-        >>> data = pd.DataFrame({
-        ...     'category': ['A', 'B', 'C'],
-        ...     'value': [10, 20, 15]
-        ... })
-        >>> fig = create_plot(data, 'category', 'value', title='Sample Chart')
-    """
-    # 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}")
-
-    # Create figure
-    fig, ax = plt.subplots(figsize=figsize)
-
-    # Plot data using seaborn barplot
-    sns.barplot(data=data, x=category, y=value, color=color, edgecolor=edgecolor, alpha=alpha, ax=ax, **kwargs)
-
-    # Set y-axis to start at zero for accurate visual comparison
-    ax.set_ylim(bottom=0)
-
-    # Add subtle grid on y-axis only
-    ax.yaxis.grid(True, alpha=0.3)
-    ax.set_axisbelow(True)
-
-    # Labels
-    ax.set_xlabel(xlabel if xlabel is not None else category)
-    ax.set_ylabel(ylabel if ylabel is not None else value)
-
-    # Title
-    if title is not None:
-        ax.set_title(title)
-
-    # Rotate x-axis labels if specified
-    if rotation != 0:
-        plt.xticks(rotation=rotation, ha="right")
-
-    # Layout
-    plt.tight_layout()
-
-    return fig
-
-
-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]}
-    )
-
-    # Create plot
-    fig = create_plot(sample_data, "category", "value", title="Sales by Product", xlabel="Product", ylabel="Sales ($)")
-
-    # Save - ALWAYS use 'plot.png'!
-    plt.savefig("plot.png", dpi=300, bbox_inches="tight")
-    print("Plot saved to plot.png")
+# Data
+data = pd.DataFrame(
+    {"category": ["Product A", "Product B", "Product C", "Product D", "Product E"], "value": [45, 78, 52, 91, 63]}
+)
+
+# Create plot
+fig, ax = plt.subplots(figsize=(16, 9))
+sns.barplot(
+    data=data,
+    x="category",
+    y="value",
+    hue="category",
+    palette=["#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6"],
+    legend=False,
+    ax=ax,
+)
+
+# Labels and styling
+ax.set_xlabel("Category", fontsize=20)
+ax.set_ylabel("Value", fontsize=20)
+ax.set_title("Basic Bar Chart", fontsize=20)
+ax.tick_params(axis="both", labelsize=16)
+ax.yaxis.grid(True, alpha=0.3)
+ax.set_axisbelow(True)
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")