import gradio as gr
import pandas as pd
import plotly.express as px

def update_columns(csv_file):
    if csv_file is None:
        return gr.Dropdown(choices=[]), gr.Dropdown(choices=[])
    df = pd.read_csv(csv_file.name)
    numeric_cols = df.select_dtypes(include=['number']).columns.tolist()
    return gr.Dropdown(choices=numeric_cols), gr.Dropdown(choices=numeric_cols)

def create_scatter_plot(csv_file, x_col, y_col):
    if csv_file is None or x_col is None or y_col is None:
        return None, None
    
    df = pd.read_csv(csv_file.name)
    
    # Gradio ScatterPlot için uygun formatta veri hazırla
    return (
        gr.ScatterPlot(
            value=df,
            x=x_col,
            y=y_col,
            tooltip=df.columns.tolist(),
            title="Interactive Scatter Plot",
            color_legend_title="Values",
            interactive=True,
            brush_radius=5
        ),
        df
    )

def get_selected_points(evt: gr.SelectData, df):
    if evt is None or df is None:
        return pd.DataFrame()
    
    # Seçilen indeksleri kullanarak verileri filtrele
    selected_indices = [i["index"] for i in evt.selected]
    return df.iloc[selected_indices]

with gr.Blocks() as app:
    gr.Markdown("## 🔷 Polygon ile Veri Seçimi")
    
    with gr.Row():
        csv_upload = gr.UploadButton(label="CSV Yükle", file_types=[".csv"])
        x_dropdown = gr.Dropdown(label="X Ekseni")
        y_dropdown = gr.Dropdown(label="Y Ekseni")
    
    with gr.Row():
        scatter_plot = gr.ScatterPlot(interactive=True, brush_radius=5)
        selected_table = gr.DataFrame(label="Seçilen Veriler")
    
    df_state = gr.State()
    
    csv_upload.upload(
        fn=update_columns,
        inputs=csv_upload,
        outputs=[x_dropdown, y_dropdown]
    )
    
    x_dropdown.change(
        fn=create_scatter_plot,
        inputs=[csv_upload, x_dropdown, y_dropdown],
        outputs=[scatter_plot, df_state]
    )
    
    y_dropdown.change(
        fn=create_scatter_plot,
        inputs=[csv_upload, x_dropdown, y_dropdown],
        outputs=[scatter_plot, df_state]
    )
    
    scatter_plot.select(
        fn=get_selected_points,
        inputs=df_state,
        outputs=selected_table
    )

if __name__ == "__main__":
    app.launch()