Fix #1332: Add benchmark plots

[graceful-coder]

Fixes #1332

[kdetry]

a clear alternative is below

def _create_plot(df, calibration, autoregressive_n, y_column, title):
    traces = generate_traces(df, calibration, autoregressive_n, y_column)
    yaxis_title = (
        "Predictoor Profit (OCEAN)"
        if y_column == "pdr_profit_OCEAN"
        else "Trader Profit (USD)"
    )
    fig = go.Figure(data=traces, layout=layout)
    fig.update_layout(
        title=f"{df['Model'].iloc[0]} - {title} - {y_column}",
        yaxis_title=yaxis_title,
    )
    fig.show()


def plot_data(filename, calibration, autoregressive_n, y_column):
    # Load data from CSV
    df_without_eth, df_with_eth = load_data_from_csv(filename)
    
    # Plot without ETH
    title_without_eth = "Predictoor Profit Benchmarks (Trained with BTC-USDT Data)"
    _create_plot(df_without_eth, calibration, autoregressive_n, y_column, title_without_eth)
    
    # Plot with ETH
    title_with_eth = "Predictoor Profit Benchmarks (Trained with BTC-USDT & ETH-USDT Data)"
    _create_plot(df_with_eth, calibration, autoregressive_n, y_column, title_with_eth)
    
    ```

[kdetry]

It looks difficult to read. You might want to consider splitting this function.

[kdetry]

In this function, you append everythink to the traces and temp_traces variables are created inside, you append everything into the temp_traces (good), then you extend the traces variable by reversing the the temp_traces but the traces variable is already empty.

Why don't we do like that?

I assumed we have _get_group_data and _create_trace functions, think it like a pseudo-code

   traces = []

    # Grouping the dataframe
    grouped = df.groupby(["Model", "Calibration", "predictoor_ss.aimodel_data_ss.autoregressive_n"])

    # Sorting the groups by the maximum y_column value in descending order
    sorted_groups = (
        grouped[y_column].max().reset_index().sort_values(by=y_column, ascending=False)
    )

    # Generating the traces
    for _, row in sorted_groups.iterrows():
        group_df = _get_group_data(grouped, row)
        color = green_shades.pop(0)  # Get the next available color
        trace = _create_trace(group_df, row, color, y_column)
        traces.append(trace)

    return list(reversed(traces))
    ```

[kdetry]

I am not familiar with the context of this task, but I wanted to make some suggestions about the code.

My codes that I shared could have some syntax errors