def METHOD_NAME():
    with st.expander("Detailed correlation"):
        if not isinstance(st.session_state.df_scores, pd.DataFrame):
            st.warning(MSG_NO_DATA)
            return
        df = st.session_state.df_scores
        selected_uploaders = st.session_state.selected_uploaders
        col1, col2, col3 = st.columns(3)
        with col1:
            x = st.selectbox("x", CRITERI_EXT, 1)
            log_x = st.checkbox("x log scale")
        with col2:
            y = st.selectbox("y", CRITERI_EXT, 4)
            log_y = st.checkbox("y log scale")
        with col3:
            st.write(" ")
        if len(selected_uploaders):
            fig = go.Figure()
            for u, uploader in enumerate(selected_uploaders):
                df_uploader = df[df["uploader"] == uploader]
                fig.add_trace(
                    go.Scatter(
                        x=df_uploader[x],
                        y=df_uploader[y],
                        name=uploader,
                        mode="markers",
                        marker_color=TCOLOR[u % len(TCOLOR)],
                    )
                )
        else:
            fig = go.Figure()
            fig.add_trace(
                go.Scatter(
                    x=df[x],
                    y=df[y],
                    mode="markers",
                )
            )
        if log_x:
            fig.update_xaxes(type="log")
        if log_y:
            fig.update_yaxes(type="log")
        fig.update_layout(xaxis=dict(title=x), yaxis=dict(title=y))
        fig.update_xaxes(showline=True, linewidth=2, linecolor="black")
        fig.update_yaxes(showline=True, linewidth=2, linecolor="black")
        st.plotly_chart(fig)