Plotly bar plot : Customize legend label based on values in pandas column

📊 Plotly Python
1

I have a dataframe with positive and negative values in one column. I am using plotly barplot, and I’d like customize legend labels based on the value.

Here’s a mock pandas DataFrame:

df = pd.DataFrame({'Date': [07-2020, 08-2020, 09-2020, 10-2020],
                   'Value': [3, -2, 4, -1] })

df["Color"] = np.where(df["Value"]<0, 'rgb(0,0,255)', 'rgb(255,0,0)')
df["Name"] = np.where(df["Value"]<0, 'Low', 'High')


    fig = go.Figure(

        data=[

              go.Bar(
                        x=df["Date"],
                        y=df["Value"],
                        color=df['Name'],
                        marker_color=df['Color']
                    ),

              ],

        layout=go.Layout(

        

            xaxis=dict(
                tickangle=60,
                tickfont=dict(family="Rockwell", color="crimson", size=14)
            ),

            yaxis=dict(
                title="Net Change",
                showticklabels=True
            ),

            barmode="stack",

        )
    )

How do I add legend labels Low when value is negative and High when positive?