def update_graph(xaxis_column_name, yaxis_column_name,
                 xaxis_type, yaxis_type,
                 year_value):
    dff = df[df['Year'] == year_value]
            
    fig = px.scatter(x=dff[dff['Indicator Name'] == xaxis_column_name]['Value'],
                     y=dff[dff['Indicator Name'] == yaxis_column_name]['Value'],
                     hover_name=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'])
        
    fig.update_layout(margin={'l': 40, 'b': 40, 't': 10, 'r': 0}, hovermode='closest')
    
    fig.update_xaxes(title=xaxis_column_name, 
                     type='linear' if xaxis_type == 'Linear' else 'log') 
    
    fig.update_yaxes(title=yaxis_column_name, 
                     type='linear' if yaxis_type == 'Linear' else 'log') 

    return fig 

def update_graph(xaxis_column_name, yaxis_column_name,
                 xaxis_type, yaxis_type,
                 year_value):
    dff = df[df['Year'] == year_value]

    fig = px.scatter(x=dff[dff['Indicator Name'] == xaxis_column_name]['Value'],
            y=dff[dff['Indicator Name'] == yaxis_column_name]['Value'],
            hover_name=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name']
            )

    fig.update_traces(customdata=dff[dff['Indicator Name'] == yaxis_column_name]['Country Name'])

    fig.update_xaxes(title=xaxis_column_name, type='linear' if xaxis_type == 'Linear' else 'log')

    fig.update_yaxes(title=yaxis_column_name, type='linear' if yaxis_type == 'Linear' else 'log')

    fig.update_layout(margin={'l': 40, 'b': 40, 't': 10, 'r': 0}, hovermode='closest')

    return fig 

def create_time_series(dff, axis_type, title):

    fig = px.scatter(dff, x='Year', y='Value')

    fig.update_traces(mode='lines+markers')

    fig.update_xaxes(showgrid=False)

    fig.update_yaxes(type='linear' if axis_type == 'Linear' else 'log')

    fig.add_annotation(x=0, y=0.85, xanchor='left', yanchor='bottom',
                       xref='paper', yref='paper', showarrow=False, align='left',
                       bgcolor='rgba(255, 255, 255, 0.5)', text=title)

    fig.update_layout(height=225, margin={'l': 20, 'b': 30, 'r': 10, 't': 10})

    return fig 

def build_scatter_trendline(x, y, trendline):
    fig = px.scatter(x=x, y=y, trendline=trendline)
    return fig.data[1] 

def update_figure(selected_year):
    filtered_df = df[df.year == selected_year]
    
    fig = px.scatter(filtered_df, x="gdpPercap", y="lifeExp", 
                     size="pop", color="continent", hover_name="country", 
                     log_x=True, size_max=55)
    
    fig.update_layout(transition_duration=500)

    return fig 

def update_store_data(indicator, country):
    dff = df[df['country'] == country]
    return px.scatter(dff, x='year', y=str(indicator)) 

def scatter(self, x: str = None, y: str = None, color: str = None, **kwargs):
        import plotly.express as px

        if len(self.metric_names) < 2:
            raise ValueError("You need at least 2 metrics to use this plot.")

        df = self.get_wide_df()
        return px.scatter(df, x=x, y=y, color=color, **kwargs)