text: import dash
  import dash_html_components as html
  import dash_core_components as dcc
  import dash_bootstrap_components as dbc
  from dash.dependencies import Output, Input
  import pandas as pd
  
  app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
  
  poverty_data = pd.read_csv('../data/PovStatsData.csv')
  
  app.layout = html.Div([
      html.H1('Poverty And Equity Database'),
      html.H2('The World Bank'),
      dcc.Dropdown(id='country',
                   options=[{'label': country, 'value': country}
                            for country in poverty_data['Country Name'].unique()]),
      html.Br(),
      html.Div(id='report'),
      html.Br(),
      dbc.Tabs([
         dbc.Tab([
             html.Ul([
                 html.Br(),
                 html.Li('Number of Economies: 170'),
                 html.Li('Temporal Coverage: 1974 - 2019'),
                 html.Li('Update Frequency: Quarterly'),
                 html.Li('Last Updated: March 18, 2020'),
                 html.Li([
                     'Source: ',
                     html.A('https://datacatalog.worldbank.org/dataset/poverty-and-equity-database',
                            href='https://datacatalog.worldbank.org/dataset/poverty-and-equity-database')
                 ])
             ])
  
         ], label='Key Facts'),
          dbc.Tab([
              html.Ul([
                  html.Br(),
                  html.Li('Book title: Interactive Dashboards and Data Apps with Plotly and Dash'),
                  html.Li(['GitHub repo: ',
                           html.A('https://github.com/PacktPublishing/Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash',
                                  href='https://github.com/PacktPublishing/Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash')
                           ])
              ])
          ], label='Project Info')
      ]),
  
  ])
  
  
  @app.callback(Output('report', 'children'),
                Input('country', 'value'))
  def display_country_report(country):
      if country is None:
          return ''
  
      filtered_df = poverty_data[(poverty_data['Country Name']==country) &
                                 (poverty_data['Indicator Name']=='Population, total')]
      population = filtered_df.loc[:, '2010'].values[0]
  
      return [html.H3(country),
              f'The population of {country} in 2010 was {population:,.0f}.']
  
  
  if __name__ == '__main__':
      app.run_server(debug=True)