code: import dash
  from dash.dependencies import Input, Output
  from dash import dash_table
  from dash import dcc
  from dash import html
  import pandas as pd
  
  # Import data into pandas
  df = pd.read_csv("data.csv")
  df["Condition"] = df["Condition Category"]
  df = df.drop(["Condition Category", "Missed Prices", "Index", "SKU"], axis=1)
  
  df = df[
      [
          "Brand",
          "Model",
          "Reference",
          "Year",
          "Condition",
          "Papers",
          "Box",
          "Movement",
          "Dimensions",
          "Gender",
          "Case",
          "Bracelet",
          "Crystal",
          "Dial Color",
          "Price",
          "Features",
          "Link",
      ]
  ]
  
  app = dash.Dash(__name__)
  
  money = dash_table.FormatTemplate.money(0)
  # App Layout
  app.layout = html.Div(
      [
          # Title
          html.H1("Watch Data", style={"text-align": "center"}),
          # Dropdowns
          html.Div(
              className="row",
              children=[
                  # First dropdown
                  html.Div(
                      children=[
                          html.Label(["Brand"], style={"text-align": "center"},),
                          dcc.Dropdown(
                              id="brand_dropdown",
                              options=[
                                  {"label": i, "value": i}
                                  for i in df["Brand"].sort_values().unique()
                              ],
                              value=None,
                              clearable=True,
                              searchable=True,
                          ),
                      ],
                      style=dict(width="50%"),
                  ),
                  # Second dropdown
                  html.Div(
                      children=[
                          html.Label(["Model"], style={"text-align": "center"},),
                          dcc.Dropdown(
                              id="model_dropdown",
                              value=None,  # [![enter image description here][1]][1]
                              clearable=True,
                              searchable=True,
                          ),
                      ],
                      style=dict(width="50%"),
                  ),
                  html.Div(
                      children=[
                          html.Label(["Price"], style={"text-align": "center"},),
                          dcc.RangeSlider(
                              id="range_slider",
                              tooltip={"placement": "bottom", "always_visible": True},
                          ),
                      ],
                      style=dict(width="50%"),
                  ),
              ],
              style=dict(display="flex"),
          ),
          html.Br(),
          html.Div(
              [
                  dash_table.DataTable(
                      id="table",
                      filter_action="native",
                      sort_action="native",
                      style_cell={"textAlign": "left", "minWidth": 110, "width": 110},
                      style_table={"minWidth": "100%"},
                      style_cell_conditional=[
                          {"if": {"column_id": "Features"}, "textAlign": "right",},
                          {"if": {"column_id": "Link"}, "textAlign": "right"},
                      ],
                      style_data_conditional=[
                          {
                              "if": {"row_index": "odd"},
                              "backgroundColor": "rgb(220, 220, 220)",
                          }
                      ],
                      style_header={
                          "backgroundColor": "rgb(210, 210, 210)",
                          "color": "black",
                          "fontWeight": "bold",
                      },
                  )
              ]
          ),
      ]
  )
  
  # Connecting Dash Components
  @app.callback(
      [Output(component_id="model_dropdown", component_property="options")],
      [Input(component_id="brand_dropdown", component_property="value")],
  )
  def update_model(brand_selected):
  
      dff = df[df["Brand"] == brand_selected]
      return [[{"label": i, "value": i} for i in dff["Model"].sort_values().unique()]]
  
  
  @app.callback(
      [
          Output(component_id="range_slider", component_property="min"),
          Output(component_id="range_slider", component_property="max"),
          Output(component_id="range_slider", component_property="value"),
      ],
      [
          Input(component_id="brand_dropdown", component_property="value"),
          Input(component_id="model_dropdown", component_property="value"),
      ],
  )
  def update_slider(brand_selected, model_selected):
  
      dff = df[(df["Brand"] == brand_selected) & (df["Model"] == model_selected)]
      return (
          dff["Price"].min(),
          dff["Price"].max(),
          [dff["Price"].min(), dff["Price"].max()],
      )
  
  
  @app.callback(
      [
          Output(component_id="table", component_property="columns"),
          Output(component_id="table", component_property="data"),
      ],
      [
          Input(component_id="brand_dropdown", component_property="value"),
          Input(component_id="model_dropdown", component_property="value"),
          Input(component_id="range_slider", component_property="value"),
      ],
  )
  def update_table(brand_selected, model_selected, range):
      if brand_selected is None and model_selected is None:
          dff = df
      elif model_selected is None:
          dff = df[df["Brand"] == brand_selected]
      else:
          dff = df[
              (df["Brand"] == brand_selected)
              & (df["Model"] == model_selected)
              & (df["Price"] >= range[0])
              & (df["Price"] <= range[1])
          ]
      return (
          [
              {"name": i, "id": i, "hideable": True, "type": "numeric", "format": money}
              if i == "Price"
              else {"name": i, "id": i, "hideable": True}
              for i in dff.columns
          ],
          dff.to_dict("records"),
      )
  
  
  if __name__ == "__main__":
      app.run_server(debug=True)
  
apis: pandas.read_csv