text: import pandas as pd
  import datetime as dt
  
  def search_trends(df):
      # delete any '<' signs for low volume days
      for c in df.select_dtypes(include=['object']).columns[1:]:
          df[c] = df[c].str.replace('<', '')
          df[c] = pd.to_numeric(df[c])
  
      date_col = df.columns[0]
      df[date_col] = pd.to_datetime(df[date_col])
      df.set_index(date_col, inplace=True)
      df_reindexed = df.reindex(pd.date_range(start=df.index.min(),
                                              end=df.index.max() + dt.timedelta(days=6), freq='1D'))
      df = df_reindexed.interpolate(method='linear')
      df = df.round(1)
      df.reset_index(inplace=True)
      df.rename({'index': 'date'}, axis=1, inplace=True)
      return df